Chapter 1: Introduction to Databases and SQL In today’s data-driven world, information powers decisions at every level—from personal finance trackers to enterprise analytics platforms. Databases serve as the backbone for storing, organizing, and retrieving this information efficiently. In this chapter, we’ll explore why data lives in tables, familiarize you with core terminology, trace the origins of relational databases, and explain how SQL emerged as the universal language for data manipulation. What Is Data and Why We Store It in Tables Data represents facts, figures, and measurements collected from real-world activities. Without structure, raw data is difficult to query, analyze, or validate. Storing data in tables offers several advantages: Logical organization: Tables group related information into rows (records) and columns (attributes), making it easy to locate and interpret individual pieces of data. Consistency: Structured tables enforce uniform data types and formats, ...
Welcome to Part I of our beginner-friendly SQL tutorial series on Data Analyst BI. In this first module, you’ll learn the fundamentals of relational databases and get your environment ready for hands-on SQL practice. Whether you aim to become a Data Analyst, BI Developer, or just want to query data like a pro, mastering these SQL basics will set you on the path to success. Introduction to Databases and SQL Structured Query Language (SQL) is the universal standard for interacting with relational databases. Before writing your first query, it’s essential to understand: What is a Database? A database stores information in tables made up of rows (records) and columns (fields). Common examples include customer lists, sales transactions, or inventory logs. Why Relational Databases? Relational databases enforce data integrity through primary keys, foreign keys, and constraints. This structure makes it easy to join related tables and maintain consistent, accurate data. The Role of SQL SQ...