Startup Expansion

What this project explores.

This project integrates Python and Power BI to analyze a startup's store expansion performance. It features a 5-page interactive dashboard covering revenue, ROI, marketing efficiency, and detailed store-level insights. Includes data, visuals, and a full PDF report.

Follow the implementation.

1. 01

   Aggregated demographic, sales, and regional market saturation datasets using Python.

2. 02

   Engineered a dimensional model in Power BI with tables for regions, products, and customer segments.

3. 03

   Built DAX formulas to calculate running totals, regional market penetration indexes, and customer lifetime value (LTV) versus acquisition costs.

4. 04

   Visualized geographic performance using interactive map charts and forecasting models.

See the work. Inspect the details.

Revenue, marketing spend, and location performance for an expansion scenario.

Enlarge screenshot ↗

Expansion overview · Screenshot from the repository. Select to enlarge.

INTERACTIVE / POWER BI

Go beyond
the screenshot.

Load the public Power BI report to explore its pages and filters. The interactive view connects to Microsoft Power BI when you choose to load it.

Load interactive report

If the embedded view is unavailable, open the report in Power BI . Published report availability is managed in Power BI.

Choose where to look deeper.

Search the linked source inventory or narrow it to the kind of artifact you want to inspect. Files open at their original source.