SQL-based data analysis project solving real-world business problems for a Blinkit assignment. Includes optimized queries to derive actionable insights from structured datasets.
This project showcases my work on a SQL-based data analysis problem from Blinkit, where I applied SQL queries to solve various business and data problems. The goal was to extract meaningful insights from a dataset, focusing on sales, customer behaviour, and operational metrics.
The problem statement for this assignment can be found in the above pdf. It outlines various data analysis tasks that require writing SQL queries to extract and analyze business-critical metrics.
- Blinkit Data Analyst Assignment.pdf: The problem statement for the SQL assignment.
- queries.sql: A folder containing the SQL queries I wrote to solve the problem. It includes both basic queries and optimized versions for efficiency.
- Blinkit_DA_SauravSharma.pdf: A PDF report containing an in-depth analysis of the findings and business recommendations.
In the queries.sql file, you will find SQL queries designed to extract and analyze key business metrics. These queries were used to:
- Analyze customer behaviour, including churn rate and sales trends.
- Optimize performance with advanced SQL techniques like joins, aggregations, and subqueries.
- Download the queries.sql file.
- Execute the queries in your local SQL environment or any cloud-based SQL tool (like Google Cloud SQL or AWS RDS).
- Review the results and insights in the Blinkit_DA_SauravSharma.pdf.
- SQL (MySQL)
- Data analysis techniques (aggregation, joins, etc.)
- Report generation tools (MS Word)
If you have any questions about this project or want to talk about it more, please feel free to contact me at Email: [email protected] LinkedIn: https://www.linkedin.com/in/saurav82190/