A comprehensive Power BI dashboard visualizing sales, outlet types, item categories, and regional insights for Blinkit, India's last-minute delivery app.
Firstly, Data Cleaning is done and then DAX were written for KPIs (Key Metrics)
🧾 Overview
This project provides a detailed sales analytics dashboard to evaluate:
- Total and average sales
- Sales by outlet type, size, and establishment
- Item type distribution
- Fat content category analysis
- Outlet establishment trends over time
- Ratings and number of items
- Geographical breakdown by Tier 1/2/3 locations
📌 Key Metrics
- Total Sales: $1.20M
- Average Sales: $141
- No. of Items: 8523
- Average Rating: 3.9
📈 Dashboard Features
- Interactive Filters: Easily filter by outlet location, size, and item type.
- Outlet Establishment Analysis: Track how Blinkit outlets have evolved since 2012.
- Sales Breakdown:
- By outlet type (e.g., grocery store, supermarket)
- By fat content (Low Fat vs. Regular)
- By item categories (e.g., fruits, snacks, dairy)
- Drill-down Visuals: Gain insights into regional performance and item-specific contributions.
📊 Visual Components
- Donut charts for sales by fat content and outlet size
- Bar graphs for item type-wise sales
- Line chart for outlet establishment over time
- Funnel chart to trace flow of sales by location
- Tabular analysis of outlet types with metrics
- Decomposition tree for analysing factors affecting sales
💡 Key Insights
- Low fat items are more popular than regular ones.
- Fruits & Vegetables and Snack Foods lead item category sales.
- Tier 3 locations and high-sized outlets dominate in revenue.
- Supermarket Type 1 is the most successful outlet type.
- Sales peaked in 2018, dropped in 2020 (likely pandemic), and are recovering.
- Medium outlets play a key role in connecting regional demand and essential item availability.