Interactive Power BI Dashboard: Blinkit Sales & Efficiency Analysis

Interactive Power BI Dashboard: Blinkit Sales & Efficiency AnalysisInteractive Power BI Dashboard: Blinkit Sales & Efficiency Analysis

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Sapna Vikram

• 10h

Blinkit Sales & Performance Analysis Dashboard (Power BI)

An interactive Power BI dashboard designed to analyze Blinkit's quick-commerce sales and operational efficiency.

Key Insights :

• Total Sales, Average Order Value (AOV), and Total Orders breakdown.

• Rating analysis based on item types and outlet performance.

• Comprehensive evaluation of sales distribution by outlet size and location tiers.

Developed using advanced Power BI features including data modeling, custom visuals, and interactive slicers to drive data-backed decision-making.

Data Visualization Data Analysis Microsoft Power BI

Yashika Likhitker

• May 17

Built a comprehensive sales analytics dashboard for a retail superstore using Power BI, enabling stakeholders to monitor performance across product categories, customer segments, payment modes, and US states — with dynamic regional filters for Central, East, South, and West.

Business Analysis Data Analysis Microsoft Power BI

Yashika Likhitker

• May 17

The Madhav Store Dashboard is an interactive retail analytics dashboard built to analyze sales performance, profit trends, and customer purchasing behavior. The objective of this project was to transform raw sales data into meaningful business insights that support data-driven decision-making.

This dashboard provides a clear overview of revenue, quantity sold, profit distribution, and payment preferences across different states and product categories.

Business Analysis Data Analysis Microsoft Power BI

Rajdeep Ghosh

• May 17

This project is a full business analysis of an e-commerce toy store using Power BI.

Instead of just showing numbers, the focus is on answering real business questions: Where are we losing customers? Which marketing channels actually drive revenue? Which products are profitable vs risky? Do repeat users behave differently from new users?