A collection of SQL projects demonstrating query fundamentals through advanced techniques data cleaning, aggregation, business intelligence reporting, and performance optimization. Each project lives in its own folder with a full writeup, the SQL code, and the business insights drawn from the results.
| # | Project | Tool | Focus |
|---|---|---|---|
| 1 | SQL Data Analysis | SSMS | Cleaning and querying 1,200 retail transactions revenue, cancellations, marketing performance |
| 2 | Sales Data SQL Querying & Optimization | MySQL Workbench | Advanced querying (self-joins, subqueries, window functions) plus indexing/optimization on 2,755 sales records |
| 3 | Chinook Music Store SQL Analysis | MySQL Workbench | Relational joins, subqueries, and window functions across an 11-table music store database |
Fundamentals
- Filtering and sorting (
WHERE,ORDER BY) - Aggregation (
GROUP BY,HAVING,COUNT,SUM,AVG) - Conditional logic (
CASE WHEN) - Data cleaning directly in SQL (
UPDATE,ROUND)
Advanced querying
- Multi-table joins (
INNER JOIN,LEFT JOIN) across relational schemas - Self-joins (comparing rows against aggregated summaries of the same table)
- Subqueries
- Window functions (
RANK,ROW_NUMBER,PARTITION BY)
Performance & rigor
- Query optimization and indexing (
EXPLAIN,CREATE INDEX) - Data validation catching flawed comparisons (e.g. partial-year data skewing trends, or sample-data artifacts) before drawing conclusions
Communication
- Translating raw query results into clear business questions, findings, and recommendations