SQL for Data Quality: Find Duplicates, NULLs, and Errors in DuckDB

Dirty data leads to flawed analysis, broken pipelines, and incorrect business decisions. Learning how to quickly audit and profile your datasets is an essential skill for any modern data professional. This course teaches you how to write efficient SQL queries to detect common data quality issues like duplicate records, missing NULL values, invalid formats, and orphaned relationships. Using DuckDB, a fast and modern analytical engine, you will learn to run these checks directly on local files without any complex database administration. What you'll learn: - Understand foundational data quality concepts, schemas, and common types of data anomalies - Identify and resolve duplicate rows using SQL aggregation and window functions - Detect missing information and write queries to handle NULL values safely - Validate data relationships and find broken references between tables - Leverage DuckDB to query CSV and Parquet files instantly without setting up a traditional database - Apply systematic data profiling techniques to assess the health of any new dataset You will start by mastering core data quality definitions before moving on to step-by-step written guides and SQL query patterns. By analyzing practical scenarios through written explanations, you will build a reusable toolkit of validation queries to audit any dataset with confidence. This text-based course is designed for beginner data analysts, database novices, and developers who want to improve their data cleaning skills. No advanced SQL knowledge or database setup experience is required. Start reading today to master the art of finding and fixing data errors with modern SQL.