This project is a comprehensive dashboard for Blinkit, India’s Last Minute App. The dashboard provides a detailed analysis of various metrics related to sales, item types, outlet sizes, and locations. It helps users understand the performance of different outlets and item categories, offering insights into sales trends, item popularity, and outlet performance.
The dashboard is divided into several sections, each providing specific insights:
- Total Sales: ₹1.20M
- Average Sales: $141
- Number of Items: 8523
- Average Rating: 4.0
- Outlet Size: High, Medium, Small
- Outlet Location: Tier 1, Tier 2, Tier 3
- Item Type: Various categories including Baking Goods, Breads, Breakfast, Canned, Dairy, etc.
- A pie chart showing the distribution of Low Fat (35%, ₹425.36K) and Regular (65%, ₹776.32K) items.
- A bar chart listing sales for different item types, with Fruits and Vegetables leading at ₹178.12K and Seafood at the bottom with ₹9.08K.
- A bar chart showing sales of Low Fat and Regular items by outlet location (Tier 1, Tier 2, Tier 3).
- A line chart showing the sales trend from 2011 to 2022, with a peak in 2018 at ₹204.52K.
- A pie chart showing sales distribution by outlet size: High (37%, ₹444.79K), Medium (21%, ₹248.99K), and Small (42%, ₹507.90K).
- A bar chart showing total sales by location: Tier 3 (₹472.13K), Tier 2 (₹393.15K), and Tier 1 (₹336.40K).
- A summary of total sales, average sales, and number of items for different outlet types: Supermarket Type1, Supermarket Type2, Supermarket Type3, and Grocery Store.
- Sales Distribution: The majority of sales come from Regular items (65%) and Small outlets (42%).
- Top Performing Item Types: Fruits and Vegetables, Snack Foods, and Household items are the top-selling categories.
- Outlet Performance: Supermarket Type1 has the highest total sales (₹787.55K) and number of items (5577).
- Sales Trends: There was a significant increase in sales in 2018, followed by a slight decline in subsequent years.
This dashboard can be used by business analysts, marketing teams, and management to:
- Identify top-performing items and outlets.
- Understand sales trends and make data-driven decisions.
- Optimize inventory and marketing strategies based on item popularity and outlet performance.
To use this dashboard, follow these steps:
- Clone the repository from GitHub.
- Open the dashboard file in your preferred data visualization tool (e.g., Power BI, Tableau).
- Customize the filters and settings as needed to explore different metrics and insights.
We welcome contributions to improve this dashboard. Please fork the repository and submit a pull request with your changes. Ensure that your code follows the project’s coding standards and includes appropriate documentation.
