📊 Blinkit Sales Dashboard — Power BI

An interactive Power BI dashboard built to analyze Blinkit grocery sales data across outlets, item types, and locations. This project covers the full BI workflow — from raw data cleaning to interactive visual storytelling.

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🖼 Dashboard Preview

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🎯 Key Insights

Metric	Value
💰 Total Revenue	$1.20M
🛒 Avg Sale per Item	$140.99
📦 Total Items	1,559
⭐ Avg Customer Rating	3.92 / 5
🏆 Top Category	Fruits & Vegetables
📍 Best Performing Tier	Tier 3
🏪 Best Outlet Size	Medium

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🛠 Tech Stack

Tool	Purpose
Power BI Desktop	Dashboard building & visualization
Power Query	Data cleaning & ETL
DAX	Custom measures & KPIs
Microsoft Excel	Source data format

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📁 Project Structure

blinkit-sales-dashboard-powerbi/
│
├── BlinkIT_Dashboard.pbix        # Main Power BI dashboard file
├── BlinkIT_Grocery_Data.xlsx     # Source dataset
├── dashboard_preview.png         # Dashboard screenshot
└── README.md                     # Project documentation

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📊 Dashboard Features

• KPI Cards — Total Sales, Avg Sales, No of Items, Avg Rating
• Sales by Item Type — Horizontal bar chart showing top revenue categories
• Sales by Outlet Establishment Year — Line chart showing growth trend
• Sales by Item Fat Content — Donut chart (Low Fat vs Regular)
• Sales by Outlet Location Type — Tier 1 vs Tier 2 vs Tier 3 comparison
• Interactive Slicers — Filter by Outlet Size, Location Type, and Item Type
• Cross-filtering — All visuals update together when filters are applied

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⚙ DAX Measures

Total Sales = SUM('BlinkIT Grocery Data'[Sales])

Avg Sales = AVERAGE('BlinkIT Grocery Data'[Sales])

No of Items = DISTINCTCOUNT('BlinkIT Grocery Data'[Item Identifier])

Avg Rating = AVERAGE('BlinkIT Grocery Data'[Rating])

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🧹 Data Cleaning Steps (Power Query)

• Fixed inconsistent values in Item Fat Content column:
  • LF → Low Fat
  • low fat → Low Fat
  • reg → Regular
• Filled null values in Item Weight using Fill Down
• Verified correct data types for all columns (Sales → Decimal, Year → Whole Number)

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📂 Dataset

• Source: Kaggle — BlinkIT Grocery Sales Dataset
• Rows: 999+
• Columns: 12

Column	Description
Item Fat Content	Low Fat / Regular
Item Identifier	Unique product ID
Item Type	Product category
Outlet Establishment Year	Year outlet was opened
Outlet Identifier	Unique outlet ID
Outlet Location Type	Tier 1 / Tier 2 / Tier 3
Outlet Size	Small / Medium / High
Outlet Type	Supermarket / Grocery Store
Item Visibility	Shelf visibility score
Item Weight	Product weight
Sales	Total sales value
Rating	Customer rating

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🚀 How to Open

1. Download and install Power BI Desktop (free)
2. Clone or download this repository
3. Open BlinkIT_Dashboard.pbix in Power BI Desktop
4. All visuals and data will load automatically

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💡 Learnings from this Project

• End-to-end BI workflow from raw Excel data to executive dashboard
• Writing DAX measures for KPI calculations
• Data cleaning and transformation using Power Query
• UI/UX design principles for dashboards — layout, color, readability
• Cross-filtering and interactive slicer design in Power BI

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