Data Alchemist Transforming Raw Data into Strategic Insights
| Category | Skills & Technologies |
|---|---|
| Database | SQL Server, MySQL, PostgreSQL |
| Optimization | Query tuning, indexing, partitioning |
| Advanced SQL | Window functions, recursive CTEs, JSON/XML |
| ETL | SSIS, Airflow, Stored Procedures |
- Utilized window functions (RANK(), DENSE_RANK()) to identify top-performing products by category
- Implemented CTEs for multi-step analysis of pricing trends and discount strategies
- Created complex joins to correlate product ratings with sales performance
- Developed aggregate functions with GROUP BY ROLLUP for hierarchical sales reporting
- Designed date functions to analyze seasonal purchasing patterns
- Built PIVOT tables to transform row-based data into business-friendly formats
- Applied CASE statements for customer segmentation by purchase behavior
- Optimized queries with proper indexing to handle large transaction datasets
- Created time series analysis with LAG()/LEAD() functions to predict demand patterns
- Implemented stored procedures for automated report generation
- Used recursive CTEs to analyze hierarchical regional power distribution
- Developed error handling with TRY/CATCH blocks for data validation
- Performed data standardization with UPDATE statements and string functions
- Applied advanced NULL handling techniques (COALESCE, ISNULL)
- Designed self-joins to identify duplicate property records
- Created temporal tables to track data changes during cleaning process
- Implemented financial calculations (moving averages, YoY growth)
- Built dynamic SQL for flexible report parameterization
- Used window frames for precise rolling calculations
- Created volatility indicators with statistical functions
- Developed route optimization algorithms using spatial data functions
- Implemented inventory turnover calculations with date arithmetic
- Designed multi-table joins to connect suppliers, warehouses, and retailers
- Created performance dashboards with summary CTEs
- Built patient cohort analysis with PARTITION BY clauses
- Implemented HIPAA-compliant data masking with VIEWs
- Developed readmission risk models using conditional aggregation
- Created recursive queries to analyze treatment pathways
In these projects, I've focused on writing maintainable, performant SQL that tells a story with data. I particularly enjoy:
- Transforming messy real-world data into clean analytical datasets
- Balancing complex business logic with query efficiency
- Documenting my thought process through comprehensive code comments
- Creating reusable SQL components (views, functions, procedures)
Each project reflects my approach to problem-solving with SQL - starting with thorough data exploration, then building iterative solutions that deliver actionable business insights.
� Clean Code: Documented, modular SQL with CTEs
🚀 Performance First: Execution plans analyzed for every major query
📖 Storytelling: SQL that explains the "why" behind the numbers