What Is an Entity-Relationship Diagram? A Complete Guide

When designing a relational database, engineers create an entity-relationship diagram to represent how different pieces of data are related. These diagrams provide a clear visualization of data relationships, making it easier to understand the overall structure. 

ERD allows stakeholders to verify if an information system design aligns with business requirements before it gets into development. It also allows developers to create relational databases that complement data storage needs. 

The entities can be people, objects, or causes. They’re represented on an ERD using different shapes, such as ovals, rectangles, or diamonds, and connecting lines that illustrate different relationships and their key attributes. 

Engineers and database architects often combine ERD with data structure diagrams (DSD). While ERDs focus on the relationships between entities, DSDs highlight the relationships between different elements of entities, helping to describe the informational flow. 

The need for using ERDs in DBMS

Imagine you're building a complex e-commerce platform where customers can browse products, add them to a cart, and make purchases.

Behind the scenes, a well-structured database table ensures all data—from customer details to product inventory—is organized and easily accessible. ERD visualizes the relationships between different data entities, making database design smoother and more efficient.

• Clarify data relationships: An entity-relationship model depicts how different data entities are related, helping teams understand the complex interactions between tables and reducing errors in database design.
• Ensure data integrity: ERDs help maintain data consistency and prevent issues like orphaned records or redundant data by representing constraints, such as primary and foreign keys.
• Facilitate communication: ERDs provide a visual representation of the database, making it easier to communicate the database structure to non-technical stakeholders like business analysts or product managers.
• Enhance scalability and maintenance: With ERDs, developers can foresee potential database issues as the system scales, ensuring that relationships and data flow remain clear even as new features or entities are added.

Components of an entity-relationship diagram 

Entities, relationships, attributes, and cardinality are the major components of an ERD data flow diagram.

Entity 

An entity is anything that can have data stored about it. Simply put, it’s that which you can define – for example, an object, a person, or a concept. It’s a noun represented in a rectangular shape.

┌────────────┐  
│  Entity                                            │  
└────────────┘  

An entity type is a group of definable things. Similarly, an entity set is the same as an entity type but defined at a particular time. For example, “customers” is an entity type, and “customers who signed in yesterday” is an entity set. 

Entities can be categorized into three main types: 

• Strong entity: Can be defined using its attributes.
• Weak entity: Can’t be defined using its attributes.
• Associative entity: They associate entities within an entity set. 

When an attribute uniquely defines an entity within an entity set, it’s called an entity key. They are of three types. If one or more attributes define an entity in an entity set, it’s a super key. When a database designer uniquely chooses a key to represent an entity within a set, it’s the primary key. Lastly, foreign keys identify relationships between different entities. 

Relationships

Relationships are verbs that represent how entities are linked. For example, in the sentence “Sarah will pay through her phone,” the entities “Sarah” and “Phone,” are connected by the act of paying. 

   ________
  /                  \
/                      \
|     REL            |
 \                     /
  \_______/

In an ERD, relationships are often represented as diamonds or labels on connecting lines. Sometimes, you might come across a recursive relationship where the same entity participates in a relationship more than once. 

Attribute 

Attributes are often represented in an oval or a circle. They can be quality, property, or characteristic of an entity. When an attribute describes the property or characteristics of a relationship, it’s known as a descriptive attribute. 

   ________
 /                    \
|   Attribute  |
 \________/

There are different categories of attributes: 

• Simple: Their value can’t be divided further – for example, a credit card number.
• Derived: The value of these attributes is derived from different attributes, like age derived from a birth date.
• Composite: These are sub-attributes of an attribute. For example, a student’s address includes a house number.
• Single-value: They have only one value, such as age.
• Multi-value: These attributes can have multiple values, like a person having two mobile phone numbers. 

Cardinality 

Cardinality describes the number of relationships or instances between entities. It’s usually expressed as a ratio in symbols called crow's foot, which can be one-to-one or one-to-many. 

A one-to-one relationship exists between a teacher and their mailing address. Similarly, you’ll see a one-to-many relationship between students and their subjects, which can also be viewed as a many-to-one relationship, as subjects have a single line back to the student. 

Lastly, many-to-many relationships can be students learning from multiple teachers. The group of teachers is, in turn, associated with many students.

Representing ER components as parts of speech 

You can use parts of speech to represent ER components, for example: 

• A proper noun like Sarah would be an entity.
• A common noun will be an entity type, like teachers.
• A verb equals relationship type.
• Adjectives are an entity’s attributes.
• Adverbs are descriptive attributes that convey the properties of a relationship. 

How to create a simple entity-relationship diagram 

Before we dive deeper into creating an entity-relationship diagram, it’s crucial to understand how they’re depicted. 

An ERD can be depicted using three types of data models: 

• Conceptual data model: Lacks specific details but gives an overview of the database project’s scope while describing how datasets are related.
• Logical data model: Describes particular attributes and relationships among data points. It’s more detailed than a conceptual data model and serves as the basis for a physical data model.
• Physical data model: Offers a blueprint of the relational database. 

With this understanding, let’s go through the steps to help you create a relational data model.

1. Decide on the purpose and scope of the information system project you’re working on. Understand what you’re modeling. 
2. Find the entities involved and draw them using rounded rectangles with appropriate labels. 
3. Determine how entities are interconnected and draw lines to depict those relationships. These relationships would be labeled using the diamond shape. 
4. Add details by incorporating entity attributes using the oval shape. 
5. Present the relationships as one-to-one, one-to-many, or many-to-many as required. 

Here’s an example of an ERD to use as a reference. 

Source: Research Gate

Entity relationship diagram use cases 

Below are some notable use cases of entity-relationship diagrams. 

Designing relational databases 

ERDs help model a database with logic and relevant business rules. These diagrams help project stakeholders understand the requirements for an information system and later help the team transform the design into a database. 

For instance, imagine an airline wanting to model its booking system. The entities might include Flight, Passenger, and Ticket, and the relationships could describe how passengers book flight tickets. An ERD helps the development team understand how to structure these relationships before building the actual database.

Troubleshooting issues in a database 

Entity-relationship diagrams help engineers analyze an existing database and understand the relationships between entities and their attributes. When issues arise, these diagrams help engineers locate the root cause, facilitating quick resolution.

For example, if an e-commerce website is having issues with inventory management, an ERD helps engineers trace relationships between Products, Orders, and Suppliers to identify where the data flow is breaking down. Developers can quickly isolate and resolve the problem by pinpointing the entities and relationships.

These two are the primary use cases of the ERD. Additionally, ERD can be used to design business information systems or in business process re-engineering (BPR), where ERDs streamline the process of modeling or re-engineering an existing business information system. 

Overall, ERDs are crucial for engineers when designing relational databases.

Challenges of entity-relationship diagram 

It's important to keep the following challenges in mind when working with an entity-relationship diagram.

• Although entity-relationship diagrams are invaluable when designing a database or troubleshooting errors, they’re tricky to use when working with unstructured or semi-structured data. Unless the data is organized into different fields, rows, and columns, ERDs won’t prove helpful.
• Entity-relationship diagrams work only for relational data where they showcase the relational structure.
• On the other hand, using ER models can be challenging if you plan to integrate them with an existing database, especially if the database has a different architecture. In such cases, it would be difficult to represent entity relationships properly. 

Best practices for creating ERDs

When working with ERDs, it’s best to align with these practices to avoid rework or unnecessary back and forth with the team. 

• Align on the data model you want to draw. Decide on what’s necessary for your purpose. You can go with anyone among conceptual, logical, or physical data models.
• Be consistent with the notation you use to represent entities, their relationships, attributes, and cardinality.
• Involve stakeholders while modeling the database, helping you keep everyone aligned with business requirements.
• Watch out for inconsistencies, such as missing entities, relationship information, or attributes when troubleshooting a relational database issue.
• Ensure the labeling of entities and relationships, but don’t overcomplicate them with unnecessary details.
• Let the ERD support and update your data storage requirements as the system evolves. 

Increasing efficiency through planning 

ERDs offer a clear way to visualize data. They make it easy to show what the database system would be like in terms of its architecture and get feedback from the team. This helps avoid any blunders that might come up later due to stakeholder misalignment or scope creep.

Moreover, visually planning the database structure helps remove bottlenecks that might emerge during development. It allows the development team to work more efficiently when no consistent firefighting is involved. 

Ready to model your data and design databases? Check out different data modeling techniques that will help design reliable systems.