Data Wrangling with SQL is a hands-on textbook designed to help students develop the practical skills needed to prepare real-world data for analysis. Because most data arrives incomplete, inconsistent, or poorly structured, data wrangling is often the most time-consuming and critical phase of the analytics process.
Using clear explanations, business-focused examples, and guided exercises, students learn how to assess data quality, clean messy datasets, handle missing values, remove duplicates, normalize formats, merge data from multiple sources, create calculated fields, and reshape data for reporting and analysis. The text introduces essential SQL concepts in the context of solving practical data preparation challenges rather than memorizing syntax.
The book also explores modern AI-assisted approaches to data cleaning, validation, and SQL query development, helping students understand how artificial intelligence can support data professionals while maintaining data quality and accuracy.
Features include:
• Seven chapters covering the complete data wrangling workflow
• Step-by-step demonstrations and guided labs
• Practice exercises and review questions
• Real-world business and analytics scenarios
• Coverage of joins, filtering, transformations, aggregation, and reshaping
• AI-assisted data preparation techniques
• Companion resources for students and instructors
Ideal for introductory data analytics, business analytics, database, data science, and information systems courses.
