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Excel Visualization: A Guide to Clear Data Presentation for Beginners

I once struggled with dull data tables.

Numbers clustered in rows and columns become a blur. But with Excel visualization , you can empower your audience to make informed decisions based on the data presented. Excel charts and graphs replace chaos, revealing patterns and trends.

Convey ideas efficiently with the right visual. It’s not just about creating a chart; it’s about making data understandable and engaging.

In this article, I’ll guide you step-by-step on transforming your Excel data into insightful visuals.

Let’s get started!

Table of Contents

Understanding the Basics of Excel Visualization

Excel provides various visualization options, whether 2D or 3D versions, standard, stacked, or 100% stacked options. It’s all about finding the right fit that best represents your data and message.

The Excel Charting Interface

Let’s start with creating a chart in Excel.

When you click on the Insert tab in Excel, you’ll see various chart types that you can use to visualize your data.

The Excel charting interface provides a wide range of options, from line and area charts to bar and column charts. When you click on a chart, the ‘ Chart Tools ’ contextual tab provides additional features for customizing your charts.

Types of Data for Visualization

Excel visualization data can be broadly categorized into numerical, categorical, and time-series data.

• Numerical data includes values that can be measured, such as sales figures or temperature readings.
• Categorical data includes information such as names, labels, or groups.
• Time-series data involves values measured over time, such as stock prices or website traffic.

Excel offers different chart types depending on your data type.

Selecting the Right Chart Type

Selecting the right chart type is half the battle for effective data visualization in Excel.

Pie charts are best for part-to-whole comparisons. Use line charts for time series or trends. Bar or column charts are the most suitable for categorical comparisons.

However, consider more advanced chart types for more complex data sets.

Scatter plots are excellent for correlation analysis , while histograms and box plots are ideal for distribution analysis of quantitative data.

It’s all about understanding your data and determining the best way to display it.

Steps for Visualizing Data in Excel – Creating Basic Charts

Creating basic charts in Excel is a fundamental skill for anyone looking to present data in a visual format.

Excel offers a variety of chart types, each with unique properties and use cases. The key to successful chart creation in Excel is understanding these different chart types and knowing how to present your data most effectively with them.

Organizing Your Data

Before you dive into creating Excel charts, it is crucial to organize your data correctly . 

Well-organized data will make the charting process easier and the resulting charts more meaningful. Ensure your data is clean, error-free, and arranged clearly and logically.

This will make it easier to select the data for your charts and create visuals that effectively communicate your data analysis results.

Pie and Donut Chart

Pie charts are popular for showing the proportion of different categories within a whole. While visually appealing, they are often misused and can lead to misleading interpretations.

Generally, they are most effective when comparing a few categories representing parts of a whole.

On the other hand, donut charts are a variation of pie charts with a hole in the middle (as the name implies!). Like pie charts, they can display multiple data series, but they should be used sparingly.

To create a pie chart in Excel:

• Select the data you want to visualize
• From the “ Insert ” tab, choose “ Pie ” from the chart options.
• You can customize your chart by changing the colors, adding labels, and adjusting other settings in the “ Format Chart Area ” pane.

Here’s a video guide on how to create a donut chart:

Line and Area Chart

Line and area charts are handy when dealing with time-series data . These charts plot data points on a graph and connect them with a line, allowing you to see trends over time. 

Check out this video for a step-by-step guide on how to create a line chart:

One of the business essentials when working with line and area charts is customizing the axis and gridlines. This can help make your chart more readable and meaningful .

The “ Format Axis ” pane allows you to customize the axis labels, adjust the scale, and add gridlines.

Column and Bar Graph

Bar and column charts are Excel’s most commonly used chart types. They are excellent for comparing different categories of data.

While bar charts and column charts are often used interchangeably, there is a difference: A bar chart presents data horizontally , while a column chart presents data vertically . This distinction can influence how easily your audience interprets the chart.

You can also choose between a stacked or clustered bar and column chart layout.

In a stacked chart , data series are stacked on each other, while in a clustered chart , they are placed side by side.

To create a bar or column chart:

• Select the data
• Then choose either “Bar” or “Column” from the chart options in the “ Insert ” tab
• Remember to format the chart and the axis labels to make the chart easier to understand

Advanced Charting Techniques

In this section, I’ll describe how to present complex data in a visually appealing and easily understandable format. Since each dataset is unique, treat these charts as ideas for meaningfully presenting your data.

Combination Charts

This type of chart combines the features of line and column charts, allowing you to present mixed data more comprehensively.

For example, when you have a target and actual data for comparison , a combination chart can be the perfect tool for visualization.

Clicking the Chart Design tab on the ribbon allows you to change the chart type and create a customized combination chart.

This allows you to have your target values in columns and the actual values marked along the line, which provides a clearer visualization of your data.

Trendlines and Data Analysis

Another essential feature of Excel charts is the ability to add trendlines. These can be linear, polynomial, or moving average trendlines.

A trendline graphically displays trends in your data , and you can extend it beyond the actual data to predict future values.

Along with trendlines, interpreting R-squared values is also crucial in data analysis. This will help you understand the relationship between your dependent and independent variables, thus enhancing your analysis results.

Check out our detailed how-to post on adding trendlines to Excel charts .

Conditional Formatting in Charts

Conditional formatting is another advanced charting technique in Excel that can enhance your data visualization. You can also add data bars, color scales, and icon sets.

These features allow you to customize your charts based on certain conditions, making it easier for your audience to understand your data. Applying these formatting options enables you to create more engaging and visually appealing charts for your data presentation.

Creating a Tornado Chart in Excel

Tornado charts are particularly effective when comparing and contrasting different variables . A well-crafted tornado chart can help you visualize how changes in several factors can impact a specific outcome – for example, the impact of inflation on NPV and IRR results.

Here’s a video showing you how to create a tornado chart:

Designing a Funnel Chart in Excel

Funnel Charts in Excel are highly effective tools for monitoring sales processes or any other process that narrows down over time.

Here are two quick methods for designing funnel charts in Excel:

Building a Waffle Chart in Excel

Waffle charts, also known as square pie or waffle bar charts, are a great way to visualize individual data points compared to the whole data set. They are a fun and engaging way to present percentages or proportions.

Here is a simple method for creating waffle charts:

Data Visualization Tips – Enhancing Chart Aesthetics

The aesthetics of your Excel chart play a significant role in how effectively your data is communicated.

A visually appealing chart is easier to understand and engages your audience. Enhancing chart aesthetics involves working with various chart elements and features, such as colors, styles, and data labels.

Adding data labels, for instance, provides additional information on your chart, making it easier to interpret.

Besides, you can customize the chart’s colors and styles to match your presentation theme or company branding.

Check out this post for more information on good dashboard design principles .

Working with Chart Elements

Working with chart elements can significantly improve the readability and effectiveness of your data visualization.

Some key chart elements you can manipulate include titles, legends, and data labels.

• Data labels provide additional context to your data and can be customized to suit your chart
• Modify axis labels and gridlines to adjust their appearance and improve readability. Check out this video on how to add gridlines to your Excel charts:

These chart elements can enhance your aesthetic appeal and make your data easier to interpret.

Customizing Chart Colors and Styles

Spicing up your Excel charts is easier than you think.

The ‘ Chart Design ‘ tab in the Excel ribbon allows you to alter your charts’ aesthetics significantly.

Navigate to the ‘ Chart Styles ‘ section, and you’ll see various styles for your chart. 

Looking for a bit more customization? No problem! Simply click the ‘ Change Colors ‘ dropdown and choose a color scheme.

You can use Excel’s preset color schemes or create a custom color palette for brand consistency. Minor visual changes can significantly affect your chart’s overall look and feel.

3D Charts and Effects

Adding a third dimension to your charts can make them pop . But be careful.

While 3D effects can add a specific wow factor, they can also lead to misinterpretations of your data if they are not used properly.

To add 3D effects to your charts, click the ‘ Chart Styles ‘ and choose a style with 3D effects. 

Remember, though, that 3D effects should be used sparingly and only when they can enhance the understanding of the data. Overuse of these effects can lead to cluttered, confusing charts. When it comes to 3D effects, less is often more .

Advanced Excel Graphics

Beyond the basic charts, Excel offers advanced graphics capabilities to take your data presentation to the next level.

This includes using Sparklines, shapes, and icons, among other features.

Sparklines are mini-charts within individual cells, each representing a row of data. They give a quick snapshot of trends, helping you understand your data at a glance.

Excel offers line, column, and win/loss types of Sparklines that you can add with the Quick Analysis tool.

Using Shapes and Icons

Remember to appropriately format these shapes and icons to convey the right message and not distract from the data.

Portraying a Story Through Data

Excel visualization is not just about creating charts or diagrams; it’s about telling a story with your data. This is where the concept of data storytelling comes in.

It’s about using visualization tools to highlight key points and trends in your data, making it easier for your audience to understand and absorb.

It’s not unlike creating a plot in a novel where rows and columns of data are the characters, and the chart is the narrative arc. Every element should convey your story effectively and compellingly, from simple bar charts to intricate trend analysis.

Exporting and Sharing Your Visualizations

Once you’ve created your data visualization in Excel, it’s important to know how to share it! This involves exporting the visual representation of data in a format that others can easily access.

Whether you’re sharing a simple bar graph or a complex infographic, the export method will depend on the intended use of the chart/graphic.

This process can be as simple as saving your chart as an image or embedding Excel visuals in PowerPoint presentations and documents.

Saving Charts as Images

One of the simplest ways to share visualizations is by saving them as images .

To do this, right-click the chart and select ‘Save as Picture.’ Several image formats are available, each with its uses.

For instance, JPEG is great for photographic images, while PNG is ideal for images with transparent backgrounds. However, it’s important to consider the resolution of your image. High resolution is crucial for clear, crisp images, especially if they’re intended for print.

Embedding Excel Visuals in Presentations and Documents

Embedding them in presentations and documents is another way to share your Excel visualizations.

This can be done in two ways: linking and embedding .

• Linking refers to connecting the original Excel file and the document where it’s inserted. Any changes made to the original file will automatically update in the document (assuming the link isn’t broken ).
• Embedding involves inserting a copy of the chart into the document. While this won’t update automatically, it ensures that the chart will always be available, regardless of the status of the original file.

Both methods have advantages and should be chosen based on your specific needs.

Frequently Asked Questions

What are some common mistakes for beginners to avoid in data visualization with excel.

Common mistakes include overcrowding the chart with too much data, using inappropriate chart types, neglecting to label axes or data points clearly, and choosing colors or styles that reduce readability.

What are the best practices for presenting Excel data visually to a non-technical audience?

Focus on simplicity and clarity .

Use straightforward chart types, avoid technical jargon, and highlight key takeaways. Ensure your charts are well-labeled, and use annotations or callouts to draw attention to important data points.

What are some resources to learn more about Excel visualization? 

For more tips and tricks, visit my YouTube channel . Alternatively, look at Chandoo’s training, where I learned many excellent dashboard design ideas.

Can Excel visualization help in career development?

Absolutely! Proficiency in Excel visualization is a valuable skill in many industries.

It’s especially relevant in fields like data science, finance, marketing, and others involving large amounts of data. Effectively communicating data through graphical representation can give you a significant advantage in your professional journey.

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10 Tips for Visually Analyzing and Presenting Data in Excel

Excel data analysis for dummies.

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Here are some concrete suggestions about how you can more successfully use charts as data analysis tools in Excel and how you can use charts to more effectively communicate the results of the data analysis that you do.

Use the right chart type

What many people don’t realize is that you can make only five data comparisons in Excel charts.

If you decide or can figure out which data comparison you want to make, choosing the right chart type is very easy:

Pie, doughnut, or area: Use for part-to-whole data comparison.

Bar, cylinder, cone, or pyramid: Use for a whole-to-whole data comparison.

Line or column: Use for a time-series data comparison.

Scatter or bubble: Use for a correlation data comparison in Excel.

Surface: Use for a geographic data comparison.

Use your chart message as the chart title

Chart titles are commonly used to identify the organization that you’re presenting information to or perhaps to identify the key data series that you’re applying in a chart. A better and more effective way to use the chart title is to make it into a brief summary of the message that you want your chart to communicate.

Beware of pie charts

Pie charts are very inferior tools for visually understanding data and for visually communicating quantitative information.

Almost always, information that appears in a pie chart would be better displayed in a simple table.

Pie charts possess several debilitating weaknesses:

You’re limited to working with a very small set of numbers.

Pie charts aren’t visually precise.

With pie charts, you’re limited to a single data series.

Consider using pivot charts for small data sets

For small data sets, pivot charts can work very well. The key thing to remember is that a pivot chart, practically speaking, enables you to plot only a few rows of data.

However, if you create a cross-tabulation that shows only a few rows of data, try a pivot chart. Here is a cross-tabulation in a pivot table form.

Here is a cross-tabulation in a pivot chart form. For many people, the graphical presentation here shows the trends in the underlying data more quickly, more conveniently, and more effectively.

Avoid 3-D Charts

The problem with 3-is that the extra dimension, or illusion, of depth reduces the visual precision of the chart. With a 3-D chart, you can’t as easily or precisely measure or assess the plotted data.

Here is a simple column chart.

Here is the same information in a 3-D column chart. If you look closely at these two charts, you can see that it’s much more difficult to precisely compare the two data series in the 3-D chart and to really see what underlying data values are being plotted.

Charts often too easily become cluttered with extraneous and confusing information.

Never use 3-D pie charts

Pie charts are really weak tools for visualizing, analyzing, and visually communicating information. Adding a third dimension to a chart further reduces its precision and usefulness. When you combine the weakness of a pie chart with the inaccuracy and imprecision of three-dimensionality, you get something that is usually misleading.

Be aware of the phantom data markers

A phantom data marker is some extra visual element on a chart that exaggerates or misleads the chart viewer. Here is a silly little column chart that was created to plot apple production in the state of Washington.

Notice that the chart legend, which appears off to the right of the plot area, looks like another data marker. It’s essentially a phantom data marker it exaggerates the trend in apple production.

Use logarithmic scaling

With logarithmic scaling of your value axis, you can compare the relative change in data series values. This line chart doesn’t use logarithmic scaling of the value axis.

This is the same information in the same chart type and subtype, but the scaling of the value axis was changed to use logarithmic scaling.

To tell Excel that you want to use logarithmic scaling of the value axis, follow these steps:

Right-click the value (Y) axis and then choose the Format Axis command from the shortcut menu that appears.

When the Format Axis dialog box appears, select the Axis Options entry from the list box.

To tell Excel to use logarithmic scaling of the value (Y) axis, simply select the Logarithmic Scale check box and then click OK.

Don’t forget to experiment

The suggestions you fund here are really good guidelines to use. But you ought to experiment with your visual presentations of data. Sometimes by looking at data in some funky, wacky, visual way, you gain insights that you would otherwise miss.

If you regularly use charts and graphs to analyze information or if you regularly present such information to others in your organization, reading one or more of these books will greatly benefit you.

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How to Create Powerful Presentations Using Excel

TL;DR Transform raw Excel data into compelling presentations with our 15-step guide. Learn to set objectives, clean data, select appropriate charts, and incorporate interactive elements for engaging and effective presentations. Enhance your storytelling and data visualization skills to create powerful, dynamic presentations.

Introduction

Sometimes, we receive data in Excel and are tasked with transforming this raw data into powerful presentations. Excel is not just for spreadsheets; its powerful data manipulation capabilities make it an excellent tool for creating presentations, especially when dealing with large datasets or when you need to display data-driven insights dynamically. This guide provides 15 detailed steps to help you turn Excel data into compelling presentations effectively.

Detailed Steps to Create Engaging Presentations Using Excel

• Set Your Objectives
• Clearly define the purpose of your presentation.
• Identify the core message you want to convey.
• Understand your audience's needs and expectations.
• Set actionable goals for what your presentation should achieve.
• Align your presentation structure to these objectives for maximum impact.
• Organize Your Data
• Separate raw data and analysis into different sheets for clarity.
• Group similar data together to facilitate easier analysis.
• Use named ranges to make data references clearer.
• Organize data chronologically or categorically based on the presentation flow.
• Maintain a clean and organized data setup to avoid confusion during visualization.
• Clean Your Data
• Remove any irrelevant or redundant data.
• Correct all errors and inconsistencies in the data set.
• Use Excel functions like TRIM to clean text data.
• Standardize data formats (dates, numbers, etc.) across your dataset.
• Check for and resolve any missing data issues.
• Select Appropriate Charts
• Choose charts that best represent the nature of your data.
• Consider the impact of different chart types on data interpretation.
• Use bar or column charts for comparisons among categories.
• Opt for line charts to display trends over time.
• Employ pie charts to show proportions within a whole.
• Utilize Advanced Chart Options
• Explore Excel’s specialized charts like radar or waterfall for complex data.
• Customize chart colors, labels, and legends for better readability.
• Use trend lines or data labels to add meaningful insights to charts.
• Employ dual-axis charts for comparing different datasets on the same chart.
• Utilize 3D charts to enhance visual appeal, but use sparingly to avoid distortion of data.
• Link Data Dynamically
• Connect charts to live data sources to ensure real-time data updates.
• Use Excel’s Data Model to integrate data from multiple sources.
• Apply dynamic formulas like INDEX and MATCH to make charts responsive.
• Employ data validation techniques to ensure data integrity.
• Set up dynamic ranges to auto-adjust as data grows.
• Incorporate Interactive Elements
• Use slicers and timelines for interactive data segmentation.
• Implement PivotTables to summarize large datasets dynamically.
• Add form controls like buttons and sliders to make the presentation interactive.
• Design your slides to respond to user inputs or selections.
• Ensure interactive elements are intuitive and clearly contribute to the narrative.
• Design a Dashboard
• Combine multiple data visualizations on a single screen for a unified view.
• Ensure each component of the dashboard provides unique but complementary information.
• Use consistent design elements across all visuals for a cohesive look.
• Make sure the dashboard is easy to read and navigate.
• Include interactive elements in the dashboard to engage the audience.
• Automate with Macros
• Use macros to streamline repetitive tasks, enhancing presentation efficiency.
• Automate data updates and visual adjustments with VBA scripts.
• Write macros that help navigate through the presentation smoothly.
• Ensure macros are tested and error-free to avoid glitches during the presentation.
• Provide button triggers for macros on the Excel interface for easy access.
• Narrative Flow
• Structure your presentation to tell a coherent story.
• Begin with an introduction that outlines key points.
• Build the body of your presentation with data-driven analysis.
• Conclude with a strong, data-supported conclusion.
• Transition smoothly between sections to keep your audience engaged.
• Maintain Design Consistency
• Use a uniform color scheme, font style, and layout across all slides.
• Apply consistent formatting rules for all data visuals.
• Design templates that can be reused for future presentations.
• Ensure that the visual design supports the data narrative.
• Avoid overdesigning that may distract from the data itself.
• Test and Iterate
• Conduct dry runs to test the flow and functionality of your presentation.
• Invite feedback from peers to refine content and design.
• Make iterative adjustments based on practical trials and feedback.
• Test on different devices to ensure compatibility.
• Finalize the presentation after thorough testing and refinement.
• Prepare Backups
• Save copies of your presentation in multiple formats.
• Ensure you have both digital and physical backups available.
• Regularly update your backups to reflect the latest changes.
• Store backups in different locations to mitigate risk.
• Consider cloud storage options for easy access and additional security.
• Have a contingency plan in place in case of technical issues.
• Add Supporting Notes
• Embed comments within your Excel cells to provide additional context.
• Use the notes section for personal reminders during the presentation.
• Prepare detailed explanations that can be referred to if questions arise.
• Keep notes concise and relevant to the data being presented.
• Ensure all notes are hidden from the audience view but accessible to you.
• Peer Review
• Share your presentation with colleagues or experts for feedback.
• Encourage constructive criticism to refine your presentation.
• Consider diverse perspectives to enhance the presentation’s appeal.
• Implement suggested changes that align with your objectives.
• Conduct a final review session to ensure all feedback has been addressed.

Mastering Excel for presentations transcends basic data visualization—it transforms how we communicate and persuade with data. This expertise not only empowers you to deliver insights in a compelling manner but also enhances your strategic influence within your organization or client base. Through the careful integration of data, design, and narrative, your presentations become not just informative but transformative, inspiring action and facilitating decision-making. The steps outlined in this guide equip you with the tools to turn complex data into captivating stories that resonate deeply with your audience. Embrace these practices to elevate your presentations from mundane to memorable, ensuring that every data point not only informs but also inspires and engages.

Are you ready to leverage your Excel data into powerful narratives that not only inform but also inspire and persuade? Visit INK PPT today and discover how our expert design services can amplify your presentation impact. At INK PPT, we don't just design slides; we craft stories that engage, inform, and motivate your audience to action. Elevate your presentations with us—where data meets design and storytelling.

Discover how we can create magic in your communication

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Visualizing Data in Excel: A Comprehensive Guide

By   STC

July 15, 2023

Explore the diverse data visualization possibilities in Excel that aid in analyzing and interpreting your data effectively.

Introduction

Welcome to our comprehensive guide on visualizing data in Excel. In this article, we will delve into the world of data visualization and provide you with valuable insights on how to create compelling visual representations of your data using Excel. Whether you are a beginner or an experienced Excel user, this guide will equip you with the knowledge and techniques to effectively communicate your data through visually appealing charts and graphs.

Why Data Visualization Matters

Data visualization is a powerful tool that enables us to make sense of complex datasets. It allows us to identify patterns, trends, and outliers that might not be immediately apparent in raw data. Visualizing data in Excel not only enhances our understanding of the information at hand but also enables us to communicate our findings to others in a clear and concise manner.

Getting Started with Excel Charts

• Selecting the Right Chart Type Choosing the appropriate chart type is crucial for effectively representing your data. Excel offers a wide range of chart options, including bar charts, line charts, pie charts, scatter plots, and more. Consider the nature of your data and the message you want to convey when selecting the most suitable chart type.
• Formatting and Customization Excel provides extensive formatting and customization options to refine the appearance of your charts. From adjusting axis labels to modifying colors and styles, these features allow you to create visually appealing charts that align with your brand or presentation requirements.
• Adding Data Labels and Annotations To enhance the clarity of your visualizations, Excel enables you to add data labels and annotations. These labels provide additional context and make it easier for your audience to interpret the information being presented. You can include axis labels, data point labels, and explanatory text to further enrich your charts.

Advanced-Data Visualization Techniques

• Creating PivotCharts PivotCharts are a powerful feature in Excel that allows you to visualize data from pivot tables. By summarizing and aggregating data, pivot tables provide a comprehensive overview that can be transformed into dynamic and interactive charts. Utilizing PivotCharts enables you to explore and analyze complex datasets with ease.
• Utilizing Advanced Charting Features Excel offers advanced charting features that can take your visualizations to the next level. From trendlines and error bars to 3D charts and sparklines, these tools allow you to add depth and sophistication to your data representations. Experimenting with these features can help you create visually striking charts that captivate your audience.

Best Practices for Effective Data Visualization

To ensure your data visualizations have maximum impact, keep the following best practices in mind:

• Simplify and Declutter Avoid cluttering your charts with excessive information or unnecessary embellishments. Focus on the key message you want to convey and remove any elements that distract from that message. Remember, simplicity is key when it comes to effective data visualization.
• Use Color Strategically Colors can evoke emotions and draw attention to specific areas of your charts. Use color strategically to highlight important data points or to group related information. However, be mindful of accessibility considerations and ensure that your color choices are accessible to individuals with color vision deficiencies.
• Tell a Story with Your Data Data visualization is not just about presenting numbers; it’s about telling a story. Structure your visualizations in a way that guides your audience through a narrative. Start with an introduction, present the main findings, and conclude with a clear takeaway or call to action.

In conclusion, mastering the art of visualizing data in Excel can significantly enhance your ability to analyze and communicate complex information. By selecting the right chart types, utilizing advanced techniques, and following best practices, you can create visually compelling representations that effectively convey your data’s story. We hope this comprehensive guide has provided you with the knowledge and inspiration to create outstanding data visualizations in Excel. Start exploring the power of data visualization today and unlock new insights from your data.

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About the author

We are passionate about the power of visual storytelling and believe that charts can convey complex information in a captivating and easily understandable way. Whether you're a data enthusiast, a business professional, or simply curious about the world around you, this page is your gateway to the world of data visualization.

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Data Visualization in Excel

Ever felt overwhelmed by a massive spreadsheet filled with data, wondering how to make sense of it all?

In today's fast-paced environment, being able to quickly visualize and interact with your data is crucial for making informed decisions.

Here's how you can transform a sea of data into an insightful and interactive dashboard in Excel, all within 20 minutes.

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Dashboard design tips video, download completed excel dashboard & data, design tips guide to creating excel dashboards, additional resources.

For step-by-step instructions check out the video below.

Enter your email address below to download the sample workbook.

1. Prepare Your Data and Dashboard Sheet

Before diving into the creation of the dashboard, I'll start by organizing my data. For this example, I used a sales dataset spanning 12 months, categorized by seller, product, state, sales, and profit.

I formatted the data in an Excel Table to allow for automatic updating of my dashboard.

I prepared five PivotTables to support the charts I plan to insert on the dashboard.

Get up to speed with PivotTables here .

2. Designing Your Dashboard Canvas

The foundation of a good dashboard is its design. Begin by setting the dashboard's background color.

Click the arrow at the intersection of the row and column labels to select the whole sheet, then apply the cell fill color.

I'm using a dark indigo, providing a visually appealing contrast for my charts and data elements. This is on a newly inserted blank sheet in my Excel workbook.

3. Inserting Titles and Subtitles

To provide clear understanding, insert a main title, "Sales Performance Dashboard," and a subtitle indicating the time frame, "January - December 2024."

4. Highlighting Key Figures

At the top of your dashboard, highlight important figures like total sales, profit, and profit margin. Microsoft 365 users can use icons (available free for from within Excel) next to each figure to visually represent their meaning - a telemarketer for sales and a money symbol for profit. These icons not only draw attention but also aid in quick comprehension.

I'll come back to the pie chart for the profit margin.

5. Creating and Positioning Charts

The visual heart of your dashboard will be the charts:

- Sales by Month: A column chart showing trends over time.

- Sales by Salesperson and Category: Two bar charts providing insights into sales distribution.

- Map Chart: Though Excel doesn't directly support creating map charts from PivotTables, you can trick it by copying the PivotTable data as values and then inserting a filled map chart.

- Profit Margin: I created an icon from a pie chart. I removed the legend and title and made it very small to fit beside the headline figure:

6. Interactivity with Slicers

To allow users to interact with the dashboard, insert Slicers for different categories like seller, category, and state. This lets users customize the view to see exactly what's relevant to them.

Ensure these slicers are formatted to match the dashboard's color theme and are positioned strategically for easy access.

Connect the Slicers to each dashboard through the Report Connections menu (right-click > Report Connections):

Check out this post on custom formatting Slicers .

7. Finishing Touches

With all elements in place, use shapes and formatting tricks to give each visual element its own distinct space, enhancing overall readability.

I added a rounded rectangle shape behind each chart and slicer in a shade slightly lighter than the background:

For the border, apply an inner shadow:

Creating an effective dashboard doesn't have to be a time-consuming process. With some preparation and the right techniques, you can turn your raw data into a dynamic tool for exploration and decision-making in no time.

If you're interested in diving deeper into dashboard creation, consider taking my Excel Dashboard course .

This transformation from raw data to an interactive dashboard not only simplifies data analysis but also empowers users to make more informed, data-driven decisions quickly and efficiently. Whether you're in business, academia, or any field that relies on data, mastering these skills can significantly enhance your productivity and analytical capabilities.

CIMA qualified Accountant with over 25 years experience in roles such as Global IT Financial Controller for investment banking firms Barclays Capital and NatWest Markets.

Mynda has been awarded Microsoft MVP status every year since 2014 for her expertise and contributions to educating people about Microsoft Excel.

Mynda teaches several courses here at MOTH including Excel Expert , Excel Dashboards , Power BI , Power Query and Power Pivot .

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Creating Data Visualizations in Excel: What to Keep in Mind

• 14 Oct 2021

One of the most valuable and abundant resources businesses have at their disposal is data. With vast amounts of data being generated every minute of every day, the insights gleaned can inform virtually every business decision —often resulting in favorable outcomes.

There are many data visualization tools on the market designed for creating illustrations for business purposes. Fortunately, one of the most popular and easy-to-use options is likely already installed on your computer: Microsoft Excel.

If you don’t have access to Microsoft Excel, consider using free options like Google Sheets for a similar, albeit more limited, experience.

While Excel isn’t visualization software, it’s a versatile, powerful tool for professionals of all levels who want to analyze and illustrate datasets. Here are the types of data visualizations you can create in Excel and the steps involved in doing so, along with some tips to help you along the way.

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Types of Data Visualizations in Excel

There are different data visualization techniques you can employ in Excel, depending on the data available to you and the goal you’re trying to achieve, including:

• Area charts
• Scatter plots

Other visualization techniques can be used to illustrate large or complex data sets. These include:

• Gantt charts
• Highlight tables
• Bullet graphs

More advanced visualizations, such as those that include graphic elements like geographical heat maps, may not be possible to create in Excel or require additional tools.

Related: 6 Data Visualization Examples to Inspire Your Own

How to Create Data Visualizations in Excel

The steps involved in creating data visualizations in Excel depend on the type of graph or chart you choose. For basic visualizations, the process is largely the same. More complex datasets and illustrations may require additional steps.

To craft a data visualization in Excel, start by creating an organized spreadsheet. This should include labels and your final dataset.

Then, highlight the data you wish to include in your visual, including the labels. Select “insert” from the main menu and choose the type of chart or graph you’d like to create. Once you’ve made your selection, the visualization will automatically appear in your spreadsheet.

Right-click on the chart or graph to edit details, such as the title, axes labels, and colors. Doing so will open a pop-up or side panel that includes options to add a legend, adjust the scale, and change font styles and sizes.

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Tips for Creating Visualizations in Excel

1. choose the right type of visualization.

To create an effective data visualization, it’s critical to choose the right type of chart or graph. Consider the type of data you’re using, the size of your dataset, and your intended audience.

A mismatch between the type of data being leveraged and the visual used to present it can be detrimental to viewers’ understanding of the information. Whether you’re working with qualitative or quantitative data, for example, impacts how you should display the information.

Your intended audience also influences how simplified or complex your illustration should be. For instance, when presenting to a large audience or high-level stakeholders, it’s helpful to distill your presentation to highlight key trends and insights rather than individual data points.

2. Remove Irrelevant or Inaccurate Data

Ultimately, your visualization’s quality is only as good as that of the data you use. For this reason, it’s important to clean data after it’s been collected to remove any irrelevant or inaccurate information. This process is often referred to as data wrangling or data cleaning.

Failure to thoroughly clean data prior to using it can be detrimental to its integrity and lead to inaccurate or misleading data visualizations .

Related: What Is Data Integrity & Why Does It Matter?

3. Provide Context For the Visualization

If necessary, include a key or legend and additional context to help viewers make sense of your illustration.

For example, consider a heatmap that shows the frequency of COVID-19 infections in a location over a specific period. To form a clear understanding of the information being presented, viewers need to know details such as the period being examined, the data source, and what each color means.

This context is important because it helps viewers interpret the information being displayed. Without a key clearly defining the coloring system, for instance, it would be virtually impossible to know what each color indicates, rendering the heatmap useless.

4. Tell A Story

Finally, the key to crafting a compelling visualization is to use data to tell a story. If the data illustrates a trend or supports a hypothesis, your visualization should make that clear. After all, the purpose of visualizations is to present findings in a way that’s easy for viewers to digest and understand.

Telling a story not only makes your visualization more interesting and engaging but also aids in data-driven decision-making . In addition, it helps stakeholders understand the essence of your findings and, in turn, informs their decision-making processes .

Making Data-Backed Business Decisions

Data visualization is a powerful tool when it comes to addressing business questions and making informed decisions. Learning how to create effective illustrations can empower you to share findings with key stakeholders and other audiences in a manner that’s engaging and easy to understand.

You don’t have to be in an analytics or data science role to take advantage of data visualizations. Professionals of all levels and backgrounds can develop data skills to more effectively communicate within their organizations and make informed decisions.

Are you interested in improving your analytical skills? Learn more about Business Analytics —one of the three courses that comprise CORe —which teaches you how to apply analytical techniques in Excel to solve real business problems.

About the Author

Excel for Data Visualization in Business Presentations

Excel is a versatile tool for data visualization in business presentations, allowing professionals to create impactful visual representations of data insights. With various chart types, pivot tables, and conditional formatting, Excel enables the transformation of complex data into easily understandable visuals. These visualizations can be seamlessly integrated into business presentations to communicate trends, comparisons, and key findings effectively. Excel's familiarity and accessibility make it a valuable asset for professionals to display data-driven information, enabling informed decision-making and enhancing the overall impact of business presentations.

Introduction

In the fast-paced world of business, effective data visualization is paramount for conveying insights, making informed decisions, and presenting complex information in a clear and compelling manner. Microsoft Excel, a ubiquitous spreadsheet software, offers powerful tools for data visualization in business presentations. With its array of charts, graphs, and interactive features, Excel empowers professionals to transform raw data into visually engaging representations that resonate with stakeholders.

Excel's charting capabilities allow users to create a wide range of visualizations, such as bar charts, line graphs, pie charts, and scatter plots , to highlight trends, comparisons, and patterns in data. PivotTables offer a dynamic way to summarize and analyze large datasets, providing a quick overview of complex information.

Conditional formatting in Excel enables users to apply custom styles and colors to data cells, emphasizing significant data points and adding visual context to tables and charts. This feature helps in creating heat maps, traffic light indicators, and color scales for intuitive data interpretation.

Excel's seamless integration with other Microsoft Office applications, like PowerPoint, makes it convenient to embed visualizations directly into business presentations. Furthermore, Excel's widespread usage in the business world ensures that data visualization remains accessible and familiar to users across different organizations.

Understanding Excel’s Data Visualization Features

1. Excel’s chart types and options

• Column Charts: Ideal for comparing data across categories. Users can choose from clustered, stacked, or 100% stacked column charts.
• Bar Charts: Similar to column charts but with the x and y-axis roles reversed. Suitable for displaying data horizontally.
• Line Charts: Useful for showing trends over time or continuous data. Users can create single or multiple series line charts.
• Pie Charts: Effective for illustrating the proportion of different categories in a dataset. Users can also create 3D pie charts for added visual appeal.
• Area Charts: Suitable for displaying data trends over time, similar to line charts but with the area beneath the lines shaded.
• Scatter Plots: Ideal for visualizing the relationship between two variables. Useful for detecting correlations or outliers.
• Bubble Charts: Similar to scatter plots, but with an additional dimension represented by varying bubble sizes. Useful for displaying three sets of data.
• Radar Charts: Suitable for comparing multiple quantitative variables. Users can create spider-like graphs for easy comparison.
• Stock Charts: Designed for visualizing stock market data, including high, low, open, and close prices.
• Surface Charts: Useful for representing three-dimensional data sets, displaying the data in a 3D surface format.

Excel's chart options allow users to customize chart elements, such as titles, data labels, legends, and axes. Users can adjust colors, fonts, and styles to match their presentation or branding. Additionally, Excel's pivot tables provide a dynamic way to summarize and analyze large datasets, offering a quick overview of complex information.

2. Customization capabilities for charts and graphs

Excel provides extensive customization capabilities for charts and graphs, enabling users to tailor visualizations to their specific needs and preferences. Here are the key customization options available:

• Chart Types: Excel offers a wide range of chart types, including column, bar, line, pie, area, scatter , and more. Users can choose the most suitable chart type for their data representation.
• Chart Elements: Users can customize various chart elements, such as chart titles, data labels, axis titles, legends, and data tables , to provide context and enhance data understanding.
• Data Series Formatting: Customize individual data series by selecting specific colors, line styles, markers, or patterns , making it easier to differentiate data sets within the chart.
• Axis Settings: Adjust axis labels, scales, and units to ensure that the chart displays data accurately and meaningfully.
• Conditional Formatting: Use conditional formatting to apply specific colors or styles to data points based on predefined rules or thresholds, highlighting important data trends or outliers.
• Chart Styles and Themes: Apply predefined chart styles and themes or create custom styles to match the overall look and feel of the presentation or report.
• 3D Rotation and Perspective (for 3D Charts): Users can modify the 3D rotation and perspective of 3D charts to change the viewing angle and enhance visual impact.
• Trendlines and Error Bars: Add trendlines to visualize data trends and regression analysis. Include error bars to display data variability and uncertainty.
• Secondary Axes: Incorporate secondary axes to plot different data series with different scales on the same chart, enabling better comparisons.
• Chart Animation (for 3D Maps): When using Power Map (3D Maps), create time-based animations to visualize data changes over time.

3. Integration with other Excel features

Excel's integration with other features enhances its functionality and enables a seamless workflow for data analysis and visualization. Here are some key integration points:

• PivotTables: PivotTables allow users to summarize, analyze, and pivot data in a dynamic and flexible manner. Excel charts can be directly linked to PivotTables, updating automatically when the underlying data changes.
• Power Query: Power Query allows users to clean, transform, and reshape data from various sources before importing it into Excel. This ensures that the data is in the desired format for visualization.
• Power Pivot: Power Pivot is an Excel add-in that enables users to work with large datasets and create more complex data models. It allows for the creation of relationships between tables and advanced calculations.
• Conditional Formatting: Conditional formatting can be applied to Excel charts to highlight specific data points based on predefined criteria, making it easier to identify trends or outliers.
• Slicers and Filters: Slicers and filters can be added to Excel charts to allow users to interactively explore and analyze data, focusing on specific subsets of information.
• Data Validation: Data validation rules can be set up in Excel to ensure that data entered into charts is accurate and conforms to predefined criteria.
• VBA and Macros: Excel's Visual Basic for Applications (VBA) enables users to automate tasks and create customized solutions for data analysis and charting.
• Power BI Integration: Power BI, a business intelligence tool from Microsoft, can be used to create interactive dashboards and reports with Excel data and charts.
• SharePoint and OneDrive: Excel workbooks with charts and data can be saved to SharePoint or OneDrive for easy collaboration and sharing with others.

Selecting the Right Chart Type According to Your Data

Common chart types for business presentations

When selecting the right chart type for your data in business presentations using Excel, it's crucial to choose the chart that best represents and highlights the patterns and relationships within your data. Here are some common chart types that are widely used in business presentations:

• Column Chart: Suitable for comparing data across different categories or time periods. Clustered or stacked column charts can be used for visualizing multiple data series.
• Bar Chart: Similar to column charts, but with the axes reversed. Ideal for displaying data horizontally, especially for long category names.
• Line Chart: Effective for showing trends over time or continuous data. Useful for illustrating patterns and changes in data values.
• Pie Chart: Ideal for representing proportions or percentages of a whole. Best for displaying data with few categories.
• Area Chart: Similar to line charts, but the area beneath the lines is filled. Suitable for showing data trends over time and comparing multiple data series.
• Scatter Plot: Useful for displaying the relationship between two variables, identifying correlations or outliers.
• Bubble Chart: A variation of the scatter plot, with an additional dimension represented by varying bubble sizes. Suitable for visualizing three sets of data.
• Radar Chart: Effective for comparing multiple quantitative variables. Useful for showing performance across different categories.
• Waterfall Chart: Ideal for illustrating how values contribute to an overall total, particularly in financial analyses.
• Gantt Chart: Useful for project management, showing task schedules, durations, and dependencies.

Column and bar charts for comparisons

Column and bar charts are excellent choices for visualizing and comparing data in Excel. Both chart types are ideal for displaying categorical data and showcasing the relationships between different data sets. Here's when to use column and bar charts:

Column Chart:

• Use column charts when the categories you want to compare are positioned along the horizontal axis (x-axis).
• The vertical bars represent the values of each category, making it easy to compare the magnitude of data points.
• Column charts are effective for displaying data with time-based or numerical categories on the x-axis.
• They are especially suitable for showing comparisons between discrete data points or for time-series data.
• Use bar charts when the categories you want to compare are positioned along the vertical axis (y-axis).
• The horizontal bars represent the values of each category, allowing for quick comparison between data points.
• Bar charts are effective for comparing data with text-based or non-numeric categories on the y-axis.
• They are particularly useful when you have long category names that might not fit well along the x-axis in a column chart.

Line charts for trends and patterns

Line charts are ideal for visualizing trends and patterns in data over time or any continuous variable. Here's how to use line charts in Excel to represent trends:

• Organize Data: Arrange your data in columns or rows, with the time or continuous variable in one column and the corresponding data values in another column.
• Select Data: Highlight the data range you want to visualize, including both the time or continuous variable and the corresponding data values.
• Insert Line Chart: Go to the "Insert" tab on the Excel ribbon, click on the "Line Chart" icon in the Charts group, and choose the desired line chart subtype (e.g., Line, Stacked Line, or Line with Markers).
• Customize Chart: After inserting the line chart, customize it by adding chart titles, data labels, axis labels, and other elements to make it more informative and presentable.
• Format Data Series: Format the line and marker styles, colors, and sizes according to your preference or to match the overall theme of your presentation.

Pie and doughnut charts for proportions

Pie and doughnut charts are ideal for representing proportions and percentages in Excel. They visually display how individual components contribute to the whole, making them effective for showcasing data with distinct categories. Here's how to use pie and doughnut charts in Excel:

• Select the data range containing the categories and corresponding values.
• Go to the "Insert" tab on the Excel ribbon.
• Click on the "Pie Chart" button in the "Charts" group and choose the desired pie chart style.
• Excel will generate a pie chart with slices representing each category's proportion of the whole.
• Doughnut Chart:
• The doughnut chart is a variation of the pie chart with a hole in the center.
• Follow the same steps as for the pie chart to create the initial chart.
• Once the pie chart is generated, right-click on it and select "Change Chart Type."
• Choose the doughnut chart style from the options available.

Scatter plots for relationships and correlations

Here's how scatter plots are used for data analysis:

• Relationships: Scatter plots help identify relationships between two variables. If the data points tend to form a pattern that follows a particular direction (positive or negative slope), it indicates a linear relationship between the variables. For example, in a scatter plot of sales revenue (y-axis) against advertising spend (x-axis), a positive slope suggests that higher advertising spend is associated with higher revenue.
• Correlations: Scatter plots assist in determining the strength and direction of correlations between variables. A clustered group of data points indicates a strong correlation, while a dispersed group suggests a weak or no correlation. The line of best fit, or regression line, can be added to the scatter plot to quantify the correlation and predict future values.
• Outliers: Scatter plots help identify outliers, which are data points that significantly deviate from the general pattern of the data. These outliers may indicate errors in data collection or represent unique cases worth investigating.
• Clusters and Patterns: Scatter plots can reveal clusters or patterns within the data, highlighting distinct groups or trends.

Data Characteristics and Message Clarity

• Data Structure: Consider the data's structure, such as categorical, numerical, or time-series, to determine the most suitable chart type.
• Data Distribution: Understand the data distribution to choose between bar/column charts for comparing categories or line charts for showing trends over time.
• Relationships: Use scatter plots to visualize relationships between two variables or bubble charts to include a third dimension of data.
• Hierarchical Data: Represent hierarchical data using tree maps or sunburst charts to show the breakdown of data categories.

Audience preferences and comprehension

• Familiarity: Consider the audience's familiarity with chart types and their preferences for understanding data visually.
• Complexity: Choose a chart type that strikes a balance between simplicity and complexity, ensuring the audience can grasp the information easily.
• Accessibility: Opt for chart types that are accessible to all, including individuals with visual impairments, by providing alternative text and proper labeling.

Presentation context and objectives

• Presentation Medium: Consider the medium in which the chart will be presented, such as print, digital, or projection, as it may impact the chart's size and resolution.
• Presentation Time: Choose chart types that allow for quick data interpretation during short presentations or detailed analysis for longer discussions.
• Objectives: Align the chart type with the presentation's objectives, whether it's to compare data, show trends, or display proportions.

Creating Effective Visualizations in Excel

1. Designing visually appealing charts

• Choose the Right Chart Type: Select a chart type that best represents your data and conveys the intended message clearly. Consider options like bar/column charts for comparisons, line charts for trends, pie charts for proportions, and scatter plots for relationships.
• Simplify and Focus: Avoid cluttering your charts with unnecessary elements. Keep the design clean and focus on the key data points to prevent visual distractions.
• Color Selection: Use a consistent color scheme that complements your data and aligns with your presentation or company branding. Avoid using too many colors and ensure color choices are accessible to all audiences.
• Fonts and Text: Choose clear and readable fonts for axis labels, titles, and data labels. Ensure that the text size is appropriate for the chart size and doesn't obstruct the data.
• Gridlines and Axes: Utilize gridlines and axes to guide data interpretation, but keep them subtle to avoid overwhelming the chart.
• Data Labels and Annotations: Include data labels or annotations to provide context and aid in data interpretation. Avoid cluttering the chart with excessive labels.
• Chart Titles: Use descriptive and concise titles to highlight the chart's main message and focus.
• Visual Hierarchy: Organize data elements in a logical visual hierarchy. Highlight the most important data points with appropriate formatting.

2. Choosing appropriate colors and fonts

• Consistency: Maintain consistency in color usage across charts and graphs within the same presentation to create a cohesive and professional look.
• Data Contrast: Use contrasting colors for data points and categories to ensure clear differentiation and easy identification of data trends.
• Color Meanings: Be mindful of color meanings and associations. For example, use green for positive values, red for negative values, and neutral colors for neutral or insignificant data.
• Avoid Overuse: Avoid using too many colors in a single chart, as it can make the visualization cluttered and confusing. Stick to a limited color palette for a clean and organized appearance.
• Colorblind Accessibility: Ensure that the colors you choose are easily distinguishable for individuals with color vision deficiencies. Test your visualizations using colorblind simulation tools.
• Readability: Choose fonts that are easy to read, even at smaller sizes. Sans-serif fonts like Arial, Calibri, or Verdana are generally more readable on screens and presentations.
• Consistency: Use a consistent font throughout your visualizations and the entire presentation for a professional and unified look.
• Hierarchy: Use font sizes and styles to create a visual hierarchy, emphasizing important elements like titles, headers, and data labels.
• Avoid Decorative Fonts: Avoid using overly decorative or stylized fonts that may distract from the data and reduce readability.
• Accessibility: Ensure that the font size and style provide sufficient contrast against the background for individuals with visual impairments.

3. Adjusting chart elements

• Chart Title: Add a descriptive and concise chart title that provides context and summarizes the chart's purpose.
• Data Labels: Include data labels on data points or bars to display specific values, aiding in data interpretation.
• Axes Titles: Label the x-axis and y-axis with clear titles to indicate the data represented on each axis.
• Legends: Add a legend to identify different data series or categories in the chart, especially useful for multi-series charts.
• Gridlines: Adjust gridlines to enhance readability and aid in data comparisons.
• Axis Scaling: Adjust the axis scaling to ensure that data points are evenly distributed and displayed accurately.
• Trendlines: Add trendlines to visualize data trends and make predictions, especially useful in line charts and scatter plots.
• Color and Style: Choose appropriate colors and styles for chart elements to make the visualization visually appealing and consistent.
• Formatting Data Series: Customize data series with different colors, line styles, and markers for better distinction.

4. Using data labels and callouts for clarity

Data labels

• Display Values: Add data labels to data points in charts to show exact values directly on the data markers, making it easy for viewers to interpret the data.
• Series Names: Include data series names in the chart to help identify different data categories and understand the context of each data point.
• Customization: Customize data labels by changing font size, color, position, and format to ensure they are clear and visually appealing.
• Annotations: Use callouts to annotate specific data points or data regions with additional information, explanations, or insights, providing valuable context to the audience.
• Arrows and Leader Lines: Connect callouts to the corresponding data points using arrows or leader lines to visually establish the relationship between the callout and the data.

5. Enhancing visualizations with Excel’s formatting options

• Colors and Themes: Choose appropriate colors and themes that complement the data and match the overall presentation style. Excel's predefined color schemes and themes provide consistency across visualizations.
• Font Styles and Sizes: Use clear and legible font styles and sizes for chart titles, axis labels, and data labels. Consistent font choices help maintain a professional look.
• Data Labels and Callouts: Display data labels on data points to provide context and clarify values. Use callouts or data cards to highlight specific data points or add supplementary information.
• Conditional Formatting: Apply conditional formatting to color-code data points based on predefined rules, making it easier to identify patterns and outliers.
• Legends and Data Tables: Position legends and data tables appropriately to avoid clutter and ensure ease of data interpretation.
• Axis Formatting: Customize axis labels, titles, and scales to better communicate data trends and insights. Consider using a secondary axis for different data series with different scales.
• Chart Titles and Captions: Create clear and descriptive chart titles and captions to provide context and help viewers understand the chart's purpose.

6. Applying chart styles and themes

• Select the Chart: First, create or select the chart you want to format in your Excel workbook.
• Chart Styles: In the "Chart Styles" group on the "Chart Design" tab of the Excel ribbon, you'll find various chart styles to choose from. Hover your mouse over each style to see a live preview of how it will look on your chart.
• Apply a Style: Click on the desired chart style to apply it to your selected chart. Excel will instantly update the chart's appearance with the selected style.
• Customize Chart Elements: After applying a style, you can further customize individual chart elements such as data labels, axis labels, legend, plot area, and chart title to fine-tune the visualization.
• Chart Themes: In addition to chart styles, Excel offers chart themes that consist of complementary colors and fonts. To apply a theme, go to the "Chart Design" tab, and in the "Chart Styles" group, click the "Change Colors" or "Change Chart Type" button to select a theme.
• Customizing Themes: If you want to create a custom theme, you can do so by clicking the "Customize" button within the "Change Colors" or "Change Chart Type" options. This allows you to adjust the colors, fonts, and effects to match your specific preferences or your organization's branding.

7. Adding textures, gradients, and transparency

• Excel allows users to add textures and gradients to elements like bars, columns, or backgrounds in charts. These visual effects can enhance the aesthetics and make the charts more visually appealing.
• Transparency can be applied to data points, shapes, or backgrounds, helping to overlay multiple data series and make the chart elements more distinguishable.

8. Using Data-Driven Visuals:

• Data-driven visuals, such as data bars and color scales in conditional formatting, enable users to highlight data trends and variances directly within the cells of the worksheet.
• Sparklines, a feature in Excel, allows for the creation of small, data-intense charts directly within a cell, providing a quick overview of data trends without the need for a separate chart.

Advanced Excel Techniques for Data Visualization

Creating advanced charts and graphs

• Waterfall Charts: Use waterfall charts to visualize cumulative changes in data over time, ideal for displaying financial data and highlighting positive and negative contributions.
• Radar Charts: Represent multiple variables in a radial format, making it easier to compare different data points across categories.

Combining multiple chart types in a single visualization

• Combo Charts: Combine two or more chart types in a single visualization. For example, use a combination of a bar chart and a line chart to display different data series with varying scales.

Utilizing Advanced Formatting Options:

• Trendlines: Add trendlines to scatter plots or line charts to identify and visualize data trends and projections.
• Error Bars: Display variability and uncertainty in data by adding error bars to charts.

Incorporating External Data Sources:

• Power Query: Import and transform data from external sources directly into Excel. Create dynamic visualizations that update automatically when the source data changes.
• Web Queries: Fetch data from web pages and combine it with your existing data to create dynamic visualizations based on real-time information.
• Excel's data visualization features offer a powerful and accessible platform for creating impactful charts and graphs to present data-driven insights in business presentations.
• A wide range of chart types, customization options, and integration with other Excel features enable users to tailor visualizations to their specific needs and preferences.
• Excel's pivot tables facilitate dynamic data analysis, providing quick overviews of complex information and supporting data exploration.
• Data-driven visuals , such as conditional formatting and sparklines, enhance data clarity within cells, eliminating the need for separate charts.
• Excel's seamless integration with PowerPoint allows users to embed visualizations directly into presentations, creating comprehensive and data-rich slides.
• The familiarity and widespread usage of Excel make it an invaluable tool for professionals across different organizations, ensuring accessibility and familiarity with data visualizations.

How to Visualize Data in Excel (With Examples)

According to Linearity , it is easier for the brain to retain data when they’re visually represented. Especially for larger data sets, it is always a good idea to illustrate your data with color-coded formatting, charts, and graphs.

Excel is a powerhouse when it comes to analyzing data. It also contains many data visualization tools, including 19 types of charts, heat maps, and 4 library icon sets.

We’ll be going through these tools and discuss what data they best represent through examples!

Charts in Excel

Charts are best used to monitor performances and analyze results. If you’re creating a presentation to compare annual sales, represent it in a chart.

Excel offers a variety of charts from simple bar charts to even map charts! Each chart is usually of these types:

• Clustered Chart : Visualize your chart in a 2-D format that includes the horizontal (X), and vertical (Y) axis.
• Stacked Chart : Illustrates the contribution of each data value in the entire data set.
• 100% Stacked Chart : Show the relative percentage of each data value in the set. The total value of one stacked chart is equal to 100.
• 3-D Chart : Includes a third axis called the depth (Z) axis.

To insert charts in Excel, first select data. Then, go to the Insert tab. On the Charts section, click on the chart you wish to insert.

If you’re unsure of what chart to use, select your data and click on Recommend Charts from the Charts section to get suggestions.

With that, let’s see every chart in detail.

Column Chart

Column charts are vertical bars that represent items on the horizontal (X) axis and frequency on the vertical (Y) axis. 

Column charts are clustered, stacked, 100% stacked, and 3-D column charts. These charts (except 3-D column charts) can be formatted to show values in 2-D or 3-D.

A line chart is used to show trends over a specific interval. When data increases, the line flows vertically upwards. Similarly, if the progress declines, it moves down the chart. 

Excel offers line charts, stacked line charts, 100% line charts, and 3-D line charts. You can insert markers representing the data value specified on your data set. 

A pie chart illustrates the total composition of an object or a task. If you need to break the pie chart further down, insert either a pie of pie or a bar of pie chart instead of a pie chart.

Excel allows you to format these charts in both 2-D and 3-D format.

Doughnut Charts

A doughnut chart is similar to a pie chart, except it can also be used to display negative values in the chart. The data value in a doughnut chart is represented in percentages that sum up to 100%

Data values in a bar graph are represented as horizontal bars. The bar stretching the farthest is the greatest value, while the bar closest to the Y axis is the smallest value. 

You have the option to insert bar charts as clustered, stacked, or 100% stacked.

An Area chart looks quite similar to a line chart. While they both display trends, an area below the plotted lines in an area chart is filled with a color. This makes data analysis easier when there are multiple trends to follow.

Area charts are of three types: Area chart, stacked area chart, and 100% stacked area chart. Excel offers all three area charts in 2-D and 3-D formatting.

Scatter and Bubble Chart

Scatter and Bubble charts establish a relationship between two data sets. If you’re trying to visualize the cost of making and the total profit made on a product, creating such plots is the correct way to go.

Create scatter charts with just the markers, smooth lines, or both—smooth lines and markers. Similarly, you have the option to insert scatter lines with straight lines or straight lines with markers.

For bubble charts, formatting is available in 2-D and 3-D effects.

Stock Chart

As the name gives it away, the stock chart is handy when it comes to monitoring the rise and fall of stocks.

If you’ve scrapped such data from the web, create a stock chart to visualize how the stock you’ve invested in is performing in the market.

A stock chart is also useful in tracking geographical data such as temperature rise and annual precipitation.

There are multiple types of stock charts depending on the number of your data series in Excel. These types include High-low-close , Open-high-low-close , Volume-high-low-close , and Volume-open-high-low-close .

For Excel to identify your data, always label and arrange them according to the chart type.

Surface Chart

Surface charts are mostly used by engineers and geologists to determine the elevation of an area. Surface charts use three variables when plotting data, making it a 3-D chart.

Surface charts are of four types in Excel consisting of 3-D surface , wireframe 3-D surface , contour , and wireframe contour chart .

Radar Chart

Radar charts, also referred to as spider charts, are used to compare items on a specific characteristic. 

If you’re quantitatively comparing the qualities of products, use radar charts to spot which feature a certain product stands out the most.

You can insert markers with markers or even fill them up with colors in Excel.

Other Charts (Available for Excel 2016 and Later)

The above-mentioned charts are available in all versions of Excel. However, if you’re on Excel 2016 or later, you have the option to insert other charts including:

• Treemap chart
• Sunburst chart
• Histogram charts
• Box and Whisker charts
• Waterfall charts
• Funnel charts
• Combo charts

A heat map is a visualization technique where you color-code numbers according to their values. Heat maps are excellent for when you’re analyzing weather reports, profit-loss, and even a mark sheet. 

Excel offers six 3-color and  2-color scales to create heat maps. Additionally, you have the option to customize the color palette to create a heat map.

You can create heat maps on Excel range, tables, and even PivotTables .

Let’s create a Green-Yellow-Red color scale heat map in the sales sheet below:

Icon sets are a part of the conditional formatting utility. You can insert icons on your data set based on a hierarchy or a custom rule.

There are four types of icons— Directional , Shapes , Indicators , and Ratings .

Directional

Directional icons show if the values have increased, increased, or remained constant in the form of arrows.

Excel allows you to choose from seven sets of arrows when inserting directional icons. Use directional icons when analyzing financial data such as a sales report.

Let’s enter directional icons to compare the sales made by Julie in twenty days:

According to the results, Julie’s performance is not that great.

Shapes and Indicators

As Shapes and Indicators are more or less the same, I’ve grouped them under the same category.

Let’s review my expenses for the past six months as an example. I’ve set a budget of $50-$100 for each category. However, I’ve gone over budget in a few areas.

We’ll be inserting shapes to make this visualization:

• Go to Home > Conditional Formatting > Icon Sets .

As the data illustrates, I have gone over my budget every month except October. This might be my sign to start budgeting more seriously!

Excel offers five types of rating icons. You can represent your ratings in the form of 3 stars, 5 quarters, 4 boxes, 4 ratings, and 5 ratings.

In this table, I have the total rating of 10 different hotels on a scale of 1-5. Let’s enter the 5 ratings icons to represent these icons.

According to the illustration, Hotel Safe Haven and Hotel Paradise have the highest ranges. Whereas, Hotel Heaven and Lake View Hotel have the lowest ratings on average.

Use Analyze Data in Excel (Excel 365)

If you’re on Excel 365, use Excel’s Analyze Data feature to visualize your data set.

Excel uses its smart AI in the Analyze Data tool to generate meaningful visuals, mainly charts and PivotTables.

In this sheet, we have a stock report. Let’s analyze this data using the Analyze Data tool.

• Look for appropriate charts and tables under Discover Insights .

Visualize Excel Data via Power BI

If you frequently need to visualize data, load your Excel sheet to Power BI .

Power BI is a Microsoft 365 E5 package and is a powerful visualization utility. Using Power BI, build visuals using all sorts of charts, graphs, and data tables.

Asmi is a content writer specializing in MS Office. She loves writing Excel-related content to assist other users to learn their way around the program. She started using Excel when she first entered the industry as a marketing intern. Soon, she realized that learning the often-overlooked spreadsheet program was no piece of cake. In her articles, she attempts to brief out complex topics to help beginner to intermediate-level Excel users. Asmi uses Excel for everything, including creating a grocery list to managing her personal finance. She’s a bit dramatic when it comes to the Flash Fill feature; so much so that could write a eulogy out of it. When she’s not working, you’ll find her learning a new recipe, or cleaning up her mess (out of the failed recipe).

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5 Excel Presentation Tips for Reports

James palic.

• August 6, 2022

Last Updated on August 6, 2022

Microsoft Excel is the best tool in the Microsoft Office Suite for analyzing data. Yet Excel also has the charting and graphing features that help display your data in an easy to understand format.  Not every presentation has to be in PowerPoint. In fact, Microsoft Excel can be a better medium for presenting data in many cases.   Let’s discuss some Excel presentation tips that will help you present data in a compelling and visually appealing format.

1. Charts and Graphs

Effectively providing a visual summary of data using graphs and charts is an important presentation technique. But it’s just as easy to make a confusing chart as it is to make a helpful one. Cramming every bit of data possible into a visual can result in your presentation becoming cluttered and complicated. Will your audience be able to comprehend the data being portrayed? Could you possibly group or format it differently to make it more meaningful or easier to understand? Excel offers several choices for chart type that can turn the raw data of your excel workbook into an easy to understand format.  Excel charts can also be used as embeds in PowerPoint presentations. 

Make sure to use the excel chart type that best matches your data.  Pie charts are used for presenting categories as a percent of the total. Line graphs are used when you have data collected over a period of time.  Scatter plots are useful to show how two different values of a data set relate.  Give your visual tools some thought before you present and use them appropriately to produce a convincing story.

2. Diagrams

If you have hierarchical excel data or you are trying to describe a process or a series of steps, then a diagram may be the best option. Diagrams are great if you’re creating organization charts, flow charts, or other data that would benefit from a visual layout. The simplest way to gain and keep someone’s attention is to show them an image that is eye-catching and easy to understand .

3. Highlighting and Borders

To call attention to sections of data in your spreadsheets, such as summary totals and conditional formatting, use color highlighting along with a border to make that section stand out.  You can also create a key to describe what different highlight colors mean. Colors are visually appealing and draw the audience’s eyes to the specific information that you want to show them. If you provide a color-coded key, then they can easily determine what they’re looking at.

Excel has a wide selection of built-in themes that will distinguish column headers and other areas of the spreadsheet so that you present a pleasing color pallet. These themes provide a starting point for choosing fonts, formatting, and colors that are easy to read and visually appealing.  People associate a coordinated color pallet with professionally done work and will be more likely to pay attention if they believe you carefully constructed your presentation.

5. Sparklines

Sparklines are small charts or graphs inserted as the background of a single cell.  Sparklines are useful for illustrating trends or patterns in a data table without creating a full chart.  And, unlike charts, sparklines are automatically printed along with the worksheet.  Sparklines can be used to show trends or maximum and minimum values.  Since sparklines don’t take up as much space as traditional charts and can be placed next to the data being described, they can be an effective tool for analysis.

With the Excel data presentation tips above, you can format your Excel spreadsheets to make a big impact on your audience. If you’d like to learn more about Excel and how you can use it for presentations, contact ONLC today.

• Categories: Microsoft Excel

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10 spiffy new ways to show data with Excel

It's time to dump the pie charts and move to donuts or even waterfalls to show off your data in ways people can better grasp..

Have you noticed that people groan when you pop open a spreadsheet to share your brilliant data insights? Maybe it’s not you — or your audience — that’s to blame. Maybe you suffer from Dull-and-Overused-Chart-Syndrome?

Here are 10 charts that can present data in clever ways that make it easy for people to grasp what you’re talking about. They don’t require people to squint and overthink; instead, these charts do to your data what a photo does to everything else: Show not tell.

You can stop boring everyone with the same old pie slices. Try serving doughnuts or showing them a waterfall. It’s more fun.

Sparklines: A heads-up display for your data

In-cell charts are like a heads-up display for your data, providing an immediate visual context in spreadsheets. The Sparkline feature, introduced in Excel 2013, lets you select data from rows or columns of cells and display line, column or handy win/loss charts.

It’s easy! Just select a range of cells next to the data you want to chart, then click Insert on the UI ribbon and click Line in the Sparklines group (you can also click Column or Win/Loss). In the Create Sparklines dialog box, click in the Data Range text box and select the rows or columns of data you want to depict. The Location Range text box should show the cells used to hold the Sparkline graphs, but you can adjust this by selecting the text in that box and using the mouse to select a row or column of cells. Click OK, and the in-cell charts appear, displaying the data. Select the Sparkline chart cell, click the Design item in the Ribbon, and play with the formatting options to get the look you want.

Make failures jump out with in-cell charts

Sparklines are handy. I especially like the Win/Loss option that displays iconography and color based on whether a value is positive or negative. Use it to, say, normalize regional sales data against projection and flag underperformers. But what if you want to embed visual context within the cell itself, rather than off to the side? Time for some conditional formatting and in-cell charts!

Select a range of data, click the Conditional Formatting item in the Ribbon, and click Icon Sets, then one of the simple options under Directional. Now each data cell displays an arrow icon. But these aren’t aligned relative to zero (and it’s visually quite busy).

So, with the range selected, click Conditional Formatting, Manage Rules, and double-click the rule you just created. In the Edit Rule Description dialog box, set the two top Icon drop downs to No Cell Icon, and the two top Value items to 0. Click the ‘greater than’ drop down and set the first the “>” and the second to “>=”. Set both Type drop downs to Number. In the bottommost Icon item, set the icon to a red down arrow. Click OK and OK again. Now, all negative cells (and only negative cells) are flagged.

Put your smarts on the table

Tables are one of my favorite features in Excel, thanks to the powerful Filter feature that can sort and filter even the largest data sets with a mouse click. But a hidden benefit is the magic it affords your charts. For instance, add a new column of data to the end of a table, and the linked chart automatically expands to add the new data series. Nice.

To Table-ize a data range, select the relevant cells (including header rows and columns) and click Insert, then Table in the Ribbon menu. Make sure the My Table Has Headers checkbox is checked, then click OK. Boom! The data gets some handy formatting and adds filter drop-down controls along the header row. Now, with an embedded chart displayed next to your data, enter a new header row item and some underlying data in the cells below it. As soon as you hit return in the header row cell, your chart resizes and sets aside a new item on the chart axis. As you add data to each cell, the chart updates to display the new data. 

Even better, Tables bring the useful magic of Filters to your charts. Suppose you have a table with monthly budget figures from 100 field offices. You can visualize only offices in, say, Ohio, by clicking the Filter drop down in the State column, then unchecking the Select All checkbox, before scrolling down to Ohio in the list and checking it. Click OK and the chart updates.

Sunburst charts: so much better than pie!

The new sunburst chart type in Excel 2016 is incredibly useful for understanding the relationship among data, taking nested hierarchies of data and showing how the granular elements combine to populate larger data groups. Think of it as a multi-level pie chart.

Sunburst charts in Excel do their thing by reading the structure of your data set. For instance, our fictional company has three strategic product lines (widgets, controllers, connectors) and keeps a spreadsheet that tracks sales for these product lines across industrial, specialized, and consumer markets. They further break these categories out by industry (automotive, medical, etc.). Once the data is properly laid out, select the relevant cells and click Insert, Chart, Recommended Charts, and click the All Charts tab, then click Sunburst from the list.

Waterfall charts for clean, clear data

Office 2016 introduces a new chart type to Excel’s arsenal — the waterfall chart. It’s great for showing how positive and negative values contribute to a total — like tracking the worth of a financial portfolio over time or visualizing income and expenses. Unlike a line chart, which reveals trends, a waterfall chart emphasizes individual gains and losses.

To create a waterfall chart, make a simple two-column array, with months in the left column and dollar amounts (positive and negative) in the right. Select the array and click Insert and click the Recommended Charts icon. Then click the All Charts tab on the insert Charts dialog box. Click Waterfall in the right pane and click OK. A rather poorly formatted chart greets you.

Next, we will rein in that Y axis so the hefty Start amount doesn’t swamp the other data. Right-click the Y-axis labels and click Format Axis. In the Axis Options pane, enter 15400 and click OK. Then click the Number item and in Category select Currency and, in the Decimal places box that appears, type 0, and press Enter. Finally, set that first data point on the chart as a Total item. Click on the first column in the chart and click on it again so that only that column is highlighted (the others should look faded). In the Format Data Point pane, click the Series Options icon and then check the Set as total checkbox. The selected column now turns gray.

Mmm… doughnuts

Pie charts can be the worst. They lack the visual precision of stacked column charts, and they’re often crowded, reducing smaller data points to inscrutable wedges. What’s more, they invite abuse, in the form of baroque 3D pies and extracted slices that can confuse hapless viewers.

That’s why you might consider serving doughnuts the next time you reach for an Excel pie chart. Like pie charts, doughnut charts are great for visualizing contributions to a total. But the additional white space and less common usage make them a refreshing change of pace on the corporate charting circuit.

To create a doughnut chart, select your data, then click Insert, click the Insert Pie or Doughnut Chart icon, and click Doughnut Chart. To tailor the presentation, right-click the chart body and click Format Data Series. In the pane that appears, change the Doughnut Hole Size value to somewhere around 60%. (I find the default 75% is too skinny.)

Roll your own project-tracking Gannt chart

You can turn a stacked bar chart into a project-savvy Gannt chart.

Make a four-column table with “Start,” “Stage,” “Date” and “On Task” across the top row. In Cells B2 through B7, enter project stages like Plan, Build, Approve, etc. In Cell A2, under Start, enter the start date for the first stage item, then in Cells D2 through D7 (under On Task), enter the number of days for each stage to complete. In Cell C2 enter “=A2” and format the cell as General. You’ll see a number like 43205, which is Excel’s time/date code needed for the chart layout. Finally, in C3 enter “=C2+D2”, then copy and paste this formula into cells C4 through C7.

Select the cells you’ve entered from Column B through D and click Insert. Click the column chart icon and then the stacked bar chart. Now let’s bring the chart into focus. Right-click the X-axis labels and click Format Axis. In the Axis Options pane, click the Number item and, in Category, select Date from the drop-down. In Type, select a shorter date format. Then, at the top of the pane under Bounds, in the Minimum text box, enter the value from Column C of the first item in your task list. It should be something like 43205. You’ll note that the Stages are in reverse order. Right-click the vertical axis and click Format Axis. In the Axis Options pane, click the Categories in Reverse Order checkbox.

Show your goal with a thermometer chart

Want to visualize an achievement against a goal? How about a fundraiser trying to raise $20,000? A thermometer chart is great for this.

We’ll keep it simple with a four-cell array with Goal and Donations on the left, and $20,000 and $16,425 on the right. Select the cells, click Insert in the Ribbon, click the Column Chart icon and then click on the Clustered Column Chart item. Click the Switch Row/Column icon in the Ribbon so the chart box displays a “1” in the X-axis label.

Right-click the smaller Donations bar and click Format Data Series. Then click Secondary Axis in the Series Options pane. The bar will disappear behind the larger Goal bar and a secondary Y-axis label appears. Right click the left axis, click Format Axis, and then enter 20000 in the Maximum box in the Axis Options pane. Do the same for the right (secondary) axis.

Empty the Goal bar by right-clicking it, clicking the Fill & Line icon in the pane, and clicking No fill and setting the Border to a black line. Format the Donations bar with a fill color of your choice and setting the border to No line. Clean up the chart by deleting the right axis and the X-axis labels. Also, tighten up the left axis in the Format Axis pane. In Axis Options, set the Number Decimal places box to 0. Add tick marks as you wish.

Charts that change as you enter data

Here’s a trick: an Excel chart that displays specific data from a large array based on your input.

You do this with the (incredibly useful) MATCH and OFFSET functions, which pluck data from an array and present it in cells that the chart is linked to. Let’s say you have seven columns representing years and 12 rows representing sales reps, with the cells containing yearly sales amounts.

In the column to the right of the last column, enter the following formula in each cell:

=OFFSET($A$1,ROW()-1,MATCH($J$1,$B$1:$H$1,0))

This tells Excel to look in the header row of the array for a value that matches the year to cell J1, so Excel can use the OFFSET function to pull the data from that year and display it in the cells in column I. So, if you enter 2014 in Cell J1, the formulas in Column I display the data that’s in the cells under 2014 (in this case, Column E). Now, all you have to do is create a chart that uses column A for its X-axis and Column I for its data. The column will update to display the data for whatever year you enter into Cell J1. Nifty.

More ways to that dynamic chart

OK, let’s take this a step further and update a line chart based on a scrollable list.

Just below the same array of data we used in the last slide, we’ll use the handy OFFSET and MATCH functions to add cells to Row 15, with formulas that pull sales data based on which rep’s name is entered into Cell A18. These formulas are in cells A15 through H15 and read as follows:

=OFFSET($A$1,MATCH($A$18,$A$1:$A$13,0)-1,COLUMN()-1)

Select Cells A1:H1 (X-axis values) and Cells A15:H15 (rep name and related sales data) and click Insert, Recommended Charts, and select Line chart from the top of the list. Now set up the drop-down list control to read names from Cells A2:A13. Click on A18, click the Data tab in the Ribbon, and click Data Validation and then Data Validation again. Click List from the Allow Drop-Down control, then click in the Source box and use the mouse to select cells A2 through A13. Click OK.

Now when you click on A18, a drop-down control appears. Click it and you’ll see a scrollable list of all your reps’ names. Select one and not only does A18 update to show that name, but the cells in Row 15 all update with that reps’ data, and the linked chart updates as well. 

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Four ways to improve your data presentation in Excel

   1.   Add a watermark text or a picture to the workbook with your company branding

See Adding watermarks to workbook for more details.

   2.   Add a background picture by choosing a graphics file to serve as a wallpaper for a spreadsheet like the wallpaper that you usually see on your Windows desktop:

See Adding a background image to the spreadsheet for more details.

   3.   Use conditional formatting to highlight cells in the worksheet:

See Applying Conditional Formatting for more details.

   4.   Use the drop-down list to simplify entering a value from the predefined set like countries, states, types, etc.

See Creating a Drop-Down List in a Cell for more details.

See also this tip in French: Quatre façons d'améliorer votre présentation de données dans Excel .

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Present Your Data Like a Pro

by Joel Schwartzberg

Summary .   

While a good presentation has data, data alone doesn’t guarantee a good presentation. It’s all about how that data is presented. The quickest way to confuse your audience is by sharing too many details at once. The only data points you should share are those that significantly support your point — and ideally, one point per chart. To avoid the debacle of sheepishly translating hard-to-see numbers and labels, rehearse your presentation with colleagues sitting as far away as the actual audience would. While you’ve been working with the same chart for weeks or months, your audience will be exposed to it for mere seconds. Give them the best chance of comprehending your data by using simple, clear, and complete language to identify X and Y axes, pie pieces, bars, and other diagrammatic elements. Try to avoid abbreviations that aren’t obvious, and don’t assume labeled components on one slide will be remembered on subsequent slides. Every valuable chart or pie graph has an “Aha!” zone — a number or range of data that reveals something crucial to your point. Make sure you visually highlight the “Aha!” zone, reinforcing the moment by explaining it to your audience.

With so many ways to spin and distort information these days, a presentation needs to do more than simply share great ideas — it needs to support those ideas with credible data. That’s true whether you’re an executive pitching new business clients, a vendor selling her services, or a CEO making a case for change.

Partner Center

A Guide to Effective Data Presentation

Key objectives of data presentation, charts and graphs for great visuals, storytelling with data, visuals, and text, audiences and data presentation, the main idea in data presentation, storyboarding and data presentation, additional resources, data presentation.

Tools for effective data presentation

Financial analysts are required to present their findings in a neat, clear, and straightforward manner. They spend most of their time working with spreadsheets in MS Excel, building financial models , and crunching numbers. These models and calculations can be pretty extensive and complex and may only be understood by the analyst who created them. Effective data presentation skills are critical for being a world-class financial analyst .

It is the analyst’s job to effectively communicate the output to the target audience, such as the management team or a company’s external investors. This requires focusing on the main points, facts, insights, and recommendations that will prompt the necessary action from the audience.

One challenge is making intricate and elaborate work easy to comprehend through great visuals and dashboards. For example, tables, graphs, and charts are tools that an analyst can use to their advantage to give deeper meaning to a company’s financial information. These tools organize relevant numbers that are rather dull and give life and story to them.

Here are some key objectives to think about when presenting financial analysis:

• Visual communication
• Audience and context
• Charts, graphs, and images
• Focus on important points
• Design principles
• Storytelling
• Persuasiveness

For a breakdown of these objectives, check out Excel Dashboards & Data Visualization course to help you become a world-class financial analyst.

Charts and graphs make any financial analysis readable, easy to follow, and provide great data presentation. They are often included in the financial model’s output, which is essential for the key decision-makers in a company.

The decision-makers comprise executives and managers who usually won’t have enough time to synthesize and interpret data on their own to make sound business decisions. Therefore, it is the job of the analyst to enhance the decision-making process and help guide the executives and managers to create value for the company.

When an analyst uses charts, it is necessary to be aware of what good charts and bad charts look like and how to avoid the latter when telling a story with data.

Examples of Good Charts

As for great visuals, you can quickly see what’s going on with the data presentation, saving you time for deciphering their actual meaning. More importantly, great visuals facilitate business decision-making because their goal is to provide persuasive, clear, and unambiguous numeric communication.

For reference, take a look at the example below that shows a dashboard, which includes a gauge chart for growth rates, a bar chart for the number of orders, an area chart for company revenues, and a line chart for EBITDA margins.

To learn the step-by-step process of creating these essential tools in MS Excel, watch our video course titled “ Excel Dashboard & Data Visualization .”  Aside from what is given in the example below, our course will also teach how you can use other tables and charts to make your financial analysis stand out professionally.

Learn how to build the graph above in our Dashboards Course !

Example of Poorly Crafted Charts

A bad chart, as seen below, will give the reader a difficult time to find the main takeaway of a report or presentation, because it contains too many colors, labels, and legends, and thus, will often look too busy. It also doesn’t help much if a chart, such as a pie chart, is displayed in 3D, as it skews the size and perceived value of the underlying data. A bad chart will be hard to follow and understand.

Aside from understanding the meaning of the numbers, a financial analyst must learn to combine numbers and language to craft an effective story. Relying only on data for a presentation may leave your audience finding it difficult to read, interpret, and analyze your data. You must do the work for them, and a good story will be easier to follow. It will help you arrive at the main points faster, rather than just solely presenting your report or live presentation with numbers.

The data can be in the form of revenues, expenses, profits, and cash flow. Simply adding notes, comments, and opinions to each line item will add an extra layer of insight, angle, and a new perspective to the report.

Furthermore, by combining data, visuals, and text, your audience will get a clear understanding of the current situation,  past events, and possible conclusions and recommendations that can be made for the future.

The simple diagram below shows the different categories of your audience.

  This chart is taken from our course on how to present data .

Internal Audience

An internal audience can either be the executives of the company or any employee who works in that company. For executives, the purpose of communicating a data-filled presentation is to give an update about a certain business activity such as a project or an initiative.

Another important purpose is to facilitate decision-making on managing the company’s operations, growing its core business, acquiring new markets and customers, investing in R&D, and other considerations. Knowing the relevant data and information beforehand will guide the decision-makers in making the right choices that will best position the company toward more success.

External Audience

An external audience can either be the company’s existing clients, where there are projects in progress, or new clients that the company wants to build a relationship with and win new business from. The other external audience is the general public, such as the company’s external shareholders and prospective investors of the company.

When it comes to winning new business, the analyst’s presentation will be more promotional and sales-oriented, whereas a project update will contain more specific information for the client, usually with lots of industry jargon.

Audiences for Live and Emailed Presentation

A live presentation contains more visuals and storytelling to connect more with the audience. It must be more precise and should get to the point faster and avoid long-winded speech or text because of limited time.

In contrast, an emailed presentation is expected to be read, so it will include more text. Just like a document or a book, it will include more detailed information, because its context will not be explained with a voice-over as in a live presentation.

When it comes to details, acronyms, and jargon in the presentation, these things depend on whether your audience are experts or not.

Every great presentation requires a clear “main idea”. It is the core purpose of the presentation and should be addressed clearly. Its significance should be highlighted and should cause the targeted audience to take some action on the matter.

An example of a serious and profound idea is given below.

To communicate this big idea, we have to come up with appropriate and effective visual displays to show both the good and bad things surrounding the idea. It should put emphasis and attention on the most important part, which is the critical cash balance and capital investment situation for next year. This is an important component of data presentation.

The storyboarding below is how an analyst would build the presentation based on the big idea. Once the issue or the main idea has been introduced, it will be followed by a demonstration of the positive aspects of the company’s performance, as well as the negative aspects, which are more important and will likely require more attention.

Various ideas will then be suggested to solve the negative issues. However, before choosing the best option, a comparison of the different outcomes of the suggested ideas will be performed. Finally, a recommendation will be made that centers around the optimal choice to address the imminent problem highlighted in the big idea.

This storyboard is taken from our course on how to present data .

To get to the final point (recommendation), a great deal of analysis has been performed, which includes the charts and graphs discussed earlier, to make the whole presentation easy to follow, convincing, and compelling for your audience.

CFI offers the Business Intelligence & Data Analyst (BIDA)® certification program for those looking to take their careers to the next level. To keep learning and developing your knowledge base, please explore the additional relevant resources below:

• Investment Banking Pitch Books
• Excel Dashboards
• Financial Modeling Guide
• Startup Pitch Book
• See all business intelligence resources
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How to present data in Excel

Data are available to researchers in raw format. Excel is a powerful tool when it comes to data presentation. It enables its users to analyze, summarize and present these data through various ways available on the application at no cost. Excel has a variety of methods that can be used in presenting the data. However, the method of representation chosen should be determined according to the data format, the method of analysis to be used, and the information to be emphasized.

In this article, we shall discuss three widely used methods in presenting raw data on Excel. Each of the methods is discussed below in lengthy.

Table of Contents

Using charts

Charts are useful for showing data changes over some time or for illustrating comparisons among items. They are the commonly used tools to present data in excel. Just like any other tool in excel, charts require a step-by-step procedure that should be followed to construct an appealing chart. These steps include:

1. Open excel

Click on Excel's icon to open it. Then, enter the data that you wish to present on the cells available in Excel.

2. Select the data

Once you've inputted all the data on the excel cells, recheck to ensure there is no space or gap between the data values. Then, highlight all your data.

3. Click the insert tab

After selecting all the data, click on the Insert tab- located at the top-left side of the bars section. Then, depending on the nature of your data, select the type of chart that is most suitable to present your data. Also, you can change the chart's layout by clicking Design>>Chart layout.

Using excel’s tables

When you want to present data that is organized in rows and columns, Excel's table proves to be the best tool to do this. After your data is well organized, you're ready to create excel's formatted table.

1. Select the data

2. Click the Insert tab and c lick the table button .

In the Tables section, click the table button. A Create table box pop up once you have clicked this button. On the Create table box, the range of your table should automatically, and my table has name -checked. Finally, click the "OK" button to accept these settings. And a table of the selected data will be displayed.

Using pivot Table Tool

A pivot table refers to an interactive table that allows you to sort and display data based on filters. Therefore they are fantastic tools for presenting both small and large amounts of data. Here are the steps to create pivot tables.

1. Input the data to be converted to a table. Then select the data.

2. Then, click the Insert tab on the ribbon. Choose the "Pivot Table" button. This will create a table. You go a step further and modify your table.

Power Pivot: Powerful data analysis and data modeling in Excel

Power Pivot is an Excel add-in you can use to perform powerful data analysis and create sophisticated data models. With Power Pivot, you can mash up large volumes of data from various sources, perform information analysis rapidly, and share insights easily.

In both Excel and in Power Pivot, you can create a Data Model, a collection of tables with relationships. The data model you see in a workbook in Excel is the same data model you see in the Power Pivot window. Any data you import into Excel is available in Power Pivot, and vice versa.

Note: Before diving into details, you might want to take a step back and watch a video, or take our learning guide on Get & Transform and Power Pivot.

Top features of Power Pivot for Excel

Import millions of rows of data from multiple data sources     With Power Pivot for Excel, you can import millions of rows of data from multiple data sources into a single Excel workbook, create relationships between heterogeneous data, create calculated columns and measures using formulas, build PivotTables and PivotCharts, and then further analyze the data so that you can make timely business decisions—all without requiring IT assistance.

Enjoy fast calculations and analysis     Process millions of rows in about the same time as thousands, and make the most of multi-core processors and gigabytes of memory for fastest processing of calculations. Overcomes existing limitations for massive data analysis on the desktop with efficient compression algorithms to load even the biggest data sets into memory.

Virtually Unlimited Support of Data Sources     Provides the foundation to import and combine source data from any location for massive data analysis on the desktop, including relational databases, multidimensional sources, cloud services, data feeds, Excel files, text files, and data from the Web.

Security and Management     Power Pivot Management Dashboard enables IT administrators to monitor and manage your shared applications to ensure security, high availability, and performance.

Data Analysis Expressions (DAX)     DAX is a formula language that extends the data manipulation capabilities of Excel to enable more sophisticated and complex grouping, calculation, and analysis. The syntax of DAX formulas is very similar to that of Excel formulas.

Tasks in Power Pivot or in Excel

The basic difference between Power Pivot and Excel is that you can create a more sophisticated data model by working on it in the Power Pivot window. Let’s compare some tasks.

How the data is stored

The data that you work on in Excel and in the Power Pivot window is stored in an analytical database inside the Excel workbook, and a powerful local engine loads, queries, and updates the data in that database. Because the data is in Excel, it is immediately available to PivotTables, PivotCharts, Power View, and other features in Excel that you use to aggregate and interact with data. All data presentation and interactivity are provided by Excel; and the data and Excel presentation objects are contained within the same workbook file. Power Pivot supports files up to 2GB in size and enables you to work with up to 4GB of data in memory.

Saving to SharePoint

Workbooks that you modify with Power Pivot can be shared with others in all of the ways that you share other files. You get more benefits, though, by publishing your workbook to a SharePoint environment that has Excel Services enabled. On the SharePoint server, Excel Services processes and renders the data in a browser window where others can analyze the data.

On SharePoint, you can add Power Pivot for SharePoint to get additional collaboration and document management support, including Power Pivot Gallery, Power Pivot management dashboard in Central Administration, scheduled data refresh, and the ability to use a published workbook as an external data source from its location in SharePoint.

Getting Help

You can learn all about Power Pivot at Power Pivot Help .

Need more help?

You can always ask an expert in the Excel Tech Community  or get support in  Communities .

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Excel Sample Data (Free Download 13 Sample Datasets)

Project Management Sample Data

A project management sample data is suitable for various types of data filtering, analyzing, and visualizing. Here are the variables that we have included in the sample data:

• Project Name
• Assigned to
• Days Required

Here is a preview of the project management dataset:

Download the Sample Workbook

Inventory Records Sample Data in Excel

Inventory management records consist of product and stock information. In our sample dataset, we have included the following fields:

• Product Name
• Opening Stock
• Purchase/Stock-in
• Number of Units Sold
• Hand-in-stock
• Cost Price Per Unit
• Cost Price Total

Here is a preview of the inventory records sample data:

Call Center Customer Satisfaction Data

Call centers deal with customer service and receive various types of feedback from customers. In our Call Center Customer Satisfaction data, we have included the following fields:

• Customer Name
• Call Timestamp
• Response Time
• Call Duration
• Call Center

Here is a preview of our sample data:

Supermarket Sales Sample Data in Excel

Supermarket sales sample data is a popular dataset for learning and practicing your Excel skills. Here is the list of variables we have included in our supermarket sales sample data:

• Retail Price
• Order Quantity

Here is a preview of the sample supermarket sales data in Excel:

Download the Practice Workbook

Employee Management Data

Employee management data contains information on all employees in an organization. In our sample employee management data in Excel, we have listed the following variables:

• Employee ID
• Designation
• Annual Salary

Here is a preview of the employee management data:

Technological Product Sample Data

Any technological product information requires various specifications. In our sample dataset, we have listed the following specifications:

• Country of Origin
• Release Date

The following image shows a preview of our sample technological product dataset:

Engineering and Manufacturing Sample Data

Engineered or manufactured products also require various specifications. Here is the list of variables we have included in our sample engineering and manufacturing sample data:

• Manufacturer
• Stock Quantity

Here is a preview of the sample dataset:

Students Marksheet Sample Data in Excel

A student mark sheet contains the student identifiers and marks in various subjects. In our sample students marksheet dataset, we have listed the following variables:

• Marks in Mathematics
• Marks in Physics
• Marks in Chemistry

Here is a preview of the sample student marksheet dataset:

2022 FIFA World Cup Performance Data

In our sample dataset, we have listed the information of each player from the World Cup-winning Argentina team. Here is the list of variables we have included:

• Player Name
• Jersey Number
• Appearances
• Goals Scored
• Assists Provided
• Dribbles per 90 Min
• Interceptions per 90 Min
• Tackles per 90 Min
• Total Duels Won per 90 Min

You can preview the sample dataset in the following image:

Tokyo Olympic Data

This sample dataset contains the team names, number of Gold, Silver, Bronze, and total medals, and ranking of teams (based on gold medal and total medal count) in the Tokyo Olympics. Here is a preview of the sample dataset:

Healthcare Insurance Sample Data in Excel

The price of healthcare insurance depends on various factors such as current age, BMI, smoking habits,  etc. In our sample healthcare insurance dataset, we have listed the following variables:

• Smoking Status
• Insurance Price

Travel Destination Distance Data in Excel

While deciding on a travel destination, we need to take the distance, available travel modes, travel duration, etc. factors into consideration. In our sample travel destination dataset, we have listed the following variables:

• Source City
• Source Latitude
• Source Longitude
• Destination City
• Destination Latitude
• Destination Longitude
• Distance (in km)
• Distance (in mile)
• Travel Mode

Netflix Movies Sample Data

The movie dataset provided in this section contains the following variables:

• IMDb Rating

You can preview the dataset in the image below:

Excel Sample Data: Knowledge Hub

• GST State Code List in Excel
• Historical Data of NSE Stocks in Excel

<< Go Back to Learn Excel

What is ExcelDemy?

Tags: Learn Excel

Seemanto Saha graduated in Industrial and Production Engineering from Bangladesh University of Engineering and Technology. He has been with ExcelDemy for a year, where he wrote 40+ articles and reviewed 50+ articles. He has also worked on the ExcelDemy Forum and solved 50+ user problems. Currently, he is working as a team leader for ExcelDemy. His role is to guide his team to write reader-friendly content. His interests are Advanced Excel, Data Analysis, Charts & Dashboards, Power Query,... Read Full Bio

Thanks for the DATA SETS !

Hello Margit ,

You are most welcome.

Regards ExcelDemy

Thank you so much

Hello Usama Jamil ,

I needed Oil parameters Offshore Foundation design 2015 excel sheet access

Hello Ameer Ahmed ,

We don’t have any dataset you asked for and your question is not clear enough. Our datasets are given in the article.

Thank you so much for the data sets.

Hello Gaurav,

Where are the solutions to these problems? Would like to check against what I did

Hello Cynthia Satterwhite ,

Neither any problem nor any solution are given. These dataset are given to practice by yourself.

Wow Great Readymade Excel Sheets, Can You provide any excel sheet to maintain monthly calibration details for internal lab

Hello Karunesh Pandey ,

As calibration details varies with lab type we can provide you the criteria. You can fill out your information and edit the list.

nice work thank you ! I need dataset for students, subjects, teachers and departments hope U help.

Hello Fulad

Thanks for your compliment! As you requested, you can use the following dataset, which contains data with your mentioned fields:

You can download the workbook from the following link:

DOWNLOAD WORKBOOK

I hope you have found the dataset you were looking for; good luck.

Regards Lutfor Rahman Shimanto ExcelDemy

ExcelDemy good work. It is difficult to get excel datasets for predictive analysis. please can I get a comprehensive CRM (customer online journey) or Supply chain dataset (Procurement-Logistics- inventory-sales) for retail industry.

Hello Amara ,

Here I’m attaching a sample dataset for CRM and Supply chain. You can modify this dataset based on your requirements. Dataset of CRM: CRM Dataset.xlsx Dataset of Supply Chain: Supply Chain Dataset.xlsx

I need a dataset for Customs Compliance Monthly Report excel sheet to help me populate:

General data: •Import/Export numbers. [Breakdown of EC, Sanctions, IP, FC, DG, Incoterms, duty spend] •CCAR performance. •Procedures status. Declaration Accuracy: •Export (Export Control/IP/General). •Import (General/IP).

Inward Processing: •Quarterly update. •Renewal.

Audit: •Export/Export Control. •Tariff Classification. •Preferential Origin. •Finance/Tax. •Documentation. •NISR audit (high risk).

Project status updates: •Incoterms. •Plain Language Customs Descriptions. •Service Level Agreements. •D365 (Service Centre). Regards Dems

Hello Demba ,

Download the Excel file from here : Customs Compliance Monthly Report.xlsx

Hi, I need an excel sample data of supply chain i.e lead time data from suppliers and lead time from warehouse to stores data.

Hello Shibani Agrawal ,

You can use our sample supply chain data modify it based on your requirements.

Download the Excel file: Dataset of Supply Chain: Sample Supply Chain Dataset.xlsx

Thankyou so much .

Hello Nidhi ,

You are most welcome. Thanks for reading our article. Keep learning Excel with ExcelDemy!

Hi, I need an excel sample data for healthcare insuranc claim patients datasets in below format. Claim ID Provider Name Provider NPI Patient Name Patient DOB Patient ID Diagnosis Code Diagnosis Description Procedure Code Procedure Description Claim Amount Relevance

Hello Akhila ,

Here is the sample dataset of Healthcare Insurance Claim Patients

Download the Dataset: Healthcare-Insurance-Claim-Patients-Dataset.xlsx

Could you please share more sample data related to a patient health care insurance claim dataset?

Hi Akhila ,

You are most welcome. Thank you for your comment! We provide sample datasets to help you get started, and you can easily extend or modify them as needed. Feel free to add more rows to suit your specific use case or dataset requirements. The sample data we’ve provided is designed to be a foundation for building your own healthcare insurance claim datasets.

thank you very much for this excel sets

Hello Esther ,

You are most welcome. Thanks for your appreciation it means a lot to us. Keep exploring Excel with ExcelDemy!

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How to Embed an Excel File in PowerPoint: Quick & Easy!

Trish Dixon

Embedding an Excel file in PowerPoint can make your presentation more dynamic by including data directly from your spreadsheet. Whether you need to showcase charts, tables, or raw data, embedding Excel allows you to maintain the connection between your presentation and the original Excel data.

In this article, we will guide you step-by-step through the process of embedding an Excel spreadsheet into a PowerPoint slide, ensuring your data remains up-to-date and easily editable.

Why Embed Excel Files in PowerPoint?

Embedding Excel files in PowerPoint offers numerous advantages. By embedding your Excel worksheet directly into PowerPoint, you can ensure that your data remains interactive, with all formulas and calculations intact. Additionally, when you update your Excel data , these changes can reflect in your PowerPoint presentation, making it more efficient for presentations that require real-time data updates.

Here are the key benefits of embedding an Excel file into PowerPoint:

• Data Accuracy : You avoid errors from manual data entry.
• Dynamic Updates : Any change in the original Excel sheet automatically updates the embedded file in PowerPoint.
• Ease of Access : Presenters can showcase charts, graphs, and tables directly within the presentation.
• Professional Appeal : It presents clean, interactive data without switching between applications.

Steps to Embed an Excel File in PowerPoint

Step 1: open your powerpoint presentation.

Begin by opening the PowerPoint presentation where you want to embed the Excel file . You can create a new slide or select an existing slide where the embedded Excel file will be placed.

• Open PowerPoint .
• Navigate to the slide where you want the Excel file to appear.
• Click on the desired slide to start the embedding process.

Step 2: Insert the Excel File

Once your PowerPoint slide is open, you’ll need to insert the Excel file into your presentation. PowerPoint provides two primary methods for embedding an Excel file : linking the file and embedding it as an object.

Method 1: Embed as a Static Object

Embedding an Excel file as an object allows you to embed the entire spreadsheet directly into PowerPoint. The data becomes part of the PowerPoint file, meaning no external link is maintained, and the data does not update when the original file is changed.

• Go to the Insert tab in the PowerPoint ribbon.
• Click on Object .
• In the dialog box, select Create from File .
• Click on Browse and navigate to the Excel file you wish to embed.
• Select the file and click OK .

The embedded Excel file will now appear as an object on your slide. You can resize and move it as needed.

Method 2: Link to the Excel File

Linking the Excel file allows you to maintain a connection between the PowerPoint slide and the original Excel spreadsheet. Any updates made to the Excel worksheet will reflect in your PowerPoint presentation.

• Go to the Insert tab.
• Click Object .
• In the dialog box, check the Link box.
• Click Browse and choose the Excel file to link.
• Click OK to embed the linked Excel file.

Now, your PowerPoint slide is linked to the Excel file. Whenever the Excel file is updated, these changes will automatically appear in the embedded object.

Step 3: Edit the Embedded Excel File

Once the Excel file is embedded, you can edit the data directly from PowerPoint without needing to open Excel separately. Here’s how to do it:

• Double-click on the embedded Excel object .
• The embedded file will open within PowerPoint, allowing you to make changes.
• After editing, click outside the embedded object to return to PowerPoint.

This method is especially useful when you want to make small adjustments to the data during a presentation.

Step 4: Display Specific Data from Excel

Sometimes, you don’t need to embed the entire Excel worksheet . Instead, you might want to show only a specific chart or table. Here’s how you can do that:

• In Excel , select the data or chart you want to embed.
• Press Ctrl + C to copy the selection.
• Switch back to PowerPoint and navigate to the slide where you want to place the data.
• Go to the Home tab and click on Paste Special under the Paste dropdown.
• Select Microsoft Excel Worksheet Object to embed the selected data as an object.

This process embeds only the selected data, giving you control over what appears on your slide.

Using Excel Charts in PowerPoint

A significant advantage of embedding Excel files in PowerPoint is that you can display Excel charts directly within your presentation. This maintains the integrity of your data while allowing you to present it visually.

Step 1: Create a Chart in Excel

To begin, create your chart in Excel. This could be a bar chart, line graph, or pie chart, depending on your data.

• Open your Excel file .
• Select the data you want to visualize.
• Click on the Insert tab and select your desired chart type.
• Once your chart is ready, select it and copy it using Ctrl + C .

Step 2: Paste the Chart in PowerPoint

Now that you have your chart ready in Excel , you can paste it into PowerPoint.

• Open your PowerPoint presentation.
• Navigate to the slide where you want to place the chart.
• Paste the chart using Ctrl + V .

You can choose to link the chart to Excel, meaning any changes made in the Excel file will update the chart in PowerPoint .

Step 3: Format the Chart in PowerPoint

After pasting the chart into PowerPoint, you can format it to fit the overall design of your presentation. Use the Chart Tools in PowerPoint to adjust the colors, fonts, and other visual elements of your chart.

Best Practices for Embedding Excel Files in PowerPoint

Here are a few best practices to keep in mind when embedding Excel files into your PowerPoint slides :

• File Size Considerations : Embedding large Excel files can significantly increase the size of your PowerPoint presentation. If possible, try embedding only the specific data or chart you need rather than the entire workbook.
• Update Links : If you choose to link your Excel file to PowerPoint, ensure the Excel file remains in its original location. Moving the Excel file could break the link, resulting in errors during your presentation.
• Maintain Formatting : When embedding Excel data, take care to maintain formatting consistency. PowerPoint may alter some of the Excel formatting, so double-check before presenting.

Troubleshooting Common Issues

Problem 1: excel object not displaying correctly.

Sometimes, the embedded Excel object might not display correctly in PowerPoint. This can happen due to compatibility issues between Excel and PowerPoint. To fix this, try embedding the Excel file as an image instead of an editable object.

• Copy the Excel table or chart.
• Go to PowerPoint and paste it as an image by selecting Paste Special and choosing Picture .

Problem 2: Linked Excel File Not Updating

If the linked Excel file is not updating in PowerPoint, ensure the Excel file is still in the same location it was originally linked from. If the file has been moved or renamed, PowerPoint will not be able to update the data.

Problem 3: PowerPoint File Size Too Large

Embedding large Excel files can inflate the size of your PowerPoint presentation. To reduce file size, consider embedding only specific parts of the Excel worksheet or using a linked file instead of embedding the entire workbook.

Final Thoughts

Embedding an Excel file in PowerPoint is a powerful way to integrate dynamic data into your presentations. Whether you’re showcasing detailed financial reports, displaying interactive charts, or embedding raw data, using Excel files within PowerPoint can make your presentation more professional and efficient. By following the steps outlined above, you can easily embed Excel worksheets , charts, or data tables in your PowerPoint slides, ensuring a seamless integration between the two Microsoft applications.

How do I embed an Excel file into PowerPoint?

To embed an Excel file into PowerPoint, go to the Insert tab, select Object, and choose Create from File. Browse and select your Excel file, then click OK.

Can I link an Excel file to PowerPoint for automatic updates?

Yes, you can link an Excel file to PowerPoint by checking the Link box when embedding the file. Any updates made to the Excel file will reflect in PowerPoint.

How do I edit the embedded Excel file in PowerPoint?

Double-click the embedded Excel object in PowerPoint. This will open the Excel file within PowerPoint, allowing you to edit it directly.

Why is my linked Excel file not updating in PowerPoint?

If your linked Excel file is not updating, ensure that the file remains in its original location. Moving or renaming the file may break the link, preventing updates.

Can I embed only a part of an Excel file, like a chart, into PowerPoint?

Yes, you can embed specific parts of an Excel file, such as a chart or table, by selecting and copying it from Excel, then pasting it into PowerPoint.

Will embedding an Excel file increase my PowerPoint file size?

Yes, embedding an entire Excel file can increase your PowerPoint file size. Consider embedding only the necessary data or using a linked file to reduce size.

• Recent Posts

• How to Embed an Excel File in PowerPoint: Quick & Easy! – September 29, 2024
• How to Turn a PowerPoint into a Video: Expert Tips! – September 28, 2024
• How to Superscript in PowerPoint? (5 Easy Methods) – September 24, 2024

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