Applied SQL for Data Analytics and Data Science in BigQuery

Data is only as valuable as the insights you can extract from it, and SQL is the foundational language for unlocking that value. If you want to work in data analytics or data science, mastering SQL within a modern cloud data warehouse like BigQuery is an essential industry standard. This text-based course guides you from foundational query concepts to advanced analytical techniques. You will learn to think like a data analyst, translating complex business questions into clean, efficient SQL queries, and utilizing modern cloud-based data features. What you'll learn: Learn the core syntax of SQL, starting with basic filtering, sorting, and aggregations; Understand how to join multiple datasets and structure complex queries using Common Table Expressions (CTEs); Apply advanced window functions to calculate running totals, rankings, and moving averages; Query and manipulate modern semi-structured data formats like JSON directly within BigQuery; Practice optimizing query performance and managing costs using partitioning and clustering; Analyze real-world datasets to extract actionable business insights and support data science workflows. You will start with key terminology, database structures, and basic SELECT statements before advancing to complex joins, analytical functions, and modern BigQuery optimization techniques. Each concept is explained through clear, written breakdowns and practical query examples you can read and analyze. This course is designed for beginners who are new to database querying, as well as aspiring data analysts and data scientists looking to build practical SQL skills. No prior programming or database experience is required. Start reading today to build a strong foundation in modern SQL and take control of your data analysis career.