SQL for Advanced Data Analysis

Write complex queries with multiple JOINs, subqueries, and Common Table Expressions (CTEs).

Apply window functions (e.g., RANK, LAG, LEAD) to perform sophisticated analysis within data partitions.

Compute running totals and moving averages using window frames.

Use CASE statements and conditional aggregation to create custom reports and pivot data.

Solve realistic business problems like user retention and churn analysis using SQL.

Analyze a relational dataset to produce a short report of actionable insights.

Structure and document SQL queries for clarity and maintainability.

Publish the SQL analysis project and its findings to a GitHub portfolio.