- This project is having big mart sales data.
- In this project, I have fired some queries to do some data manipulation tasks.
- By using SQL, We can efficiently manage and manipulate data, enabling them to gain insights and make data-driven decisions.
- Item_Identifier : Unique product ID
- Item_Weight : Weight of product
- Item_Fat_Content : Whether the product is low fat or not
- Item_Visibility : The % of total display area of all products in a store allocated to the particular product
- Item_Type : The category to which the product belongs
- Item_MRP : Maximum Retail Price (list price) of the product
- Outlet_Identifier : Unique store ID
- Outlet_Establishment_Year : The year in which store was established
- Outlet_Size : The size of the store in terms of ground area covered
- Outlet_Location_Type : The type of city in which the store is located
- Outlet_Type : Whether the outlet is just a grocery store or some sort of supermarket
- Item_Outlet_Sales : Sales of the product in the particulat store. This is the outcome variable to be predicted.