Methodology

1

Data Profiling & Quality Assessment

Column profiling in Power Query revealed missing values, duplicate records, and date inconsistencies. All issues were resolved before modeling to ensure reliable metrics.

2

Data Modeling & Relationship Design

A star schema was created linking the sales fact table with product, store, customer, and calendar dimensions.

3

DAX Measure Development

Core metrics were created including total revenue, YoY growth, repeat purchase rate, average order value, and customer lifetime value indicators.

4

Customer Behavior Analysis

Customer purchasing patterns were analyzed over time to identify where repeat purchases were declining and which segments were most affected.

5

Dashboard Design & Storytelling

The dashboard was structured to guide stakeholders from overall trends to specific drivers of the revenue decline.

The report is organized across three pages: an executive overview, a customer retention deep dive, and a product & category breakdown.

Power BI DAX Power Query Retail Analytics Customer Retention Revenue Analysis Business Intelligence Data Modeling