Explore databases from file-based systems to modern DBMS, covering data modeling, functional dependencies, and normalization for data integrity.

Computer Science Bootcamp

A database is a structured collection of data stored in a computer system. Data modeling involves designing the structure of a database to ensure efficient data storage, retrieval, and manipulation. Learning data modeling and design is essential as it enables the effective creation of database systems. This module introduces us to databases to gain a competitive edge in the tech industry. We’ll start by exploring the evolution of databases, from file-based systems to the modern era of database management systems (DBMS). Then, we’ll dive deep into fundamental concepts such as data modeling, entity-relationship models, and the relational data model. Next, we’ll learn about functional dependencies, normalization techniques, and their benefits in ensuring data integrity. By the end of this module, we’ll have a solid understanding of databases and their management, empowering us to excel in our careers as a developer and leverage this knowledge to contribute to innovative projects in the industry.

Data Modeling and Design

# Relational database schemas

A relational database schema **S** is a set of relation schemas S = {R$_1$, R$_2$, … , R$_m$} and a set of integrity constraints **IC**. A relational database state **DB** of S is a set of relation states DB = {r$_1$, r$_2$, … , r$_m$} such that each r$_i$ is a state of R$_i$. 
The figure below shows a relational database schema that we call COMPANY = {EMPLOYEE, DEPARTMENT, DEPT_LOCATIONS, PROJECT, DEPENDENT}. In each relation schema, the underlined attribute represents the primary key.



In this lesson, we will discuss the basic concepts behind relational database schemas.

Introduction

Fundamental Concepts

Data Modeling

Entity-Relationship Data Model

The Relational Data Model

Functional Dependencies

Normalization

Conclusion

Relational Database Schemas

Relational database schemas