This repository documents an analysis of customer ordering patterns on the Swiggy app. The analysis involved the development of SQL query logic, utilizing advanced SQL techniques, and exporting the results into Excel files with accompanying charts for improved data visualization. Key metrics used for this analysis included finding the latest order placed by customers, identifying preferred outlets for repeat orders, determining order frequency, and calculating the total amount spent.
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SQL Query Logic: Developed SQL queries to analyze customer ordering patterns on the Swiggy app.
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Advanced SQL Techniques: Utilized advanced SQL techniques such as window functions, joins, Common Table Expressions (CTE), and group by clauses to generate actionable insights.
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Data Visualization: Exported analysis results into Excel files and created charts to enhance data visualization.
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Key Metrics:
- Latest Order: Identified the latest order placed by customers.
- Preferred Outlet: Determined the outlet from which a customer places orders repeatedly.
- Order Frequency: Analyzed the frequency of orders.
- Total Amount Spent: Calculated the total amount spent by customers.