entity relationship (er) diagrams assignment

A Guide to the Entity Relationship Diagram (ERD)

Learn all about Entity Relationship Diagrams (ERDs), what they are used for, how to understand them, how to create them, and more in this guide.

Table of Contents

What is an Entity Relationship Diagram (ERD)?

An Entity Relationship Diagram (ERD) is a type of diagram that lets you see how different entities (e.g. people, customers, or other objects) relate to each other in an application or a database.

They are created when a new system is being designed so that the development team can understand how to structure the database. They can also be created on an existing system to help the team understand how the system works and to find and resolve any issues.

Entity Relationship Diagrams use a specific set of symbols, such as shapes and arrows, to depict the system and database.

Here’s an example of an ERD:

Components of an ERD

An Entity Relationship Diagram is made up of many different components:

Relationship

An entity is a thing that can have data stored about it. It can be a physical object (e.g. car, person), a concept (e.g. address) or an event (e.g. student enrolment in a course). They represent nouns.

They are usually represented as rectangles on an ERD with the entity name inside the rectangle.

An entity can also be a strong entity or a weak entity. What’s the difference?

A strong entity has an identifier (a primary key) and does not depend on any other entities for it to exist. For example, a student may be a strong entity, as it can have a primary key and does not depend on any other entities for it to exist.

A weak entity is one that depends on a strong entity for existence. This means it has a foreign key to another entity. For example, an enrolment of a student may be a weak entity, as an enrolment cannot exist without a student.

A relationship in an ERD defines how two entities are related to each other. They can be derived from verbs when speaking about a database or a set of entities.

Relationships in ERDs are represented as lines between two entities, and often have a label on the line to further describe the relationship (such as “enrols”, “registers”, “completes”).

There are several types of relationships that are represented on an ERD:

One to one: One record of an entity is directly related to another record of an entity
One to many: One record of an entity is related to one or more records of another entity.
Many to many: Many records of one entity can be related to many records of another entity.

An attribute is a property of an entity or something that can be used to describe an entity. They are often represented as ovals, or as entries inside an entity.

There are several different types of attributes represented on an ERD:

Simple: an attribute that cannot be split into other attributes, such as a first name.
Composite: an attribute that can be split into other attributes, such as name being split into first, middle, and last name.
Derived: an attribute that is calculated or determined from another attribute, such as the age of record being calculated from the created date.

An attribute can also be single-value or multi-value:

Single-value: an attribute that is only captured once for
Multi-Value: an attribute that can be captured more than once for an entity, such as multiple phone numbers.

What is Cardinality?

Cardinality represents the number of instances of an entity that exist in a relationship between two entities. This is often expressed as a number but could also be a symbol, depending on the style of diagram used. Common cardinality values are zero, one, or many.

We’ll see some examples of cardinality later in this guide.

Natural Language

When we are creating an ERD we often have an idea of what we want to capture. This can usually be expressed in words, or using “natural language”.

Some examples are:

“Record students, courses they enrol in, and teachers who teach the course”
“Capture the customer orders, customer details, and where the orders are being sent”
“Capture patient data and the operations they had”

These sentences include a few different types of words, which can be used as a starting point for an ERD. They are represented in a few different ways:

Noun: a “thing”, such as a student or customer. Represented as an entity.
Verb: an action, such as enrol or send. Represented as a relationship between two entities.
Adjective: a describing word, such as residential or advanced. Represented as an attribute on an entity.

This can help you translate a description of what you need to diagram into an actual diagram.

Symbols and notations

When creating an ERD, it can be simple to create boxes and lines between them. But, like many things in software development, there are a few different methods and standards that are available. For ERDs, there are several notation standards, which define the symbols used.

Here’s an example of the symbols used with the Chen notation style.

Here’s an example ERD using Chen notation:

Crow’s Foot

Here’s an example of the symbols used with the Crow’s foot notation style. This is the style you’ll see the most on Database Star as it’s the one I’m most familiar with. It’s called “crow’s foot’ as the symbol for a many relationship looks like the foot of a crow with its three prongs.

Here’s an example ERD using Crow’s Foot notation:

Here’s an example of the symbols used with the Bachman notation style.

Here’s an example ERD using Bachman notation:

Here’s an example of the symbols used with the IDEF1X notation style.

Here’s an example ERD using IDEF1X notation:

Here’s an example of the symbols used with the Barker notation style.

Conceptual, logical, physical

An Entity Relationship Diagram can be drawn at three different levels: conceptual, logical, or physical.

Each of these levels has a different level of detail and are used for a different purpose.

Let’s see some examples.

Conceptual Data Model

The conceptual data model shows the business objects that exist in the system and how they relate to each other.

It defines the entities that exist, which are not necessarily tables. Thinking of tables is too detailed for this type of data model.

An example of a conceptual data model is shown here. It shows students, courses, and how they relate.

Logical Data Model

A logical model is a more detailed version of a conceptual data model. Attributes are added to each entity, and further entities can be added that represent areas to capture data in the system.

Here’s an example of the student and course data model created as a logical data model.

Physical Data Model

The physical data model is the most detailed data model in this process. It defines a set of tables and columns and how they relate to each other. It includes primary and foreign keys, as well as the data types for each column.

These diagrams can be created manually in a data modelling tool. They are also often generated by an IDE from an existing database.

Here’s an example of the student and course physical data model.

This table outlines the differences between a conceptual, logical, and physical model:

How to Create an Entity Relationship Diagram

So how do you create a data model or an Entity Relationship Diagram?

I’ve detailed this in my Relational Database Design course, and I’ve also explained it in my guide to designing a database .

The process to create an ERD is:

Write a sentence or two about what you are storing data about
List what you’re storing data about – the nouns/objects
List the information you want to store for each object
Describe the relationships between each object
Draw the diagram

The steps listed here are brief but the process can take some time, depending on how familiar you are with the system and how experienced you are with creating Entity Relationship Diagrams.

Tools to Use

What tool should you use to create a data model or an Entity Relationship Diagram?

There are a lot of applications available to help you create one. I’ve written a post that lists them all with a comparison of major features and price, which you can find here: 79 Data Modeling Tools Compared .

Personally, I use LucidChart as it’s simple to use and web-based. But in the past, I’ve used Visio and even the data modelling capabilities inside an IDE.

That page above includes a range of tools and some recommendations if you’re not sure what to use.

You can also start with a pen and paper to get an understanding of how a diagram can be created. I often start by drawing one in my notebook. It gets messy eventually, but I transfer it to an electronic copy anyway.

Tips for Creating an Entity Relationship Diagram

Here are some tips for creating an Entity Relationship Diagram:

Determine the right level of detail based on the purpose of the diagram. Development teams often find the logical model the most useful, but others might find the conceptual model more valuable.
Review the entities and attributes to see if they include everything you want to store in the system.
Name all entities and attributes.
If you have a large diagram, consider using colours to highlight different sections, or breaking it up into smaller diagrams.
Be consistent with your naming and the symbols you use.

An Entity Relationship Diagram is a great tool to help you define, understand, and communicate the requirements of a system. It can be modelled at a high level (conceptual data model), a detailed level (physical data model) or a level in between (logical data model).

There is a range of modelling notations or types of symbols which define how entities, attributes, and relationships are captured.

If you want to get started with creating an ERD for your system, consider drawing one on paper, or use one of the many tools available.

15 thoughts on “A Guide to the Entity Relationship Diagram (ERD)”

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Great insight will be coming can you help me solve my question from my class? To identify a problem of an organization and develop ER-Diagram and a database management system to solve it.

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Just one minor point; I think the second Bachman diagram should actually be a Barker example?

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What is an Entity Relationship Diagram (ERD)? | An Introduction to ER Diagram

So you want to learn Entity Relationship diagrams? This ER diagram tutorial will cover their usage, history, symbols, notations and how to use our ER diagram software to draw them. We’ve also added some templates for you to get started quickly.

What is an ER diagram?

An Entity Relationship Diagram (ERD) is a visual representation of different entities within a system and how they relate to each other . It is a tool used to design and model relational databases, and shows the logical structure of the database. ER diagrams use symbols to represent entities, attributes, and relationships, which help to illustrate the relationships between the entities in the database. It consists of entities (which represent objects or concepts, like “Customer” or “Product”) and relationships (which represent how these entities are connected or interact with each other, like “owns” or “buys”).

Entities are depicted as rectangles, and relationships are shown as diamonds. Lines connecting entities and relationships represent the connections between them, often indicating the type of relationship (such as one-to-one, one-to-many, or many-to-many).

ER diagrams are commonly used in software engineering and database design to help developers and stakeholders understand and design complex databases. For example, the elements writer, novel, and a consumer may be described using ER diagrams the following way:

ER Diagram Template for Student Enrollment System

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History of ER Diagrams

ER diagrams were first introduced by a computer scientist named Peter Chen in 1976. He proposed them as a way to visually represent the structure of databases. During the late 1970s and early 1980s, ER diagrams became widely used in both academic and industrial settings. They provided a clear way to show how different pieces of information are related to each other.

As database systems became more complex, ER diagrams remained important tools for designing and managing databases. They helped developers and users understand how data was organized and connected.

In the 1990s and 2000s, with the rise of the internet and new technologies, ER diagrams adapted to accommodate these changes. They continued to be essential for designing databases, but they were sometimes used alongside other modeling techniques.

Today, ER diagrams are still widely used in software engineering and database design. They provide a simple and intuitive way to plan and communicate the structure of databases, making them valuable tools for developers and designers.

ER Diagram Templates

Below are some ER diagram templates so you can get started quickly. Clicking on the image and in the new page that opens click the “Use as Template” button. For more templates check our ER diagram template section .

Uses of ER Diagrams?

ER diagrams are essential tools for designing, communicating, maintaining, and optimizing databases. They facilitate collaboration, ensure data integrity, and contribute to the efficient management of database systems. Here are several uses of ER diagrams.

Database design: ER diagrams are used to design databases. They provide a visual representation of how different pieces of information, called entities, are related to each other. This helps in planning the structure of the database before it’s built.

Communication: ER diagrams act as a common language between people involved in developing databases, such as developers, designers, and clients. They help everyone understand how the database will work and how data will be organized.

Database maintenance: Even after a database is created, ER diagrams remain useful for maintenance. They help developers understand the existing structure and make changes or updates as needed while ensuring the integrity of the database.

Documentation: ER diagrams serve as documentation for the database system. They provide a detailed overview of the database schema, including entities, attributes, and relationships. This documentation helps in troubleshooting issues and training new team members.

Identifying redundancy and inconsistencies: By visualizing relationships between entities, ER diagrams help identify redundant or inconsistent data in the database design. This allows for optimization and ensures data accuracy.

Database optimization: ER diagrams aid in optimizing database performance. By understanding entity relationships, developers can design efficient queries and data retrieval strategies, leading to improved performance and scalability.

Integration with development tools: ER diagrams can be integrated into various development tools and database management systems. Many software tools provide features for creating, editing, and generating code from ER diagrams, streamlining the database development process.

The Components and Features of ER Diagrams

An entity represents a real-world object, concept, or thing about which data is stored in the database. It could be a person, place, thing, event, or concept.

Characteristics

Attributes: Entities have attributes that describe their properties or characteristics. Instances: Each entity has instances or occurrences, representing individual occurrences of the entity in the real world. Identity: Each instance of an entity is uniquely identifiable and can be distinguished from other instances. Relationships: Entities can be related to other entities through relationships, forming connections within the database schema.

Types of entities

Strong entities: Also known as regular entities, these entities have attributes that uniquely identify each instance. They can exist independently of other entities. Weak entities: Weak entities do not have a primary key attribute of their own and depend on a related strong entity (owner entity) for their existence. They are identified by their relationship with the owner entity. Associative entities: Also called many-to-many entities, these entities are used to represent relationships between relationships. They arise in many-to-many relationships and typically contain attributes in addition to the foreign keys linking the associated entities.

Types of entity keys

Simple key: A single attribute serves as the primary key. Composite key: A combination of two or more attributes serves as the primary key. It is used when no single attribute uniquely identifies each instance. Surrogate key: An artificially generated identifier, such as an auto-incremented integer, is used as the primary key. It is often added when no suitable natural key exists or when there are concerns about stability or size of natural keys.

Attributes are the characteristics or properties of entities. They describe the details of each entity. For example, attributes of a “Customer” entity might include “Customer ID,” “Name,” and “Email Address.”

Name: Each attribute has a name that identifies it within the entity. Data type: Attributes have a data type that specifies the kind of data they can hold, such as text, number, date, etc. Constraints: Attributes may have constraints that define rules or conditions for the values they can contain, such as uniqueness or requiredness. Domain: Attributes have a domain, which is the set of all possible values that the attribute can take. Nullability: Attributes may allow null values, meaning they can have no value assigned to them for some instances of the entity.

Types of attributes

Simple attribute: A single atomic value is stored in the attribute. Example: Name, Age. Composite attribute: An attribute that can be divided into smaller sub-parts, each representing a distinct attribute. Example: Address (composed of Street, City, Zip Code). Single-valued attribute: An attribute that holds a single value for each instance of the entity. Multi-valued attribute: An attribute that can hold multiple values for each instance of the entity. Example: Phone Numbers.

Relationships

Relationships show how entities are connected or related to each other in the database. They represent interactions or associations between entities. Examples include “owns,” “buys,” or “works for.”

Name: Each relationship has a name that describes the nature of the association between entities. Directionality: Relationships can be unidirectional or bidirectional, indicating the flow or direction of the association between entities. Cardinality: Cardinality specifies the number of instances of one entity that can be associated with instances of another entity in a relationship. It defines the minimum and maximum occurrences of related entities. Degree: The degree of a relationship indicates the number of entities participating in the relationship. Relationships can be unary (involving a single entity), binary (involving two entities), ternary (involving three entities), etc. Attributes: Relationships can have attributes that describe additional information or properties about the association between entities. Recursive relationships: Some relationships involve an entity being related to itself, known as recursive relationships. They represent connections or interactions within the same entity.

Types of relationships

One-to-one (1:1): Each instance of one entity is associated with exactly one instance of another entity. One-to-many (1:N): Each instance of one entity is associated with multiple instances of another entity, but each instance of the other entity is associated with only one instance of the first entity. Many-to-one (N:1): Multiple instances of one entity are associated with exactly one instance of another entity. Many-to-many (M:N): Multiple instances of one entity are associated with multiple instances of another entity, and vice versa. Recursive relationships: An entity is related to itself through a relationship. This can represent hierarchical structures or self-referential associations.

Cardinality

Cardinality specifies the number of instances of one entity that can be associated with the number of instances of another entity in a relationship. It describes the minimum and maximum number of occurrences of one entity that can be associated with occurrences of another entity.

Minimum cardinality: Specifies the minimum number of instances required in a relationship. Maximum cardinality: Indicates the maximum number of instances allowed in a relationship. Directionality: Determines if the relationship is one-way or two-way. Completeness: Shows whether participation in the relationship is mandatory or optional. Multiplicity: Defines the range of valid occurrences for each entity. Constraint enforcement: Ensures data integrity by enforcing rules on entity participation.

Entity Relationship Diagram (ERD) Symbols and Notations

There are three basic elements in an ER Diagram: entity, attribute, relationship. There are more elements which are based on the main elements. They are weak entity, multi valued attribute, derived attribute, weak relationship, and recursive relationship. Cardinality and ordinality are two other notations used in ER diagrams to further define relationships.

An entity can be a person, place, event, or object that is relevant to a given system. For example, a school system may include students, teachers, major courses, subjects, fees, and other items. Entities are represented in ER diagrams by a rectangle and named using singular nouns.

Weak Entity

A weak entity is an entity that depends on the existence of another entity. In more technical terms it can be defined as an entity that cannot be identified by its own attributes. It uses a foreign key combined with its attributed to form the primary key. An entity like order item is a good example for this. The order item will be meaningless without an order so it depends on the existence of the order.

An attribute is a property, trait, or characteristic of an entity, relationship, or another attribute. For example, the attribute Inventory Item Name is an attribute of the entity Inventory Item. An entity can have as many attributes as necessary. Meanwhile, attributes can also have their own specific attributes. For example, the attribute “customer address” can have the attributes number, street, city, and state. These are called composite attributes. Note that some top level ER diagrams do not show attributes for the sake of simplicity. In those that do, however, attributes are represented by oval shapes.

Multivalued Attribute

If an attribute can have more than one value it is called a multi valued attribute. It is important to note that this is different from an attribute having its own attributes. For example, a teacher entity can have multiple subject values.

Derived Attribute

An attribute based on another attribute. This is found rarely in ER diagrams. For example, for a circle, the area can be derived from the radius.

Relationship

A relationship describes how entities interact. For example, the entity “Carpenter” may be related to the entity “table” by the relationship “builds” or “makes”. Relationships are represented by diamond shapes and are labeled using verbs.

Recursive Relationship

If the same entity participates more than once in a relationship it is known as a recursive relationship. In the below example an employee can be a supervisor and be supervised, so there is a recursive relationship.

Cardinality and Ordinality

These two further defines relationships between entities by placing the relationship in the context of numbers. In an email system, for example, one account can have multiple contacts. The relationship, in this case, follows a “one to many” model. There are a number of notations used to present cardinality in ER diagrams. Chen, UML, Crow’s foot, Bachman are some of the popular notations. Creately supports Chen, UML and Crow’s foot notations.The following example uses UML to show cardinality.

How to Draw ER Diagrams

Below points show how to go about creating an ER diagram.

Identify all the entities in the system. An entity should appear only once in a particular diagram. Create rectangles for all entities and name them properly.
Identify relationships between entities. Connect them using a line and add a diamond in the middle describing the relationship.
Add attributes for entities. Give meaningful attribute names so they can be understood easily.

Sounds simple right? In a complex system, it can be a nightmare to identify relationships. This is something you’ll perfect only with practice.

Conceptual, Logical and Physical Data Models

Conceptual, logical, and physical data models are three distinct stages in the process of designing and implementing a database system. Each model serves a specific purpose and targets different levels of abstraction.

Conceptual Data Model

Purpose: The conceptual data model represents the highest level of abstraction and focuses on understanding the business requirements and concepts without considering implementation details. Characteristics: Describes entities, their attributes, and the relationships between them at a conceptual level. Independent of any specific database management system (DBMS) or technology. Provides a global view of the entire database system without delving into technical details. Representation: Often depicted using Entity-Relationship (ER) diagrams or similar graphical tools. Example: In a university system, the conceptual data model might include entities like Student, Course, and Instructor, along with their attributes and relationships.

Logical Data Model

Purpose: The logical data model translates the conceptual model into a more detailed and structured representation that can be implemented in a specific DBMS. Characteristics: Defines the structure of the database using tables, columns, keys, and relationships. Captures data requirements and relationships more precisely than the conceptual model. Still independent of the physical implementation details such as storage optimizations or indexing strategies. Representation: Often depicted using Entity-Relationship (ER) diagrams or Unified Modeling Language (UML) class diagrams, along with normalization techniques. Example: In the university system, the logical data model would specify tables like Student, Course, and Instructor, along with their attributes and primary/foreign keys.

Physical Data Model

Purpose: The physical data model represents the actual implementation of the database design in a specific DBMS, considering storage structures, indexing strategies, and optimization techniques. Characteristics: Translates the logical data model into a schema that can be directly implemented in a DBMS. Specifies details such as data types, indexes, partitions, and storage allocation. Optimized for performance, scalability, and efficiency based on the requirements of the application and the capabilities of the chosen DBMS. Representation: Often represented using Data Definition Language (DDL) scripts or database schema diagrams specific to the chosen DBMS. Example: In the university system, the physical data model would include details like table definitions with specific data types, indexes on frequently queried columns, and partitioning strategies for large tables.

Limitations of ER Diagrams

While Entity-Relationship diagrams are widely used for database design and modeling, they do have some limitations:

ER diagrams can get really complicated, especially in big systems with lots of entities and relationships. It can be tough to manage and understand these complicated diagrams, making it harder to see how the database works overall.

Sometimes ER diagrams don’t capture everything about the real world accurately. This can happen if the descriptions used to make the diagrams aren’t clear or if there are differences in how people understand things. It can lead to mistakes or confusion in the diagram.

ER diagrams focus on the big picture of the database structure, but they might miss out on some of the smaller details, like how the data is actually stored or used. This means they might not show everything about how the database works.

ER diagrams have trouble showing certain kinds of relationships or rules well. For example, really complicated structures or rules about time or space can be hard to draw accurately using ER diagrams.

ER diagrams might not be great at showing certain ideas from object-oriented programming, like inheritance or polymorphism. It can be tricky to translate these ideas into ER diagrams, and it might need extra explanations or changes to make them work.

As databases change over time, ER diagrams might need to be updated to show the changes accurately. Keeping track of these changes and making sure the diagrams match the actual database can take a lot of time and effort.

ER Diagram Best Practices

Provide a precise and appropriate name for each entity, attribute, and relationship in the diagram. Terms that are simple and familiar always beats vague, technical-sounding words. In naming entities, remember to use singular nouns. However, adjectives may be used to distinguish entities belonging to the same class (part-time employee and full-time employee, for example). Meanwhile attribute names must be meaningful, unique, system-independent, and easily understandable.

Remove vague, redundant or unnecessary relationships between entities.

Never connect a relationship to another relationship.

Make effective use of colors. You can use colors to classify similar entities or to highlight key areas in your diagrams.

Benefits of ER diagrams

ER diagrams constitute a very useful framework for creating and manipulating databases. First, ER diagrams are easy to understand and do not require a person to undergo extensive training to be able to work with it efficiently and accurately. This means that designers can use ER diagrams to easily communicate with developers, customers, and end users, regardless of their IT proficiency.

Second, ER diagrams are readily translatable into relational tables which can be used to quickly build databases. In addition, ER diagrams can directly be used by database developers as the blueprint for implementing data in specific software applications.

Lastly, ER diagrams may be applied in other contexts such as describing the different relationships and operations within an organization.

Drawing ER Diagrams Using Creately

You can draw entity relationship diagrams manually, especially when you are just informally showing simple systems to your peers. However, for more complex systems and for external audiences, you need diagramming software such as Creately to craft visually engaging and precise ER diagrams. The ER diagram software offered by Creately as an online service is pretty easy to use and is a lot more affordable than purchasing licensed software. It is also perfectly suited for development teams because of its strong support for collaboration.

FAQs about Entity Relationship Diagrams

Not defining the entities and relationships clearly
Overcomplicating the diagram by including too many entities and relationships
Using inconsistent naming conventions for entities and attributes
Failing to specify cardinality and participation constraints for relationships
Using unclear or ambiguous symbols or terminology

ER diagrams can represent several types of relationships, such as:

one-to-one,
one-to-many, and
many-to-many relationships.

Join over thousands of organizations that use Creately to brainstorm, plan, analyze, and execute their projects successfully.

Entity Relationship (ER) Diagram Model with DBMS Example

What is ER Diagram?

ER Diagram stands for Entity Relationship Diagram, also known as ERD is a diagram that displays the relationship of entity sets stored in a database. In other words, ER diagrams help to explain the logical structure of databases. ER diagrams are created based on three basic concepts: entities, attributes and relationships.

ER Diagrams contain different symbols that use rectangles to represent entities, ovals to define attributes and diamond shapes to represent relationships.

At first look, an ER diagram looks very similar to the flowchart. However, ER Diagram includes many specialized symbols, and its meanings make this model unique. The purpose of ER Diagram is to represent the entity framework infrastructure.

What is ER Model?

ER Model stands for Entity Relationship Model is a high-level conceptual data model diagram. ER model helps to systematically analyze data requirements to produce a well-designed database. The ER Model represents real-world entities and the relationships between them. Creating an ER Model in DBMS is considered as a best practice before implementing your database.

ER Modeling helps you to analyze data requirements systematically to produce a well-designed database. So, it is considered a best practice to complete ER modeling before implementing your database.

History of ER models

ER diagrams are visual tools that are helpful to represent the ER model. Peter Chen proposed ER Diagram in 1971 to create a uniform convention that can be used for relational databases and networks. He aimed to use an ER model as a conceptual modeling approach.

Why use ER Diagrams?

Here, are prime reasons for using the ER Diagram

Helps you to define terms related to entity relationship modeling
Provide a preview of how all your tables should connect, what fields are going to be on each table
Helps to describe entities, attributes, relationships
ER diagrams are translatable into relational tables which allows you to build databases quickly
ER diagrams can be used by database designers as a blueprint for implementing data in specific software applications
The database designer gains a better understanding of the information to be contained in the database with the help of ERP diagram
ERD Diagram allows you to communicate with the logical structure of the database to users

Facts about ER Diagram Model

Now in this ERD Diagram Tutorial, let’s check out some interesting facts about ER Diagram Model:

ER model allows you to draw Database Design
It is an easy to use graphical tool for modeling data
Widely used in Database Design
It is a GUI representation of the logical structure of a Database
It helps you to identifies the entities which exist in a system and the relationships between those entities

ER Diagrams Symbols & Notations

Entity Relationship Diagram Symbols & Notations mainly contains three basic symbols which are rectangle, oval and diamond to represent relationships between elements, entities and attributes. There are some sub-elements which are based on main elements in ERD Diagram. ER Diagram is a visual representation of data that describes how data is related to each other using different ERD Symbols and Notations.

Following are the main components and its symbols in ER Diagrams:

Rectangles: This Entity Relationship Diagram symbol represents entity types
Ellipses : Symbol represent attributes
Diamonds: This symbol represents relationship types
Lines: It links attributes to entity types and entity types with other relationship types
Primary key: attributes are underlined
Double Ellipses: Represent multi-valued attributes

Components of the ER Diagram

This model is based on three basic concepts:

Relationships

ER Diagram Examples

For example, in a University database, we might have entities for Students, Courses, and Lecturers. Students entity can have attributes like Rollno, Name, and DeptID. They might have relationships with Courses and Lecturers.

WHAT IS ENTITY?

A real-world thing either living or non-living that is easily recognizable and nonrecognizable. It is anything in the enterprise that is to be represented in our database. It may be a physical thing or simply a fact about the enterprise or an event that happens in the real world.

An entity can be place, person, object, event or a concept, which stores data in the database. The characteristics of entities are must have an attribute, and a unique key. Every entity is made up of some ‘attributes’ which represent that entity.

Examples of entities:

Person: Employee, Student, Patient
Place: Store, Building
Object: Machine, product, and Car
Event: Sale, Registration, Renewal
Concept: Account, Course

Notation of an Entity

An entity set is a group of similar kind of entities. It may contain entities with attribute sharing similar values. Entities are represented by their properties, which also called attributes. All attributes have their separate values. For example, a student entity may have a name, age, class, as attributes.

Example of Entities:

A university may have some departments. All these departments employ various lecturers and offer several programs.

Relationship

Relationship is nothing but an association among two or more entities. E.g., Tom works in the Chemistry department.

Entities take part in relationships. We can often identify relationships with verbs or verb phrases.

For example:

You are attending this lecture
I am giving the lecture
Just loke entities, we can classify relationships according to relationship-types:
A student attends a lecture
A lecturer is giving a lecture.

Weak Entities

A weak entity is a type of entity which doesn’t have its key attribute. It can be identified uniquely by considering the primary key of another entity. For that, weak entity sets need to have participation.

In above ER Diagram examples, “Trans No” is a discriminator within a group of transactions in an ATM.

Let’s learn more about a weak entity by comparing it with a Strong Entity

It is a single-valued property of either an entity-type or a relationship-type.

For example, a lecture might have attributes: time, date, duration, place, etc.

An attribute in ER Diagram examples, is represented by an Ellipse

Cardinality

Defines the numerical attributes of the relationship between two entities or entity sets.

Different types of cardinal relationships are:

One-to-One Relationships
One-to-Many Relationships
May to One Relationships
Many-to-Many Relationships

1.One-to-one:

One entity from entity set X can be associated with at most one entity of entity set Y and vice versa.

Example: One student can register for numerous courses. However, all those courses have a single line back to that one student.

2.One-to-many:

One entity from entity set X can be associated with multiple entities of entity set Y, but an entity from entity set Y can be associated with at least one entity.

For example, one class is consisting of multiple students.

3. Many to One

More than one entity from entity set X can be associated with at most one entity of entity set Y. However, an entity from entity set Y may or may not be associated with more than one entity from entity set X.

For example, many students belong to the same class.

4. Many to Many:

One entity from X can be associated with more than one entity from Y and vice versa.

For example, Students as a group are associated with multiple faculty members, and faculty members can be associated with multiple students.

How to Create an Entity Relationship Diagram (ERD)

Now in this ERD Diagram Tutorial, we will learn how to create an ER Diagram. Following are the steps to create an ER Diagram:

Let’s study them with an Entity Relationship Diagram Example:

Step 1) Entity Identification

We have three entities

Step 2) Relationship Identification

We have the following two relationships

The student is assigned a course
Professor delivers a course

Step 3) Cardinality Identification

For them problem statement we know that,

A student can be assigned multiple courses
A Professor can deliver only one course

Step 4) Identify Attributes

You need to study the files, forms, reports, data currently maintained by the organization to identify attributes. You can also conduct interviews with various stakeholders to identify entities. Initially, it’s important to identify the attributes without mapping them to a particular entity.

Once, you have a list of Attributes, you need to map them to the identified entities. Ensure an attribute is to be paired with exactly one entity. If you think an attribute should belong to more than one entity, use a modifier to make it unique.

Once the mapping is done, identify the primary Keys. If a unique key is not readily available, create one.

Steps to Create an Entity Relationship Diagram

For Course Entity, attributes could be Duration, Credits, Assignments, etc. For the sake of ease we have considered just one attribute.

Step 5) Create the ERD Diagram

A more modern representation of Entity Relationship Diagram Example

Best Practices for Developing Effective ER Diagrams

Here are some best practice or example for Developing Effective ER Diagrams.

Eliminate any redundant entities or relationships
You need to make sure that all your entities and relationships are properly labeled
There may be various valid approaches to an ER diagram. You need to make sure that the ER diagram supports all the data you need to store
You should assure that each entity only appears a single time in the ER diagram
Name every relationship, entity, and attribute are represented on your diagram
Never connect relationships to each other
You should use colors to highlight important portions of the ER diagram
ER Model in DBMS stands for an Entity-Relationship model
The ER model is a high-level data model diagram
ER diagrams are a visual tool which is helpful to represent the ER model
ER diagrams in DBMS are blueprint of a database
Entity relationship diagram DBMS displays the relationships of entity set stored in a database
ER diagrams help you to define terms related to entity relationship modeling
ER Model in DBMS is based on three basic concepts: Entities, Attributes & Relationships
An entity can be place, person, object, event or a concept, which stores data in the database (DBMS)
Relationship is nothing but an association among two or more entities
A weak entity is a type of entity which doesn’t have its key attribute
It is a single-valued property of either an entity-type or a relationship-type
It helps you to defines the numerical attributes of the relationship between two entities or entity sets
ER- Diagram DBMS is a visual representation of data that describe how data is related to each other
While Drawing ER diagrams in DBMS, you need to make sure all your entities and relationships are properly labeled.
Difference between Clustered and Non-clustered index
Difference Between DDL and DML in DBMS
Difference Between File System and DBMS
Difference Between Primary Key and Foreign Key
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What is Entity Relationship Diagram (ERD)?

Database is absolutely an integral part of software systems. To fully utilize ER Diagram in database engineering guarantees you to produce high-quality database design to use in database creation, management, and maintenance. An ER model also provides a means for communication.

Today we're going to walk you through everything you need to know about ER Diagramming. By reading this ERD guide, you will get the essential knowledge and skills about ER Diagrams and database design. You will learn things like what is ERD, why ERD, ERD notations, how to draw ERD, etc. along with a bunch of ERD examples.

Design Database Faster, Better and Easier

Are you looking for a Free ERD tool for creating data models faster, easier and quicker? Visual Paradigm Community Edition provides you with an ERD editor for database design. It is an international award-winning modeler, and yet it is easy-to-use, intuitive & completely free.

What is an ER diagram (ERD)?

First of all, what is an Entity Relationship Diagram?

Entity Relationship Diagram, also known as ERD, ER Diagram or ER model, is a type of structural diagram for use in database design. An ERD contains different symbols and connectors that visualize two important information: The major entities within the system scope , and the inter-relationships among these entities .

And that's why it's called "Entity" "Relationship" diagram (ERD)!

When we talk about entities in ERD, very often we are referring to business objects such as people/roles (e.g. Student), tangible business objects (e.g. Product), intangible business objects (e.g. Log), etc. "Relationship" is about how these entities relate to each other within the system.

ER Diagram depicts business entities relationship

In a typical ER design, you can find symbols such as rounded rectangles and connectors (with different styles of their ends) that depict the entities, their attributes, and inter-relationships.

When to draw ER Diagrams?

So, when do we draw ERDs? While ER models are mostly developed for designing relational databases in terms of concept visualization and in terms of physical database design, there are still other situations when ER diagrams can help. Here are some typical use cases.

Database design - Depending on the scale of change, it can be risky to alter a database structure directly in a DBMS. To avoid ruining the data in a production database, it is important to plan out the changes carefully. ERD is a tool that helps. By drawing ER diagrams to visualize database design ideas, you have a chance to identify the mistakes and design flaws, and to make corrections before executing the changes in the database.
Database debugging - To debug database issues can be challenging, especially when the database contains many tables, which require writing complex SQL in getting the information you need. By visualizing a database schema with an ERD, you have a full picture of the entire database schema. You can easily locate entities, view their attributes and identify the relationships they have with others. All these allow you to analyze an existing database and to reveal database problems easier.
Database creation and patching - Visual Paradigm, an ERD tool, supports a database generation tool that can automate the database creation and patching process by means of ER diagrams. So, with this ER Diagram tool, your ER design is no longer just a static diagram but a mirror that reflects truly the physical database structure.
Aid in requirements gathering - Determine the requirements of an information system by drawing a conceptual ERD that depicts the high-level business objects of the system. Such an initial model can also be evolved into a physical database model that aids the creation of a relational database, or aids in the creation of process maps and data flow modes.

ERD notations guide

An ER Diagram contains entities, attributes, and relationships. In this section, we will go through the ERD symbols in detail.

An ERD entity is a definable thing or concept within a system , such as a person/role (e.g. Student), object (e.g. Invoice), concept (e.g. Profile) or event (e.g. Transaction) (note: In ERD, the term "entity" is often used instead of "table", but they are the same). When determining entities, think of them as nouns. In ER models, an entity is shown as a rounded rectangle, with its name on top and its attributes listed in the body of the entity shape. The ERD example below shows an example of an ER entity.

Entity Attributes

Also known as a column, an attribute is a property or characteristic of the entity that holds it .

An attribute has a name that describes the property and a type that describes the kind of attribute it is, such as varchar for a string, and int for integer. When an ERD is drawn for physical database development, it is important to ensure the use of types that are supported by the target RDBMS.

The ER diagram example below shows an entity with some attributes in it.

Primary Key

Also known as PK, a primary key is a special kind of entity attribute that uniquely defines a record in a database table . In other words, there must not be two (or more) records that share the same value for the primary key attribute. The ERD example below shows an entity 'Product' with a primary key attribute 'ID', and a preview of table records in the database. The third record is invalid because the value of ID 'PDT-0002' is already used by another record.

Foreign Key

Also known as FK, a foreign key is a reference to a primary key in a table . It is used to identify the relationships between entities. Note that foreign keys need not be unique. Multiple records can share the same values. The ER Diagram example below shows an entity with some columns, among which a foreign key is used in referencing another entity.

Relationship

A relationship between two entities signifies that the two entities are associated with each other somehow . For example, a student might enroll in a course. The entity Student is therefore related to Course, and a relationship is presented as a connector connecting between them.

Cardinality

Cardinality defines the possible number of occurrences in one entity which is associated with the number of occurrences in another . For example, ONE team has MANY players. When present in an ERD, the entity Team and Player are inter-connected with a one-to-many relationship.

In an ER diagram, cardinality is represented as a crow's foot at the connector's ends. The three common cardinal relationships are one-to-one, one-to-many, and many-to-many.

One-to-One cardinality example

A one-to-one relationship is mostly used to split an entity in two to provide information concisely and make it more understandable. The figure below shows an example of a one-to-one relationship.

One-to-Many cardinality example

A one-to-many relationship refers to the relationship between two entities X and Y in which an instance of X may be linked to many instances of Y, but an instance of Y is linked to only one instance of X. The figure below shows an example of a one-to-many relationship.

Many-to-Many cardinality example

A many-to-many relationship refers to the relationship between two entities X and Y in which X may be linked to many instances of Y and vice versa. The figure below shows an example of a many-to-many relationship. Note that a many-to-many relationship is split into a pair of one-to-many relationships in a physical ERD. You will know what a physical ERD is in the next section.

Conceptual, Logical and Physical data models

An ER model is typically drawn at up to three levels of abstraction:

Conceptual ERD / Conceptual data model
Logical ERD / Logical data model
Physical ERD / Physical data model

While all the three levels of an ER model contain entities with attributes and relationships, they differ in the purposes they are created for and the audiences they are meant to target.

A general understanding to the three data models is that business analyst uses a conceptual and logical model to model the business objects exist in the system, while database designer or database engineer elaborates the conceptual and logical ER model to produce the physical model that presents the physical database structure ready for database creation. The table below shows the difference between the three data models.

Conceptual model vs Logical model vs Data model:

Conceptual data model

Conceptual ERD models the business objects that should exist in a system and the relationships between them . A conceptual model is developed to present an overall picture of the system by recognizing the business objects involved. It defines what entities exist, NOT which tables. For example, 'many to many' tables may exist in a logical or physical data model but they are just shown as a relationship with no cardinality under the conceptual data model.

Conceptual data model example

NOTE: Conceptual ERD supports the use of generalization in modeling the 'a kind of' relationship between two entities, for instance, Triangle, is a kind of Shape. The usage is like generalization in UML. Notice that only conceptual ERD supports generalization.

Logical data model

Logical ERD is a detailed version of a Conceptual ERD . A logical ER model is developed to enrich a conceptual model by defining explicitly the columns in each entity and introducing operational and transactional entities. Although a logical data model is still independent of the actual database system in which the database will be created, you can still take that into consideration if it affects the design.

Logical data model example

Physical data model

Physical ERD represents the actual design blueprint of a relational database . A physical data model elaborates on the logical data model by assigning each column with type, length, nullable, etc. Since a physical ERD represents how data should be structured and related in a specific DBMS it is important to consider the convention and restriction of the actual database system in which the database will be created. Make sure the column types are supported by the DBMS and reserved words are not used in naming entities and columns.

Physical data model example

How to draw an ER diagram?

If you find it difficult to get started with drawing an ER diagram, don't worry. In this section, we will give you some ERD tips. Try to follow the steps below to understand how to draw an ER diagram effectively.

Make sure you are clear about the purpose of drawing the ERD. Are you trying to present an overall system architecture that involves the definition of business objects? Or are you developing an ER model ready for database creation? You must be clear about the purpose to develop an ER diagram at the right level of detail (Read the section Conceptual, Logical and Physical Data Models for more details)
Make sure you are clear about the scope to model. Knowing the modeling scope prevents you from including redundant entities and relationships in your design.
Draw the major entities involved in the scope.
Define the properties of entities by adding columns.
Review the ERD carefully and check if the entities and columns are enough to store the data of the system. If not, consider adding additional entities and columns. Usually, you can identify some transactional, operational and event entities in this step.
Consider the relationships between all entities and relate them with proper cardinality (e.g A one-to-many between entity Customer and Order). Don't worry if there are orphan entities. Although it's not common, it's legit.
Apply the technique of database normalization to re-structure the entities in a way that can reduce data redundancy and improve data integrity. For example, the details of the manufacturer might be stored under the Product entity initially. During the process of normalization, you may find that the detail keeps repeating records over records, then you can split it as a separate entity Manufacturer, and with a foreign key that links between Product and Manufacturer.

Data model examples

Erd example - movie rental system.

ERD example - Loan System

ERD example - Online Shop

Using ERD with Data Flow Diagram (DFD)

In system analysis and design, Data Flow Diagram (DFD) can be drawn to visualize the flow of information within system processes. In a Data Flow Diagram, there is a symbol called Data Store, which represents a database table that provides the information needed by the system.

Since a physical ER Diagram provides a blueprint of an actual database, the entities in such an ERD are aligned with datastores in a DFD. You can draw ERD as a complement to DFD by representing the structure of information that flows within a system, or, on the contrary, to draw DFD in complementing an ERD by showing how the data will be utilized by the system in runtime.

Using ERD with BPMN Business Process Diagram (BPD)

In business process mapping, BPMN Business Process Diagram (BPD) can be drawn to visualize business workflows. In a Business Process Diagram, there is a symbol called Data Object, which represents the data input into / output from process activities.

Since a conceptual and logical data model provides a high-level view of business objects within a system, the entities in such ERDs are aligned with data objects in BPD. You can draw ERD as a complement to BPD by representing the structure of data objects needed by a business workflow, or, on the contrary, to draw BPD in complementing an ERD by showing how the data will be utilized throughout a business process.

Choosing an ERD tool

It takes time and effort to develop a data model with ERD. A helpful database design tool should be able to reduce your time and effort spent. Visual Paradigm provides you with not only an ERD tool but also a set of visual modeling features that helps you draw faster and easier. It supports most of the popular relational database management systems in the market today both in terms of database design, database generation, and ERD reversal.

The ERD designer is available in Visual Paradigm Modeler , which costs only US $6 per month . We would recommend you download and have a try . 30 days of FREE evaluation is offered. No credit card required.

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Explaining an ER Diagram, With Steps and Use Cases

Sudip is a TOGAF Certified Solutions Architect with more than 15 years spent in the IT industry. He is now a full-time freelance technical writer and has contributed to several publications on various topics including the cloud, DevOps, SaaS, and cybersecurity. When not reading or writing, he is found playing a game of chess or in a squash court.

Entity-Relationship Diagram
Vertabelo Features

Get to know what an ER Diagram is through use cases and examples. Explore the notations for the essential components of an ERD.

Entity-relationship diagrams (ERDs) are used to visualize data and relationships among the entities of a system. At its core, an ER Diagram explains the logical structure and the flow of information within a data model. To do so, an entity-relationship diagram highlights entities, attributes , and relationships through predefined symbols for effective visualization of the architecture. Preparing an ERD is an essential first step towards designing a database, helping to analyze data flow and helping with due diligence of related system requirements.

When you Need an ER Diagram

An ER diagram is used to design database data models. If you are designing a new data model, preparing an ER Diagram helps with essential due diligence to capture and document system requirements. While in production, an ER diagram acts as a reference to improve database throughput , debug errors , and redesign architecture .

In addition to technical references, as ERDs are conceptual blueprint of the data flow within a system, they are also used to streamline business processes by identifying redundancies and bottlenecks within business entities.

In this article, we will go through a few ER diagram examples and how you can use Vertabelo to create ER diagrams to design efficient data models.

Objects in ER Diagrams

While there are several notations, the crow’s foot notation (also known as the information engineering notation or the IE notation) is prominently used in ER modeling due to its intuitive format and symbols. Let us delve into the representation of entities and relationships in crow’s foot notation to help model an ER diagram.

Entities represent data components within a database that could be living or non-living, real or abstract, so long as their data is stored in the database. Examples of entities include people, places, objects, events, or concepts. In ER diagrams, entities are usually depicted by rectangles, with the entity name at the top.

Client, City and Country Entities of a Data Model

An attribute is a description of the properties of an entity or relationship. For instance, the entity shipment could have attributes such as shipment ID ( id ), client_id , shipment time_created , billing_address , etc. In the crow’s foot notation, an attribute is represented as a line of text in the lower compartment of the corresponding entity’s rectangle.

A Snapshot Showing Various Attributes of the shipment Entity

Relationship

A relationship denotes how various entities interact with each other. For instance, in a database for a vehicle hiring service, a customer will form a relationship with the entity vehicle through the act of selecting . “Select” is, therefore, a relationship between the two entities.

The relationship between data in one table and data in another table is called cardinality . Specifically, the cardinality indicates the number of times one entity in a table can relate with the instances of another entity.

When drawing relationships in crow’s foot notation, there are two indicators: one for multiplicity (cardinality) while the other indicates whether a relationship is optional or mandatory. A mandatory relationship is shown by a line perpendicular to the relationship line, while an optional relationship is shown by an empty circle.

In data modeling, there are three types of cardinalities.

In a one-to-one association, one entity in a table can relate only once to an entity in another table. For instance, a customer can hire only one vehicle at a time, and a vehicle can be assigned to only one customer at a time.

In an entity-relationship diagram, one row in one table would correlate to only one row in another table. In the IE notation, a mandatory one-to-one relationship is represented by two lines perpendicular to the relationship line near both entity rectangles.

One-to-One Association With Mandatory Relationship

One-to-One Association With Optional Relationship

One-to-Many

A one-to-many relationship occurs when one instance of an entity can interact with multiple instances of another entity. For instance, one customer can hire several vehicles, while each vehicle can only be assigned to one customer at a time.

In the IE notation, a one-to-many relationship is represented by a single line at the end of the single instance, and a three-pronged crow’s-foot symbol facing the multiple instance rectangle.

One-to-Many Association With Mandatory Relationship

Many-to-Many

This type of cardinality occurs when multiple instances of one entity can relate with more than one instance of another set of entities. Imagine a scenario in which a customer could select multiple vehicles, and a vehicle could be leased by multiple customers within a certain time period. In the IE notation, a many-to-many relationship is depicted by crow’s feet at both ends of the relationship line.

Many-to-Many Association With Mandatory Relationship

Many-to-Many Association With Optional Relationship

While the above notations are in crow’s foot notation, there are a number of other ERD notation formats, the details of which can be found here .

Types of Data Models

There are three types of data models in ER modeling.

Conceptual and Logical Data Models

The conceptual and logical data models describe how information is organized in a system regardless of the database used. The logical model specifies entities, attributes, and relationships between entities. It abstracts away from actual DBMS used in the implementation of the system.

Physical Data Model

The physical data model represents how the model will be built in the database. It shows the full table definition, including column names, column data types, table constraints, the primary key, the foreign keys, and the relationships between tables. The physical data model will be different for different RDBMS. For example, the data type for a given column may be different between MySQL and SQL Server.

This section appears incomplete. There is no explanation of what a conceptual model is (as opposed to logical). Also, the last sentence is incomplete. here .-->

How to Draw an ER Diagram

Let’s create an ER diagram for a data model using Vertabelo . Consider a simple scenario in which a client orders food at a restaurant. The client must purchase one or more menu items, while each menu item is served by one attendant.

1. First, identify the entities in your database. In this case, we have three entities: Client , Menu_Item , and Attendant .

2. The second step involves identifying the relationships between the selected entities.

The Client is served a Menu_Item .
The Attendant delivers the Menu_Item .

3. The third step involves identifying cardinalities .

A Client can be assigned multiple Menu_Item s.
An Attendant can only deliver one Menu_Item at a time before taking another order from the same Client (assumption) .

4. The fourth step is identifying entity attributes . Make sure that every attribute is mapped to only one entity; assign modifiers for those that belong to more than one.

Specify the primary key for each entity by using the most uniquely identifying attributes.

Setting the Attributes of an Entity Using the Vertabelo Property Editor

5. Once you have identified the entities, relationships, cardinalities, and attributes, you can now create your ER diagram. Here’s what our sample project will look like when designed using the crow’s foot (IE) notation.

Disclaimer: All the above diagrams were created using Vertabelo .

Data modeling challenges in the real world are often complex. Creating a precise ER diagram requires not only the right knowledge but also the right tools. Whether you are learning or designing a data model, Vertabelo acts as a great resource to your ERD designing needs. To find out more about Vertabelo features and how it can help, visit this article .

ER Diagram Example Use Cases

Let’s look at a few examples of the entity-relationship diagram to understand its use cases better.

Use Case: Data Model for a Freelancers Collective

You can find a detailed discussion of this ER diagram in A Data Model for a Freelancers Collective .

This model shows the logical structure that can be used in large freelance projects that require collaboration between distributed teams. Since the freelance world connects professionals in a wide range of fields with varying skill sets, you will need a tool to orchestrate the interactions among freelancers, teams, and clients. Let’s consider the Freelancer Collective platform as a project management solution that helps connect various actors to collaborate on a number of projects.

Our model is broken into four main subject areas: Freelancers , Customers & Projects , Teams , and Project Phases .

The Freelancers section includes all the information provided by freelancers when they register to use the application. The information relevant to our database includes the freelancer’s skills, skill level, and skill sets. We also need to understand the freelancer’s availability to be sure that they can deliver an assigned project.

The second focus area is Customers & Projects . Customers use the system to upload their projects and connect with freelancers. This section includes the customer , project , project_status_history , skill , and project_outcome tables. Customers have also registered to use the application, and the system extracts their details from a special form. Project details are revealed when the client posts a project.

The third section is for the teams . This subject area forms a team and assigns them a project based on the freelancer’s ability and skill sets. The team is the major entity for this section. Other tables in this section include team_member , in_charge , freelancer , phase_plan , and project .

The final section involves the Project phases . Some entities in this section have appeared in other subject areas, and these include freelancer , customer , project_outcome , and project . The new entities in this set include phase_history , phase_catalog , and phase_plan .

Relationships

When a client posts a project, the system checks for the skill requirements and the availability of freelancers. The system then creates a team of freelancers who will collaborate on the project, which is now divided into phases. This system works as a supervisor, looking for the best collective that will work on a project, and assigning different project phases to different freelancers depending on the availability and skill level.

Collectively, this is how the data model can look:

Use Case: Peer-to-Peer Lending Data Model

You can find a detailed discussion of this ER diagram in A Peer-to-Peer Lending Platform Data Model .

Peer-to-peer lending refers to the practice of multiple lenders and borrowers transacting through a common platform. A peer-to-peer lending platform here essentially acts as a liaison between the parties to enable the process of lending, while ensuring necessary compliance and maintaining data security of all parties.

Let’s understand the data model by considering a scenario.

The entities are the following:

A borrower requests a loan of a specific amount through the peer-to-peer lending platform after submitting details of his credit score, default history, tax returns, etc. Additional details of the loan may include repayment duration and preferred interest rate window.
The lender(s) register(s) on the platform by entering its respective financial details, including KYC, tax returns, etc. It also enters its lending preferences, including the loan duration, interest rate, amount, borrower credit score, etc.

The borrower asks for funding from an investor, who releases the funds through the loan fulfilment and repayment subsystem. This subsystem forms an associative relationship between the two entities.

The lending platform here essentially acts as the interface, connecting would-be investors with potential borrowers. This reduces the complexity of access to financing by allowing users to determine their own lending rates. The data model that can support this platform is outlined below:

An ER Diagram Is a Must

An ER diagram provides an easy way to represent your data model at a higher level of abstraction. With marked-up relationships among data sets, an ER diagram is perfect for process modeling and system debugging. In this article, we discussed the core concepts of ER modeling, with practical examples using Vertabelo for pragmatic experience. Whether you are learning or working on real-time data modeling, creating an ER diagram is a must.

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Entity Relationship Diagram (ERD)

Quickly generate er diagrams from data or start with a built-in template, what is erd, types of erd, erd symbols, cardinality types, erd data models, data generated erd, how to make an erd, er diagram tips, erd examples, with smartdraw, you can create many different types of diagrams, charts, and visuals, what is an entity relationship diagram (erd).

ERD stands for entity relationship diagram. People also call these types of diagrams ER diagrams and Entity Relationship Models. An ERD visualizes the relationships between entities like people, things, or concepts in a database. An ERD will also often visualize the attributes of these entities.

By defining the entities, their attributes, and showing the relationships between them, an ER diagram can illustrate the logical structure of databases. This is useful for engineers hoping to either document a database as it exists or sketch out a design of a new database.

Why Make an ERD?

An ER diagram can help businesses document existing databases and thereby troubleshoot logic or deployment problems or spot inefficiencies and help improve processes when a business wants to undertake business process re-engineering. ERDs can also be used to design and model new databases and make sure that engineers can identify any logic or design flaws before they're implemented in production.

Document an existing database structure
Debug, troubleshoot, and analyze
Design a new database
Gather design requirements
Business process re-engineering (BPR)

When documenting a system or process, looking at the system in multiple ways increases the understanding of that system. ERD diagrams are commonly used in conjunction with a data flow diagram to display the contents of a data store. They help us to visualize how data is connected in a general way, and are particularly useful for constructing a relational database.

The History of Entity Relationship Diagrams

Peter Chen developed ERDs in the 1970s and published his proposal for entity relationship modeling in a 1976 paper titled "The Entity-Relationship Model: Toward a Unified View of Data". Peter Chen was a computer scientist who worked on improving database design. His entity relationship model was a way to visualize a database that unified other existing models into a single understanding that removed ambiguities. Prior to ERDs, there were three data models for databases: the network model, the relational model, and the entity set model. Each had their own strengths and weaknesses, but none provided a complete view of the database. With an ERD, Chen could provide a unified framework for database modeling.

Peter Chen's work was greatly influenced by scientists and engineers who came before him, specifically Charles Bachman, who worked on visualizing databases in the 1960s and his data structure diagrams became known as Bachman diagrams.

Chen's entity relationship model is in many ways the foundation for later practices like Unified Modeling Language or UML in information systems.

In the 1980s, another computer scientist named James Martin, worked to further refine Chen's ER model and introduced what's known today as the IE notation. IE notation uses Crow's foot to express cardinality (one to many relationship) instead of Chen's notation to epxress the same.

Types of Entity Relationship Diagrams

ER diagrams will differ on how they express cardinality. They will also differ in how they display entities and their attributes and whether or not they show relationships or attributes as separate symbols.

Traditional ERD

The traditional Chen ERD is like a flowchart with connected symbols for entities, relationships, and attributes. Since its first introduction by Chen in the 70s, others have proposed different cardinality notations, but the basic symbols used and how they're connected tend to look the same.

IDEF1X Notation ERD - Relational Schema

IDEF1X stands for integrated definition for data modeling. This type of ER diagram will show entities connected to each other without relationship symbols. The attributes for any entity will be listed as part of a table inside each entity shape instead of separate symbols. Some also call this type of ER diagram a Relational Schema diagram.

Common ERD Symbols

An ER diagram has three main components: entities, relationships, and attributes connected by lines.

Entities , which are represented by rectangles. An entity is an object or concept about which you want to store information. A weak entity is an entity that must be defined by a foreign key relationship with another entity as it cannot be uniquely identified by its own attributes alone.
Relationships , which are represented by diamond shapes, show how two entities share information in the database. In some cases, entities can be self-linked.
Attributes , which are represented by ovals. A key attribute is the unique, distinguishing characteristic of the entity. For example, an employee's social security number might be the employee's key attribute. A multivalued attribute can have more than one value. For example, an employee entity can have multiple skill values. A derived attribute is based on another attribute. For example, an employee's monthly salary is based on the employee's annual salary.
Connecting lines , solid lines that connect attributes and show the relationships of entities in the diagram.
Cardinality specifies the numerical attribute of the relationship between entities. It can be one-to-one, many-to-one, or many-to-many.

Styles of Cardinality

Cardinality is the mathematical sense just means the number of values in a set. In relationship to databases and ERD, cardinality specifies how many instances of an entity relate to one instance of another entity. Ordinality is also closely linked to cardinality. While cardinality specifies the occurrences of a relationship, ordinality describes the relationship as either mandatory or optional. In other words, cardinality specifies the maximum number of relationships and ordinality specifies the absolute minimum number of relationships.

In other words, there will be multiple instances of each entity in a database. Cardinality allows you express the number of each entity that can be associated with another entity. For example, in an employee database, a manager will have multiple employee reports (in a one to many relationship), but an employee will only have one ID number (a one to one relationship). There are three main types of relationships in a database expressed using cardinality notation in an ER diagram.

one-to-many
many-to-many

There are many notation styles that express cardinality. Information Engineering Style, IE Notation or Crow's Foot Notation

Information Engineering Style Cardinality - ERD

Entity Relationship Models can also vary based on the level of abstraction visualized. There are usually three models people refer to based on the level of detail you want to show: conceptual ERD, logical ERD, and physical ERD.

Conceptual ERD or data model : This model has the most abstraction and least amount of detail, as such it's appropriate for large projects that need a higher level view used by business analysts. A typical conceptual ERD will contain entities and relationships, but offer no details on specific database columns or cardinalities. It's a general, high-level view of database design.
Logical ERD or data model : This model adds more detail to the conceptual model by defining additional entities that are operational and transactional.
Physical ERD or data model : This model serves as the actual design or blueprint of the database with lots of technical details including defining cardinality and showing primary and foreign keys of entities instead of just their abstract semantic names. For this type of ERD, attributes will often be listed to represent the columns of the real database table.

Documenting an Existing Database from Data

There are two reasons to create a database diagram. You're either designing a new schema or you need to document your existing structure.

If you have an existing database you need to document, you can create a database diagram using data directly from your database. You can export your database structure as a CSV file ( there are some scripts on how to this here ), then have a program generate the ERD automatically.

This will be the most accurate portrait of your database and will require no drawing on your part.

Here's an example of a very basic database structure generated from data.

If you want to create a new plan, you can edit the generated diagram and collaborate with your team on what changes to make.

Learn more about generating ER diagrams from data automatically using SmartDraw's ERD extension.

ERD Explained

Watch this quick video learn more about ERD diagrams and their components.

Entity Relationship Diagram Tutorial

Here are some best practice tips for constructing an ERD:

Identify relationships. Look at two entities, are they related? If so draw a solid line connecting the two entities and add a diamond between them with a brief description of how they are related.
Add attributes. Any key attributes of entities should be added using oval-shaped symbols.
Complete the diagram. Continue to connect the entities with lines, and adding diamonds to describe each relationship until all relationships have been described. Each of your entities may not have any relationships, some may have multiple relationships. That is okay.

Tips for Effective ER Diagrams

Make sure that each entity only appears once per diagram.
Name every entity, relationship, and attribute on your diagram.
Examine relationships between entities closely. Are they necessary? Are there any relationships missing? Eliminate any redundant relationships. Don't connect relationships to each other.
Use colors to highlight important portions of your diagram.

Entity Relationship Diagram Examples

The best way to understand ER diagrams is to look at some examples of ER diagrams.

Click on any of these ER diagrams included in SmartDraw and edit them:

Internet Sales Entity Relationship Diagram

Browse SmartDraw's entire collection of ERD examples and templates

More ER Diagram Information

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What is an Entity Relationship Diagram (ERD)?

What are your erd needs.

Learn the essentials of ER Diagrams and ER Models, along with their origins, uses, examples, components, limitations and guidelines on how to draw them using our ER diagram tool.

10 minute read

Want to make an ERD of your own? Try Lucidchart. It's quick, easy, and completely free.

What is an ER diagram?

An Entity Relationship (ER) Diagram is a type of flowchart that illustrates how “entities” such as people, objects or concepts relate to each other within a system. ER Diagrams are most often used to design or debug relational databases in the fields of software engineering, business information systems, education and research. Also known as ERDs or ER Models, they use a defined set of symbols such as rectangles, diamonds, ovals and connecting lines to depict the interconnectedness of entities, relationships and their attributes. They mirror grammatical structure, with entities as nouns and relationships as verbs.

ER diagrams are related to data structure diagrams (DSDs), which focus on the relationships of elements within entities instead of relationships between entities themselves. ER diagrams also are often used in conjunction with data flow diagrams (DFDs), which map out the flow of information for processes or systems.

History of ER models

Peter Chen (a.k.a. Peter Pin-Shan Chen), currently a faculty member at Carnegie-Mellon University in Pittsburgh, is credited with developing ER modeling for database design in the 1970s. While serving as an assistant professor at MIT’s Sloan School of Management, he published a seminal paper in 1976 titled “The Entity-Relationship Model: Toward a Unified View of Data.”

In a broader sense, the depiction of the interconnectedness of things dates back to least ancient Greece, with the works of Aristotle, Socrates and Plato. It’s seen more recently in the 19th and 20th Century works of philosopher-logicians like Charles Sanders Peirce and Gottlob Frege.

By the 1960s and 1970s, Charles Bachman (above) and A.P.G. Brown were working with close predecessors of Chen’s approach. Bachman developed a type of Data Structure Diagram, named after him as the Bachman Diagram. Brown published works on real-world systems modeling. James Martin added ERD refinements. The work of Chen, Bachman, Brown, Martin and others also contributed to the development of Unified Modeling Language (UML), widely used in software design.

Uses of entity relationship diagrams

Database design:, database troubleshooting:, business information systems:, business process re-engineering (bpr):, the components and features of an er diagram.

ER Diagrams are composed of entities, relationships and attributes. They also depict cardinality, which defines relationships in terms of numbers. Here’s a glossary:

A definable thing—such as a person, object, concept or event—that can have data stored about it. Think of entities as nouns. Examples: a customer, student, car or product. Typically shown as a rectangle.

Entity type:

Entity set:, entity categories:, strong entity, weak entity, entity keys:, candidate key:, primary key:, foreign key:, relationship.

How entities act upon each other or are associated with each other. Think of relationships as verbs. For example, the named student might register for a course. The two entities would be the student and the course, and the relationship depicted is the act of enrolling, connecting the two entities in that way. Relationships are typically shown as diamonds or labels directly on the connecting lines.

Recursive relationship:

A property or characteristic of an entity. Often shown as an oval or circle.

Descriptive attribute:

Attribute categories:, multi-value:, single-value:, one-to-one example, one-to-many example (or many-to-one, depending on the relationship direction):, many-to-many example:, cardinality views:, cardinality constraints:, mapping natural language.

ER components can be equated to parts of speech, as Peter Chen did. This shows how an ER Diagram compares to a grammar diagram:

Common noun:

Proper noun:.

The database query language ERROL actually mimics natural language constructs. ERROL is based on reshaped relational algebra (RRA) and works with ER models, capturing their linguistic aspects.

ERD symbols and notations

There are several notation systems, which are similar but vary in a few specifics.

Chen notation style

Crow’s foot/martin/information engineering style, bachman style, idef1x style, barker style.

Following are examples of ERD diagrams made in each system.

Conceptual, logical and physical data models

ER models and data models are typically drawn at up to three levels of detail:

Conceptual data model:

Logical data model:, physical data model:.

Note that similar detail and scope levels exist in other types of diagrams, such as data flow diagrams, but that it contrasts with software engineering’s three schema approach, which divides the information a bit differently. Sometimes, engineers will branch out ER diagrams with additional hierarchies to add necessary information levels for database design. For example, they may add groupings by extend up with superclasses and down with subclasses.

Limitations of ER diagrams and models

Only for relational data:, not for unstructured data:, difficulty integrating with an existing database:, how to draw a basic er diagram, purpose and scope:, relationships:, attributes:, cardinality:, more tips for er diagrams.

Show the level of detail necessary for your purpose. You might want to draw a conceptual, logical or physical model, depending on the detail needed. (See above for descriptions of those levels.)

Watch for redundant entities or relationships.

If you’re troubleshooting a database problem, watch for holes in relationships or missing entities or attributes.

Make sure all your entities and relationships are labeled.

You can translate relational tables and ER diagrams back and forth, if that helps you achieve your goal.

Make sure the ER diagram supports all the data you need to store.

There may be different valid approaches to an ER diagram. As long as it provides the necessary information for its scope and purpose, it’s good.

Helpful Resources

How to Draw an ER Diagram
Entity-Relationship Diagram Symbols and Notation

Lucidchart lets you easily create ER diagrams, with smooth placement of shapes, lines and labels. With all editing taking place in the cloud, it’s easy to collaborate with colleagues. You can share your diagram digitally or via print.

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DBMS Tutorial - Database Management System

Basic of DBMS

Introduction of DBMS (Database Management System) - Set 1
History of DBMS
Advantages of Database Management System
Disadvantages of DBMS
Application of DBMS
Need for DBMS
DBMS Architecture 1-level, 2-Level, 3-Level
Difference between File System and DBMS

Entity Relationship Model

Introduction of er model.

Structural Constraints of Relationships in ER Model
Difference between entity, entity set and entity type
Difference between Strong and Weak Entity
Generalization, Specialization and Aggregation in ER Model
Recursive Relationships in ER diagrams

Relational Model

Introduction of Relational Model and Codd Rules in DBMS
Types of Keys in Relational Model (Candidate, Super, Primary, Alternate and Foreign)
Anomalies in Relational Model
Mapping from ER Model to Relational Model
Strategies for Schema design in DBMS

Relational Algebra

Introduction of Relational Algebra in DBMS
Basic Operators in Relational Algebra
Extended Operators in Relational Algebra
SQL | Join (Inner, Left, Right and Full Joins)
Join operation Vs Nested query in DBMS
Tuple Relational Calculus (TRC) in DBMS
Domain Relational Calculus in DBMS

Functional Dependencies

Functional Dependency and Attribute Closure
Armstrong's Axioms in Functional Dependency in DBMS
Equivalence of Functional Dependencies
Canonical Cover of Functional Dependencies in DBMS

Normalisation

Introduction of Database Normalization
Normal Forms in DBMS
First Normal Form (1NF)
Second Normal Form (2NF)
Boyce-Codd Normal Form (BCNF)
Introduction of 4th and 5th Normal Form in DBMS
The Problem of Redundancy in Database
Database Management System | Dependency Preserving Decomposition
Lossless Decomposition in DBMS
Lossless Join and Dependency Preserving Decomposition
Denormalization in Databases

Transactions and Concurrency Control

Concurrency Control in DBMS
ACID Properties in DBMS
Implementation of Locking in DBMS
Lock Based Concurrency Control Protocol in DBMS
Graph Based Concurrency Control Protocol in DBMS
Two Phase Locking Protocol
Multiple Granularity Locking in DBMS
Polygraph to check View Serializability in DBMS
Log based Recovery in DBMS
Timestamp based Concurrency Control
Dirty Read in SQL
Types of Schedules in DBMS
Conflict Serializability in DBMS
Condition of schedules to View-equivalent
Recoverability in DBMS
Precedence Graph for Testing Conflict Serializability in DBMS
Database Recovery Techniques in DBMS
Starvation in DBMS
Deadlock in DBMS
Types of Schedules based Recoverability in DBMS
Why recovery is needed in DBMS

Indexing, B and B+ trees

Indexing in Databases - Set 1
Introduction of B-Tree
Insert Operation in B-Tree
Delete Operation in B-Tree
Introduction of B+ Tree
Bitmap Indexing in DBMS
Inverted Index
Difference between Inverted Index and Forward Index
SQL Queries on Clustered and Non-Clustered Indexes

File organization

File Organization in DBMS - Set 1
File Organization in DBMS | Set 2
File Organization in DBMS | Set 3

DBMS Interview questions and Last minute notes

Last Minute Notes - DBMS
Commonly asked DBMS interview questions
Commonly asked DBMS interview questions | Set 2

DBMS GATE Previous Year Questions

Database Management System - GATE CSE Previous Year Questions
Database Management Systems | Set 2
Database Management Systems | Set 3
Database Management Systems | Set 4
Database Management Systems | Set 5
Database Management Systems | Set 6
Database Management Systems | Set 7
Database Management Systems | Set 8

The Entity Relational Model is a model for identifying entities to be represented in the database and representation of how those entities are related. The ER data model specifies enterprise schema that represents the overall logical structure of a database graphically.

The Entity Relationship Diagram explains the relationship among the entities present in the database. ER models are used to model real-world objects like a person, a car, or a company and the relation between these real-world objects. In short, the ER Diagram is the structural format of the database.

Why Use ER Diagrams In DBMS?

ER diagrams are used to represent the E-R model in a database, which makes them easy to convert into relations (tables).
ER diagrams provide the purpose of real-world modeling of objects which makes them intently useful.
ER diagrams require no technical knowledge and no hardware support.
These diagrams are very easy to understand and easy to create even for a naive user.
It gives a standard solution for visualizing the data logically.

Symbols Used in ER Model

ER Model is used to model the logical view of the system from a data perspective which consists of these symbols:

Rectangles: Rectangles represent Entities in the ER Model.
Ellipses: Ellipses represent Attributes in the ER Model.
Diamond: Diamonds represent Relationships among Entities.
Lines: Lines represent attributes to entities and entity sets with other relationship types.
Double Ellipse: Double Ellipses represent Multi-Valued Attributes .
Double Rectangle: Double Rectangle represents a Weak Entity.

Symbols used in ER Diagram

Components of ER Diagram

ER Model consists of Entities, Attributes, and Relationships among Entities in a Database System.

An Entity may be an object with a physical existence – a particular person, car, house, or employee – or it may be an object with a conceptual existence – a company, a job, or a university course.

Entity Set: An Entity is an object of Entity Type and a set of all entities is called an entity set. For Example, E1 is an entity having Entity Type Student and the set of all students is called Entity Set. In ER diagram, Entity Type is represented as:

1. Strong Entity

A Strong Entity is a type of entity that has a key Attribute. Strong Entity does not depend on other Entity in the Schema. It has a primary key, that helps in identifying it uniquely, and it is represented by a rectangle. These are called Strong Entity Types.

2. Weak Entity

An Entity type has a key attribute that uniquely identifies each entity in the entity set. But some entity type exists for which key attributes can’t be defined. These are called Weak Entity types .

For Example, A company may store the information of dependents (Parents, Children, Spouse) of an Employee. But the dependents can’t exist without the employee. So Dependent will be a Weak Entity Type and Employee will be Identifying Entity type for Dependent, which means it is Strong Entity Type .

A weak entity type is represented by a Double Rectangle. The participation of weak entity types is always total. The relationship between the weak entity type and its identifying strong entity type is called identifying relationship and it is represented by a double diamond.

Strong Entity and Weak Entity

Attributes are the properties that define the entity type. For example, Roll_No, Name, DOB, Age, Address, and Mobile_No are the attributes that define entity type Student. In ER diagram, the attribute is represented by an oval.

1. Key Attribute

The attribute which uniquely identifies each entity in the entity set is called the key attribute. For example, Roll_No will be unique for each student. In ER diagram, the key attribute is represented by an oval with underlying lines.

Key Attribute

2. Composite Attribute

An attribute composed of many other attributes is called a composite attribute. For example, the Address attribute of the student Entity type consists of Street, City, State, and Country. In ER diagram, the composite attribute is represented by an oval comprising of ovals.

Composite Attribute

3. Multivalued Attribute

An attribute consisting of more than one value for a given entity. For example, Phone_No (can be more than one for a given student). In ER diagram, a multivalued attribute is represented by a double oval.

Multivalued Attribute

4. Derived Attribute

An attribute that can be derived from other attributes of the entity type is known as a derived attribute. e.g.; Age (can be derived from DOB). In ER diagram, the derived attribute is represented by a dashed oval.

Derived Attribute

The Complete Entity Type Student with its Attributes can be represented as:

Entity and Attributes

Relationship Type and Relationship Set

A Relationship Type represents the association between entity types. For example, ‘Enrolled in’ is a relationship type that exists between entity type Student and Course. In ER diagram, the relationship type is represented by a diamond and connecting the entities with lines.

Entity-Relationship Set

A set of relationships of the same type is known as a relationship set. The following relationship set depicts S1 as enrolled in C2, S2 as enrolled in C1, and S3 as registered in C3.

Relationship Set

Degree of a Relationship Set

The number of different entity sets participating in a relationship set is called the degree of a relationship set.

1. Unary Relationship: When there is only ONE entity set participating in a relation, the relationship is called a unary relationship. For example, one person is married to only one person.

Unary Relationship

2. Binary Relationship: When there are TWO entities set participating in a relationship, the relationship is called a binary relationship. For example, a Student is enrolled in a Course.

Binary Relationship

3. Ternary Relationship: When there are n entities set participating in a relation, the relationship is called an n-ary relationship.

Cardinality

The number of times an entity of an entity set participates in a relationship set is known as cardinality . Cardinality can be of different types:

1. One-to-One: When each entity in each entity set can take part only once in the relationship, the cardinality is one-to-one. Let us assume that a male can marry one female and a female can marry one male. So the relationship will be one-to-one.

the total number of tables that can be used in this is 2.

one to one cardinality

Using Sets, it can be represented as:

Set Representation of One-to-One

2. One-to-Many: In one-to-many mapping as well where each entity can be related to more than one entity and the total number of tables that can be used in this is 2. Let us assume that one surgeon department can accommodate many doctors. So the Cardinality will be 1 to M. It means one department has many Doctors.

total number of tables that can used is 3.

one to many cardinality

Using sets, one-to-many cardinality can be represented as:

Set Representation of One-to-Many

3. Many-to-One: When entities in one entity set can take part only once in the relationship set and entities in other entity sets can take part more than once in the relationship set, cardinality is many to one. Let us assume that a student can take only one course but one course can be taken by many students. So the cardinality will be n to 1. It means that for one course there can be n students but for one student, there will be only one course.

The total number of tables that can be used in this is 3.

many to one cardinality

Using Sets, it can be represented as:

Set Representation of Many-to-One

In this case, each student is taking only 1 course but 1 course has been taken by many students.

4. Many-to-Many: When entities in all entity sets can take part more than once in the relationship cardinality is many to many. Let us assume that a student can take more than one course and one course can be taken by many students. So the relationship will be many to many.

the total number of tables that can be used in this is 3.

many to many cardinality

Many-to-Many Set Representation

In this example, student S1 is enrolled in C1 and C3 and Course C3 is enrolled by S1, S3, and S4. So it is many-to-many relationships.

Participation Constraint

Participation Constraint is applied to the entity participating in the relationship set.

1. Total Participation – Each entity in the entity set must participate in the relationship. If each student must enroll in a course, the participation of students will be total. Total participation is shown by a double line in the ER diagram.

2. Partial Participation – The entity in the entity set may or may NOT participate in the relationship. If some courses are not enrolled by any of the students, the participation in the course will be partial.

The diagram depicts the ‘Enrolled in’ relationship set with Student Entity set having total participation and Course Entity set having partial participation.

Total Participation and Partial Participation

Using Set, it can be represented as,

Set representation of Total Participation and Partial Participation

Every student in the Student Entity set participates in a relationship but there exists a course C4 that is not taking part in the relationship.

How to Draw ER Diagram?

The very first step is Identifying all the Entities, and place them in a Rectangle, and labeling them accordingly.
The next step is to identify the relationship between them and place them accordingly using the Diamond, and make sure that, Relationships are not connected to each other.
Attach attributes to the entities properly.
Remove redundant entities and relationships.
Add proper colors to highlight the data present in the database.

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Blog Data Visualization

What is an Entity Relationship Diagram and How to Draw one?

By Danesh Ramuthi , Nov 21, 2023

ER diagrams are not just mere illustrations but the backbone of the conceptual data model, a critical phase in database development that precedes the more granular logical and physical data models.

ER diagrams embody the essence of entity relationship modeling, serving to capture all the entities—ranging from a strong entity like an employee record to a weak entity that cannot exist without a strong one—and their interconnections, ensuring that every primary key and foreign key is meticulously mapped out to pave the way for a coherent, well-organized database.

They help identify relationships, whether one to one, one to many or many to many and illuminate the path to streamlining database structure by eliminating redundant entities and fostering efficient data storage.

With tools like Venngage Diagram Maker , creating an ER diagram is not just accessible but an engaging experience. Whether it’s about mapping out a new database or dissecting an existing database, Venngage’s collection of ER Diagram Templates allows database designers to craft diagrams that speak volumes about their data models.

Click to jump ahead:

What is an ER diagram?

History of er models, entity relationship diagram examples, erd symbols and notations, how to draw er diagrams, what is the use of er diagrams, final thoughts.

An Entity-Relationship (ER) diagram is a specialized diagram that illustrates the interrelationships between entities in a database. ER diagrams are designed to reflect the entity relationship model, a framework that dictates how data is connected and structured within a database.

Each entity contains key attributes, including a primary key that uniquely identifies each record within the entity set. Relationships, depicted by lines between these entities, showcase how data in one entity relates to data in another—be it through a primary and foreign key pairing in a one-to-many relationship or a many-to-many relationship necessitating a junction table. Additionally, attributes such as the derived attribute, which is based on another attribute within the database, can also be displayed within an ER diagram, enriching the data model with more nuanced details.

ER diagrams serve as a map for database designers to create, refine and implement database schemas for relational databases.

By depicting entities (like a student entity or a course entity), their relationships (like a student enrolled in multiple courses) and all the associated attributes (like phone numbers or faculty members), these diagrams help to identify relationships and ensure that the data stored in an actual database is organized efficiently.

Symbols and notations, like cardinality and modality, are used within ER diagrams to represent relationships clearly, providing an essential communication tool that supports the alignment of database structure with business processes.

The Entity-Relationship (ER) model was developed by Peter Chen in 1976 to provide a unified framework for data modeling. It became a foundational concept for relational database design, allowing for the representation of data structures and their relationships in a clear, abstract way, facilitating database design and other systems applications.

Entity Relationship Diagrams (ERDs) act as blueprints, detailing how entities relate to each other within the system. These diagrams help to ensure that all the necessary data is accounted for and that it is organized in a way that supports the database’s logical structure and business processes.

Let’s explore five different ER diagram examples that cater to various aspects of a business’s data needs, each illustrating the relationships and attributes of their entities with clarity and precision.

Product ER diagram examples

Product inventory er diagram.

In a product inventory ER diagram, the emphasis is on managing the data related to products, stock levels, suppliers and warehouses. The entities in this diagram would include ‘Items,’ ‘Inventory’ and ‘Order.’

A primary key would uniquely identify each product, while foreign keys would connect relationships between products and suppliers and inventory levels in warehouses. This ER diagram would be essential for database management systems in retail operations, showcasing a one-to-many relationship between suppliers and products or a many-to-many relationship if products are sourced from multiple suppliers.

Product point of sale ER diagram

The product point of sale (POS) ER diagram is focused on the transactional entities involved in the retail checkout process. This ER diagram would illustrate entities such as ‘Product,’ ‘Orders,’ ‘Payment Type’ and ‘Customer Type.’

Each ‘Product’ record could be connected to multiple ‘Product’ records, indicative of a many-to-many relationship, requiring a junction table to handle the multiple line items in a single transaction. POS ER diagram would also identify relationships between sales and payment methods, encapsulating the business process at the point of sale.

Vintage Product Point of Sale ER Diagram

In both examples, ER diagrams serve as the conceptual data model that guides the creation of a logical data model and eventually the physical data model. They help database designers in defining entities and relationship types, ensuring that all the data necessary for the operation of a business process, such as inventory management or sales transactions, is represented accurately within the relational database.

Human resource ER diagram

A Human resource (HR) ER diagram is created to manage and represent the relationships between various entities within a company’s HR database. This type of diagram would typically include entities such as ‘Employee,’ ‘Department,’ ‘Role’ and ‘Login.’

An ‘Employee’ entity, for instance, would have attributes like Employee ID (the primary key), name, contact information, address and other personal details. It could also include derived attributes such as ‘age’ or ‘years with company,’ calculated from the date of birth or hire date.

In this ERD, the ‘Employee’ entity would have a relationship with the ‘Department’ entity, showing which department the employee works in and potentially a one-to-many relationship indicating that one department can have many employees.

Similarly, relationships between ‘Employee’ and ‘Role’ would define what role an employee fill. An HR ER diagram supports HR departments in tracking employee data, optimizing the departmental structure and managing employee-related information effectively.

Banking system ER diagram

A Banking system ER diagram is more complex, given the nature of financial transactions and the range of services offered by financial institutions. In this ER diagram, one might see entities such as ‘Customer,’ ‘Bank Account,’ ‘Transaction’ and ‘Bank.’

The ‘Customer’ entity would hold information about the bank’s clients, with each record uniquely identified by a Customer ID. ‘Bank Account’ would detail various account types (checking, savings, etc.) and would include a foreign key to the ‘Customer’ entity to signify account ownership.

The ‘Transaction’ entity would document all customer transactions and might be linked to the ‘Account’ entity with a foreign key to reflect the account from which the transaction was made. This could involve a complex many-to-many relationship if customers can transfer funds between different accounts.

The ‘Bank’ entity would represent the banking institution itself. It has one attribute, ‘Name’, which would be the name of the bank. For both ‘Customer’ and ‘Employee,’ key attributes would be used to uniquely identify individuals within those entities.

Customer mobile payment ER diagram

An ER diagram illustrating a customer mobile payment system provides a conceptual model of how mobile payment data is organized within a database.

Such a diagram helps in understanding the logical structure of the database and the relationships between different entities involved in mobile payments.

The entities such as Customer, Mobile, Bill and Login are central to this model and their interconnections are critical for the representation of a robust and efficient mobile payment system.

May have attributes like CustomerID (as the primary key), Name and ContactDetails.
Could be related to the Mobile entity indicating ownership or usage of a mobile device.
Is linked to the Bill entity to represent payments made by the customer.
Might include attributes such as Mobile phoneID (primary key), Name and Price.
Connects to the Customer entity, suggesting that a customer uses or possesses the mobile device.
Could have attributes like Price and Bid.
Linked to the Customer entity, to represent the obligation of the customer to pay the bill.
Likely has attributes such as Username and Password (potentially as a derived attribute for security)

Blank ER diagram example

A blank ER diagram example serves as a template to be used in database design for a variety of applications. It usually contains the standard symbols and notation conventions used in entity-relationship modeling, such as rectangles for entities, diamonds for relationships and ovals for attributes.

The primary purpose of such a blank ER diagram is to allow a database designer to conceptualize the data model by defining all the entities relevant to a business process, their key attributes and the relationships among those entities.

The blank ER diagram can then be fleshed out into a logical data model and eventually a physical data model, which includes all the implementation-specific details such as data types and constraints.

The progression from a conceptual model, through a logical model, to a physical model is a critical process in database design, ensuring that the actual database system is well-organized, efficient and scalable.

https://venngage.com/templates/diagrams/blank-er-diagram-example-498eefb9-d6c8-4d8f-860b-e55a9d51aa24

Entity-Relationship Diagrams (ERDs) are a fundamental part of database design and modeling. They represent the logical structure of databases. Here are the primary symbols and notations used in ERDs:

Entities : Represented by rectangles, entities are objects or concepts about which data is stored. Each entity has a name which is typically a noun, such as “Customer” or “Order”.
Attributes : Represented by ovals, attributes are the data we collect about the entities. An attribute may be a primary key (underlined), which uniquely identifies each instance of the entity.
Relationships : Depicted by diamonds, relationships show how two entities share information in the database. The name of the relationship is often a verb, such as “buys” or “owns”.
Connecting lines : Solid lines are used to connect entities to attributes and entities to relationships, illustrating the linkage between them.
One-to-One (1:1) : A single instance of an entity is associated with a single instance of another entity.
One-to-Many (1:N) : A single instance of an entity is associated with many instances of another entity.
Many-to-One (N:1) : Many instances of an entity are associated with a single instance of another entity.
Many-to-Many (N:N) : Many instances of an entity are associated with many instances of another entity.
Weak entities : Sometimes represented by a double rectangle, a weak entity is an entity that cannot exist in the database without the existence of another entity (its owner).
Identifying relationships : Depicted by a double diamond, these represent the connection between a weak entity and its owner entity.
Derived attribute : Represented by a dashed oval, a derived attribute is one whose value is calculated from other attributes.
Composite attribute : If an attribute is made up of multiple components, it is shown as an oval with ovals inside it, indicating the composition.
Multi-valued attribute : Depicted by a double oval, a multi-valued attribute can have more than one value for a single entity (like multiple phone numbers for one person).
Participation constraints : Sometimes, there are constraints on how entities participate in relationships, which are depicted by placing either “partial” or “total” on the lines that connect entities to relationships.

Let’s explore the fundamentals of crafting an ER diagram, from identifying entities and defining relationships to incorporating attributes and leveraging advanced diagramming tools, ultimately underscoring the substantial benefits that these diagrams offer in the field of data modeling.

1. Identify all entities

When creating an ER diagram, the first step is to identify all entities within the system. An entity represents a real-world object or concept that holds data in a database. In an ER diagram, entities are typically depicted as rectangles, each labeled with a singular noun that best represents the object or concept it symbolizes. It’s crucial to ensure clarity and avoid duplication, making certain that each entity appears only once in the diagram. This practice aids in establishing a clear and organized representation of the data to be managed within the database.

2. Determine relationships

Understanding and defining how entities are connected is a fundamental aspect of modeling a system with an ER diagram. Relationships articulate the associations between entities, acting as verbs to describe interactions or connections. They are graphically represented by lines linking entities, often with a diamond-shaped symbol to detail the nature of the relationship. These connections can signify various types of associations, like ownership, membership or reference and are key to mapping out the logical structure of a database.

3. Add attributes to entities

Each entity in an ER diagram has attributes, which are specific pieces of information that the database stores. These are represented as ovals connected to their respective entities by a line and each attribute is named descriptively to ensure the information is clearly communicated. Attributes can range from simple, such as a name or date, to more complex data types like addresses or descriptive text. Properly defining attributes is crucial for detailing the structure and storage of data related to each entity.

4. Define primary and foreign keys

A primary key is a unique identifier for each entity instance, ensuring that each record can be uniquely distinguished from others. Conversely, foreign keys are attributes that create a link between two entities, establishing a relationship by referencing the primary key of a different entity. The correct implementation of primary and foreign keys is vital in an ER diagram as it forms the basis for relational database design, allowing for data integrity and efficient querying.

5. Use best practices

To maintain clarity and effectiveness in an ER diagram, it’s important to adhere to best practices. These include avoiding vague or redundant entities and relationships and never directly connecting relationships to each other—relationships should only exist between entities. Utilizing colors and standard shapes can also be beneficial to categorize and emphasize components of the diagram, making it more intuitive and accessible.

6. Consider weak entities and relationship types

Weak entities are those that do not have a sufficient set of attributes to form a primary key. They are often dependent on another entity (a strong entity) for identification. Moreover, it’s crucial to identify and represent the types of relationships—such as one-to-one, one-to-many or many-to-many—since they define how entities are related and the nature of their interactions. Accurate depiction of these elements is key for a comprehensive ER diagram.

7. Understand the benefits

The primary advantage of using ER diagrams lies in their ability to visually represent the logical structure of databases. They provide a clear methodology for translating conceptual models into physical databases, ensuring efficient database design and implementation. ER diagrams facilitate communication among stakeholders, provide a blueprint for database creation and help foresee potential design issues before they become problematic.

8. Leverage software tools

For the development of more intricate ER diagrams, employing specialized software tools like Venngage Diagram Maker is highly recommended. It offers a suite of pre-designed templates and symbols tailored for ER diagramming, which can greatly simplify and accelerate the creation process. It also often includes features that enable more dynamic and complex modeling, beneficial for representing intricate systems.

ER diagrams are widely used in database and systems design for various purposes:

ER diagrams are instrumental in modeling and designing relational databases, capturing both the logical framework of the database (logical data model) and the specifics of the technology to be implemented (physical data model)
They serve to visualize data and the interconnections among the entities within a system, clarifying the logical structure and the flow of information within the data model.
Essential for modeling the data stored in a database, ER diagrams specify the entities and their attributes and how these entities relate to one another. They form the foundational design upon which databases are built.
ERDs enable one to see how different entities, such as people, customers or objects, relate to each other within an application or a database, which is crucial when designing new systems for clear database structure.
Analyzing Data Requirements :

The ER model assists in the systematic analysis of data requirements to produce a well-designed database, representing real-world entities and the relationships between them.

Related: 10+ Types of Diagrams and How to Choose the Right One

From the historical context that has shaped their evolution to the diverse examples that demonstrate their versatility, ER diagrams are indispensable for conceptual, logical and physical data models.

Whether you are mapping out the structure for a banking system or delineating the complexities of human resource management, ER diagrams stand as faithful guides to translating business requirements into actual database structures.

Remember that an ER diagram is not just a diagram; it’s a conceptual gateway to efficient and effective database management. With the power of ER diagrams at your fingertips, facilitated by intuitive tools like Venngage Diagram Maker with its customizable templates , you can step confidently into the world of database design, ready to handle the complexities of relational databases and the nuances of data modeling with expertise and ease.

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ER Diagram Practice

Camille v. leonard.

The CS 5012 curriculum included learning to read and build Entity Relationship (ER) diagrams and schemas. The following were the assignment prompts and my submissions.

Create an ER diagram for the following database scenario. Make sure to include an indication of the cardinality of relationships and indicate any mandatory relationships (total participation). State any assumptions that you make!

Convert Task 1’s ER diagram to a DB Schema (table names and attributes with primary key).

Simple IMDB Database

Movie stars obviously have names (real and screen in some cases).
Movie stars star in movies.
Movies have titles, the year they came out, a genre, a length, and a rating.
A rating can be G, PG, PG-13, or R.
Movies are produced by studios.
There are various different studios around the world.
Movie studios hire actors to be in their movies and pay them a great deal of money (salary).

Convert Task 3’s ER diagram to a DB Schema (table names and attributes with primary key).

Hospital Database

Hospital staff consists of doctors and nurses.
All hospital staff have a hospital ID, name (first name, middle initial, and last name), and phone number.
Doctors have an office and up to three specializations.
Doctors have nurses that work with/assist them.
Nurses have one specialization and belong to a specific department in the hospital.
All nurses work with doctors (no exception). Many nurses can work with one doctor.
Doctors sometimes consult with a colleague (who is another doctor).
Doctors treat patients.
Patient information is collected by the hospital and includes SS# (social security number), name, insurance, date of admission, and date checked out.
A patient can undergo a number of tests.
Doctors perform tests.
Tests have a unique ID, name, a result, and a date and time the test was performed.

IMAGES

Er Diagram Template
Er Diagram Tutorial
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Entity Relationship Diagram Explained
Er Diagram Database Design
Er Diagram Assignment Solution

VIDEO

What is relationships, Relationships and Relationship sets in DBMS
entity relationship diagram
Entity Relationship Diagram for a simple blog
exercise 4 er diagram
Discriminator in a Weak Entity Set/ Partial Key of a Weak Entity Set explanation with example
Chapter 3: Data Modeling Using the Entity–Relationship (ER) Model [Part Two]

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A Guide to the Entity Relationship Diagram (ERD)

What is an Entity Relationship Diagram (ERD)?

Components of an ERD

Relationship

What is Cardinality?

Natural Language

Symbols and notations

Crow’s Foot

Conceptual, logical, physical

Conceptual Data Model

Logical Data Model

Physical Data Model

How to Create an Entity Relationship Diagram

Tools to Use

Tips for Creating an Entity Relationship Diagram

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What is an Entity Relationship Diagram (ERD)? | An Introduction to ER Diagram

What is an ER diagram?

History of ER Diagrams

ER Diagram Templates

Uses of ER Diagrams?

The Components and Features of ER Diagrams

Relationships

Cardinality

Entity Relationship Diagram (ERD) Symbols and Notations

Weak Entity

Multivalued Attribute

Derived Attribute

Relationship

Recursive Relationship

Cardinality and Ordinality

How to Draw ER Diagrams

Conceptual, Logical and Physical Data Models

Conceptual Data Model

Logical Data Model

Physical Data Model

Limitations of ER Diagrams

ER Diagram Best Practices

Benefits of ER diagrams

Drawing ER Diagrams Using Creately

FAQs about Entity Relationship Diagrams

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