Blinkit Analytics Dashboard 📊

Hi Everyone,

I'm excited to share my recent Data Visualization Project, "Blinkit Analytics Dashboard", completed using Power BI and Excel! 🎉

Objective: 🎯 Create a comprehensive sales dashboard for Blinkit using Power BI, to analyze key metrics and gain actionable insights to drive business decisions.

Steps: 📝

• Data Collection: 📊 Gathered data from various reliable websites to ensure comprehensive coverage of sales information.

• Data Loading and Cleaning: 💻 Imported the collected data into Power BI, cleaned and processed it by:

• Removing unnecessary columns and duplicates

• Handling missing values

• Changing data types as needed

• Data Analysis: 🔍 Utilized DAX functions, measures, and calculated columns to perform detailed analysis.

Key Metrics Analyzed: 📊

• Total Sales: $1.20M
• Average Sales: $141
• Number of Items Sold: 8,523
• Average Customer Rating: 3.9

Insights: 💡

• Fat Content Analysis:

• Regular Fat Products: $776.32K

• Low Fat Products: $425.36K

• Sales by Outlet Tier:

• Tier 3 outlets led in sales: $472.13K

• Tier 2: $393.15K

• Tier 1: $336.40K

• Top-Selling Categories:

• Fruits & Vegetables: $0.18M

• Snack Foods: $0.18M

• Household Items: $0.18M

• Sales Performance:

• Low-fat items account for 64.6% of total sales

• Stores established in 2018 generated the highest revenue

• Geographical and Store Size Analysis:

• Tier 3 cities lead in sales performance

• Medium-sized stores contribute the highest sales

Recommendations: 🎯

• Increase inventory and marketing efforts for low-fat items and top-selling categories
• Focus on expanding and supporting stores established in 2018
• Consider strategic investments in medium-sized stores
• Develop targeted marketing campaigns for Tier 3 cities
• Investigate customer feedback to improve average customer rating

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