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Swiggy-Case-Study-Using-SQL

Swiggy Schema Tables : MetaData Description

1. Delivery_Partner : Contains information about Delivery Person.

2. Food : Contains information about Names and details of food types.

3. Menu : Contains information of the prices of each item on the restaurant's menu.

4. Order_Details : Contains details about each order that was created with the food details.

5. Orders : Contains Details about the food, delivery details , order details and the order ratings.

6. Restaurants : Contains information about the restaurent and its cuisines

7. Users : Contains details about the customer.

Case Study Analysis Questions

  • Count of customers have not placed any orders.

  • Average price of each food type.

  • Average price of food for each restaurant.

  • Find the top restaurant in terms of the number of orders for all months.

  • Find the top restaurant in terms of the number of orders for the month of June.

  • Restaurants with monthly revenue greater than given_value.

  • Show all orders with order details for a particular customer in a particular date range.

  • Restaurant with the highest number of repeat customers.

  • Month-over-month revenue growth of swiggy.

  • Top 3 ordered dish.

  • Month-over-month revenue growth of each restaurant.

  • Overall revenue generated by the platform during a specific time period.

  • Average order value per user.

  • Average delivery time for each restaurant, and how does it affect customer satisfaction.

  • Average rating for each restaurant and delivery partner.

  • How do the ratings for restaurants and delivery partners correlate with customer retention.

  • Which days and times see the highest order volume, and are there any patterns in user behavior.

  • Count of orders delivered by each delivery partner and their average delivery rating.

  • Distribution of delivery partners in the Delivery_Partner table.

ORACLE SQL Techniques Used

  1. Joins
  2. Ranking and Partition
  3. Rolling Sum
  4. Moving Average
  5. Descriptive Statistics
  6. CTE (Common Table Expression)
  7. DateTime Manipulation
  8. Grouping and Sorting
  9. Correlation
  10. Rounding
  11. Aggregation Functions
  12. Sub-Queries
  13. Other Analytical functions

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