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DMart Sales & Customer Analytics Dashboard
Overview
Developed an interactive Power BI dashboard to analyze retail sales, profitability, customer behaviour, product performance, and store-level performance using a 9,994-row DMart-style retail dataset.
Key Analysis
Sales and profit performance across time
Category and sub-category performance
Top-selling products
Customer segmentation and demographics
Payment method analysis
State, city, and store performance
Discount and profitability analysis
Customer rating analysis
Tools & Technologies
Power BI
DAX
Microsoft Excel
Data Cleaning
Data Modeling
Data Visualization
Key Power BI Features
Interactive slicers
KPI cards
Time-series analysis
Drill-down analysis
Conditional formatting
Dynamic DAX measures
Interactive page navigation
Tooltips
Date-table based time intelligence
Business Objective
The dashboard provides a consolidated view of retail performance and enables users to explore sales, profitability, customer behaviour, and geographic performance through interactive visualizations.
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I Created Microsoft Power BI Dashboard By using many of the Tools
🚀 Data Modelling
🧠 Data Visualization
🚀 Group By
🧠 Data Cleaning
“I developed an Uber Analytics Dashboard using Power BI to analyze trip performance, revenue, demand, customer experience, and operational trends. I worked on data cleaning and transformation using Power Query, created DAX measures and KPIs, and designed interactive visuals for trips by hour/day, revenue, payment types, pickup and drop areas, average fare, and distance. The dashboard helps identify peak demand periods, revenue patterns, popular areas, and customer payment preferences for better business decision-making.”
