This project presents a comprehensive SQL-based analysis for "Sabor y Tradición," a restaurant focused on refining its menu and gaining deeper insights into customer behavior. By integrating menu details with order information in a relational database, the project provides actionable insights to guide strategic decisions and enhance the overall customer experience.
- Database structure
- menu_items table: Includes dish details such as ID, name, category, price, and optional fields like description or origin (e.g., Italian dishes).
- order_details table: Tracks orders, capturing details like dates, item quantities, total spending, and other relevant data.
- SQL scripts
- Scripts for creating the database and defining relationships between tables.
- A data dictionary (in CSV format) that documents each field for clarity and easy reference.
- Analytical queries
- Three sets of queries (RDB_O1, RDB_O2, RDB_O3) address key business needs:
- Menu analysis: It examines menu items, price ranges, and dish distribution by category.
- Order analysis: It evaluates order data, including total orders, date ranges, and high-volume transactions.
- Customer behavior: It merges menu and order data to identify popular items, spending trends, and opportunities for promotions.
- Three sets of queries (RDB_O1, RDB_O2, RDB_O3) address key business needs:
- Menu exploration:
- Conducted a thorough analysis of the restaurant’s diverse menu, calculating the total number of dishes and segmenting them by category.
- Identified the least and most expensive items, with a particular focus on Italian cuisine.
- Order analysis:
- Reviewed order details comprehensively, including date ranges, total order counts, and overall items sold.
- Detected trends like high-volume orders, opening opportunities for promotions targeting large orders.
- Customer insights:
- Integrated menu and order data to uncover customer preferences and purchasing habits.
- Analyzed top-spending orders to identify patterns in premium purchases, which can guide marketing and menu adjustments.
This project demonstrates the value of SQL-based data integration and analysis in uncovering essential insights about menu performance and customer behavior. Key outcomes include opportunities to adjust pricing strategies, refine menu offerings, and design targeted promotions to boost customer loyalty and drive revenue growth.
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