{"repo":"Gaurabh007/Blinkit-Data-Analysis-SQL","free":true,"listed":false,"github":"https://github.com/Gaurabh007/Blinkit-Data-Analysis-SQL","clone":"git clone https://github.com/Gaurabh007/Blinkit-Data-Analysis-SQL.git","description":"“Blinkit Data Analysis using SQL” is a data-driven project that explores Blinkit’s grocery dataset to uncover meaningful business insights using SQL. With a strong focus on performance metrics, customer preferences, and outlet efficiency, this project showcases how structured query logic can transform raw data into actionable intelligence.","language":null,"stars":11,"topics":["blinkitdashboard","dashboard","data-visualization","dataanalysis","dbms","mysql","sql","sql-project"],"license":null,"category":"databases-storage","readme_excerpt":"Blinkit Data Analysis using SQL Tools Used : SQL, Excel, Power BI Dataset Used SQL Analysis Code Power BI Dashboard - Business Problem: To conduct a comprehensive analysis of Blinkit's sales performance, customer satisfaction, and inventory distribution to identify key insights and opportunities for optimization using various KPIs and visualizations in Power Bl. They need a robust and scalable data analytics solution to handle the amount of data and uncover valuable patterns and trends. 1. The overall revenue generated from all items sold. Result: Insight: The total revenue generated from all items sold amounts to a multi-million figure, indicating strong sales performance across the grocery catalog. This metric sets the foundation for evaluating overall business health and revenue trends. -------- 2. The average revenue per sale. Result: Insight: This output shows the average sales value per item sold, offering a view into individual product performance. It helps assess whether revenue is driven by high-value products or a large volume of low-value items. -------- 3. The total count of different items sold. Result: Insight: This query returns the count of all individual product entries, reflecting the scale and diversity of Blinkit's product offerings. A large item count suggests a wide assortment and potentially a broader market reach. --------- 4. The average customer rating for items sold. Result: Insight: This metric provides the mean customer satisfaction score across a","default_branch":null,"files":null,"tree":[],"storefront":"/r/Gaurabh007","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Gaurabh007/Blinkit-Data-Analysis-SQL/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}