SQL for Data Analysis

What you'll learn

• Data Extraction & Filtering: Write efficient SELECT queries using conditional filters (WHERE, HAVING), logical operators, and sorting constraints (ORDER BY, LIMIT).
• Table Joins & Relationships: Combine disparate datasets across multiple tables using INNER JOIN, LEFT/RIGHT JOIN, and full outer joins to perform cross-table analysis.
• Aggregations & Grouping: Summarize metrics efficiently using aggregate functions (COUNT, SUM, AVG, MIN, MAX) paired with GROUP BY clauses.
• Advanced Analytics with Window Functions: Perform complex evaluations—such as running totals, moving averages, and period-over-period growth—using window functions (ROW_NUMBER, RANK, LAG, LEAD).
• Query Modularity & Cleaning: Clean raw data, handle null values, and structure complex, multi-step queries using Subqueries and Common Table Expressions (CTEs).