Blinkit Sales Performance Dashboard: This project presents an interactive Power BI dashboard built using the Blinkit sales dataset. The dashboard provides insights into total sales, outlet performance, item categories, customer ratings, and various store attributes.
Project Overview: The purpose of this dashboard is to analyze Blinkit’s sales and operational metrics to support data-driven business decisions. The report visualizes total and average sales, number of items sold, customer ratings, outlet performance by year, product breakdown by type and fat content, store size comparison, location tier comparison, and KPIs for each outlet type.
Key Features and Insights:
*KPI Cards Total Sales: $1.20M Average Sales Per Item: $141 Number of Items: 8,523 Average Customer Rating: 3.9
*Outlet Establishment Trend: A time-series visualization showing outlet performance between 2010 and 2022, with the highest sales recorded in 2018 at $205K.
*Product Insights Fat Content Analysis: Comparative performance of Low Fat vs Regular product categories and their contribution to total revenue. Item Type Analysis: Performance of major product categories such as Fruits and Vegetables, Snacks, Household items, Frozen Foods, Dairy, and others.
*Outlet Analysis Outlet Size: Sales distribution across small, medium, and high-sized outlets. Outlet Location Type: Sales comparison across Tier 1, Tier 2, and Tier 3 cities. Outlet Type Summary: A tabular view showing total sales, number of items, average sales, rating, and item visibility for each outlet type.
*Tools Used: Power BI Desktop DAX Power Query for data cleaning and transformation
*Dataset Information The dataset contains item details (content, type, visibility), outlet attributes (location, size, type), sales data, and customer ratings. A data folder can be added to the repository if needed.
*How to Use Clone the repository. Open the .pbix file in Power BI Desktop. Use the left-panel slicers to filter the dashboard by Outlet Location Type, Outlet Size, and Item Type.
