Turning Messy Data Into Systems That Work
Every system I build starts with one question: what would make this process smoother for the people who use it every day? From there, I work backward—identifying bottlenecks, tracing issues to their source, and designing sustainable solutions that prevent problems rather than just detect them.
How I Think
I approach problems by first understanding the data landscape, identifying gaps, and letting the numbers guide the solution.
I build validation processes that catch issues before they become problems, not after they've caused damage.
I always start with the end in mind, designing solutions that work today and grow with your business tomorrow.
How I Create
These are the systems I build most often. Each one starts with a specific pain point and ends with something that runs reliably—less manual work, fewer errors, and tools that actually get used.
Validation frameworks that ensure data accuracy and consistency across your operations
What's inside:
- Data validation rules
- Reconciliation workflows
- Error detection & alerting
- Quality dashboards
Technical Stack:
| Database | PostgreSQL, SQL Server |
| Validation | Custom SQL scripts & triggers |
| Monitoring | Automated quality checks |
| Reporting | Real-time dashboards |
Automated workflows that eliminate manual tasks and reduce human error
What's inside:
- Data pipeline automation
- Compliance monitoring
- Report generation
- Integration workflows
Technical Stack:
| Automation | n8n, Zapier, Make |
| Scheduling | Cron jobs & triggers |
| Integration | REST APIs & webhooks |
| Logging | Complete audit trails |
Clear insights from complex data to drive informed business decisions
What's inside:
- Performance metrics
- Trend analysis
- Compliance reporting
- Executive dashboards
Technical Stack:
| Analysis | SQL, Python, Excel |
| Visualization | Custom dashboards |
| Delivery | Automated reports |
| Format | Interactive & static |
My Skills
Ready to turn your data challenges into working systems?