Fundamentals of Relational Databases: Tables, Data Modeling, SQL, and Normalization

There is a saying that if the foundation is not solid, the ground shakes; therefore this article first clarifies basic relational database concepts to lay a solid foundation for later learning.

The topics covered include:

Database and tables

Data models and ER diagrams

SQL language

Database normalization

Database and tables

A database is an organized, shareable collection of data stored on computer storage devices, typically composed of one or more tables, each containing rows and columns for specific data types.

Tables are structured forms that organize data in rows and columns.

Data model and ER diagram

A data model abstracts real‑world features into a conceptual representation; before designing a database, a suitable data model must be built.

The most common method is the Entity‑Relationship (ER) diagram, which uses rectangles for entities, ovals for attributes, and diamonds for relationships.

Example: a simple order ER diagram shows a one‑to‑many relationship between customers and orders.

SQL language

SQL (Structured Query Language) is the standard language for querying and managing relational databases. It is divided into four categories: DDL, DML, DQL, and DCL.

SQL is considered the core and soul of database programming, with many practical techniques to explore in future articles.

Database normalization

Normalization defines a series of rules (normal forms) to design reasonable databases. The first three normal forms are:

1NF – each column holds atomic, indivisible values.

2NF – a table must have a primary key, and non‑key columns must depend on the whole key.

3NF – eliminates transitive dependencies among non‑key columns.

Examples using an order table illustrate violations of each normal form and how to correct them.

Conclusion

The article reviewed essential database fundamentals—tables, ER diagrams, SQL categories, and normalization—highlighting their importance as a prerequisite for advanced topics, while also noting that denormalization may be appropriate in certain NoSQL scenarios.

Acknowledgments and references are provided at the end of the original article.