SQL Data Transformation for ETL: Filtering, Sorting, and Binning

In data engineering and analysis, raw data is rarely ready for immediate use. To extract meaningful insights or feed downstream systems, you must know how to shape, clean, and structure data efficiently at the database level. This course guides you through the essential SQL techniques required to transform raw tables into structured, analysis-ready datasets. You will transition from writing basic queries to crafting sophisticated data transformation steps, mastering the core operations that power ETL (Extract, Transform, Load) pipelines. What you'll learn: - Understand foundational database structures, data types, and the logical order of SQL execution - Filter complex datasets using advanced conditional logic and pattern matching - Sort and organize query results efficiently while managing null values - Aggregate data using group functions and summarize metrics across different dimensions - Bin continuous data into discrete categories using conditional CASE expressions - Apply modern SQL best practices, including Common Table Expressions (CTEs) for readable and modular query design Starting with fundamental database concepts and key terminology, this text-only course guides you step-by-step through practical query-writing scenarios. You will read clear explanations, analyze structured code examples, and learn to optimize your data preparation workflows. This course is designed for beginners, aspiring data analysts, and junior data engineers. No prior SQL experience is required, as we start with the absolute basics. Start reading today to build a strong foundation in SQL data transformation and elevate your data preparation skills.