Course Overview

Relational Database Design and Modeling for Software Engineers

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Introduction

Course Overview

Before the Advent of Database

Fundamental Concepts

What is a Database?

Database management systems (DBMS)

Overview of Relational Databases

Relational Vs. Non-Relational Databases

Data Modeling

Introduction to Data Modeling

Levels of Data Modeling

Data Modeling Process

Best Practices in Data Modeling

Quiz

Entity-Relationship (ER) Data Modeling

Introduction to ER Models

Entities, Attributes, and Relationships

Cardinality and Participation

Attributes of Relationship Types

Weak Entity Types

Creating an ER Diagram for Employee Management System

Quiz

The Relational Data Model

Introduction to the Relational Model

Relations, Tuples, and Attributes

Keys in Relational Databases

Relational Integrity Constraints

Converting ER Diagrams to Relational Model

Best Practices for ER Diagrams to Relational Models

Quiz

Functional Dependency

Introduction to Functional Dependency

Types of Functional Dependencies

Inference Rules for Functional Dependencies

Closure of Attribute Sets

Quiz

Normalization

Introduction to Normalization

First Normal Form (1NF)

Second Normal Form (2NF)

Third Normal Form (3NF)

Boyce-Codd Normal Form (BCNF)

Higher Normal Forms (4NF, 5NF)

Exercise 1

Solution to Exercise 1

Exercise 2

Solution to Exercise 2

Case Studies

Designing a Hospital Management System

Designing a Hotel Management System

Designing a Bank Management System

Designing an Instagram

Designing an E-commerce Platform

Designing an Online Food Delivery System

Relational Vs. Non-Relational Databases

Relational Databases (RDBMS)

Relational databases organize data into structured tables with rows and columns. Each table represents an entity, and tables can be linked through relationships defined by primary and foreign keys. Relational databases use Structured Query Language (SQL) for defining, querying, and managing data.

Key Features:

Predefined schema
ACID compliance (ensures data reliability)
Strong data integrity and consistency

Examples: MySQL, PostgreSQL, Oracle Database, Microsoft SQL Server.

Non-Relational Databases (NoSQL)

Non-relational databases store data in a flexible format that can handle structured, semi-structured, or unstructured data. They are designed for scalability and performance in handling large volumes of data and can use formats such as documents, key-value pairs, graphs, or wide columns.

Key Features:

Flexible schema
High scalability
Optimized for large-scale data and fast read/write operations

Examples: MongoDB, Cassandra, Redis, Neo4j.

Relational vs. Non-Relational Databases

Feature	Relational Databases (RDBMS)	Non-Relational Databases (NoSQL)
Schema	Fixed, predefined schema	Flexible schema
Data Model	Tables with rows and columns	Various (document, key-value, graph, columnar)
Query Language	SQL	No fixed query language (varies by type)
Scalability	Vertical (adding more power to one server)	Horizontal (adding more servers)
ACID Compliance	Strong ACID compliance	Typically supports BASE properties
Data Integrity	High data integrity with strict relationships	Data integrity varies, often application-managed
Best Use Cases	Financial systems, CRM, ERP	Real-time analytics, content management, IoT

Overview of Relational Databases

Introduction to Data Modeling

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On this page

Relational Databases (RDBMS)

Non-Relational Databases (NoSQL)

Relational vs. Non-Relational Databases