Databases Course Book – SQL Fundamentals

Overview

This concise, example-driven course book focuses on practical relational database concepts and essential SQL skills, with an emphasis on workflows you can apply immediately in workplace settings. Lessons move quickly from core querying to patterns for reporting, schema design, and safe data modification. Each chapter is task-oriented: run queries, inspect results, refine logic with joins and aggregations, and shape outputs into stakeholder-ready reports. The style is hands-on and pragmatic, designed to help learners build reproducible habits for analysis, development, and operational tasks.

What you will learn

• Core SQL commands for querying and modifying data (SELECT, INSERT, UPDATE, DELETE) along with idiomatic practices for predictable behavior and performance.
• Aggregation and grouping techniques (SUM, AVG, COUNT, MIN, MAX) and how to use GROUP BY and HAVING for cohort and summary analysis.
• Relational techniques including INNER, LEFT, and RIGHT joins, and guidance on when to prefer joins, subqueries, or set-based operations for clarity and efficiency.
• Practical schema design and normalization strategies that reduce redundancy, enforce integrity via keys and constraints, and support maintainable applications.
• Transaction fundamentals (atomicity, isolation, rollback) and patterns for safe concurrent updates, savepoints, and error recovery.
• Report-focused methods: calculated fields, result formatting, and exporting from GUI clients to produce repeatable deliverables for dashboards and stakeholders.

Instructional approach

The book adopts a progressive, task-first pedagogy suitable for self-study, workshops, or classroom use. Early chapters get you comfortable in a MySQL environment and common GUI clients so you can run real queries immediately. Explanations are concise and paired with worked examples and hands-on exercises that reflect everyday data tasks.

Design-oriented sections use realistic scenarios to demonstrate entity relationships and normalization, emphasizing trade-offs when choosing keys, constraints, and indexing strategies. Advanced topics present nested queries, integrity enforcement strategies, and SQL features that simplify analysis and reporting. Transaction examples tie ACID concepts back to concrete operations, showing how to implement safe updates, use savepoints, and handle rollback conditions when multiple users interact with the same data.

Practical applications

Examples mirror typical workplace problems — student and employee records, inventory and sales analytics, performance metrics aggregation, and ad hoc investigations. The material emphasizes extracting actionable insights using grouping, joins, and window-like patterns, ensuring correctness through solid schema choices and transaction controls, and preparing query outputs for visualization or printable reports. The aim is to make database tasks repeatable, auditable, and production-ready.

How to use this course effectively

• Work through lessons sequentially to build a solid foundation; revisit advanced examples as your needs evolve.
• Practice in a live MySQL instance or GUI client such as MySQL Workbench or HeidiSQL to reinforce syntax and tool workflows.
• For schema-design chapters, sketch entity-relationship diagrams and populate sample data to observe constraint and index behavior.
• Adapt reporting templates to your datasets — use calculated columns and exporting steps to create reproducible reports for stakeholders.

Exercises and project ideas

Each topic includes progressive exercises so you can apply techniques immediately. Suggested projects include building a student-performance dashboard that computes averages and distributions, creating a sales and inventory analytics model to track regional and product KPIs, and producing printable reports with formatted summaries and calculated fields. These projects reinforce integration across querying, schema design, transactions, and reporting workflows.

Quick FAQ

When should I use WHERE vs HAVING? Use WHERE to filter rows before aggregation; use HAVING to filter groups after aggregation.

Can I group by multiple fields? Yes — GROUP BY multiple columns aggregates results for each unique combination of those fields.

Core terms to know

• SQL — Structured Query Language for querying and modifying relational data.
• Aggregation — Functions (SUM, AVG, COUNT) that summarize multiple rows into single values.
• Normalization — Organizing tables to minimize redundancy and maintain integrity.
• Transaction — A set of operations executed atomically to preserve consistency (ACID concepts).
• Join — Combining rows from multiple tables based on related columns.

Who should read this

Ideal for beginners building a practical SQL foundation and for analysts, developers, or DBAs who need a concise refresher on aggregation, transactions, and reporting workflows. The example-led format supports guided self-study, classroom instruction, and rapid workplace upskilling. According to the author Paolo Coletti, the hands-on orientation is intended to bridge theoretical concepts and daily data tasks so learners can apply skills immediately.