Business Problem
Business teams often rely on spreadsheet reporting that is slow to refresh and difficult to trust.
Analytics Workflow
- Data modeling
- SQL validation
- dashboard design
- stakeholder review
- publishing
Methodology
Modeled business tables, defined KPIs, built dashboard pages, and documented metric logic.
Key Findings
Margin and revenue trends varied by product category, and inventory risk was concentrated in a small number of items.
Business Impact
Improves visibility into revenue, margin, and operational performance while reducing manual reporting.
Technical Highlights
Star schema, SQL checks, DAX/calculated metrics, dashboard UX, drilldowns.
What This Project Demonstrates
SQL, Python, data cleaning, dashboard design, machine learning or NLP where applicable, data engineering where applicable, business communication, and problem solving.
Interview Talking Points
How did you define the KPIs? How did you check dashboard accuracy?
Lessons Learned
A dashboard is only useful when metric definitions are trusted.
Future Improvements
Add live dashboard screenshots and a published BI link.