Raw data has order level information one of the largest Supermart in USA. Us the data to create the following tables:
Set 1:
1. Count city wise orders.
2. Calculate customer type wise customer payable.
3. Identify product category wise highest price.
4. Customer type wise average quantity ordered.
5. Salesman – City wise total customer payable.
6. Product Container – Delivery speed wise total orders.
7. Ship mode – city wise average delivery charges.
8. Customer Type – Delivery speed wise total customer payable.
9. Total saving in different product category.
Set 2:
1. What is contribution of city wise contribution of orders in percentage?
2. What is year wise customer payable contribution for every salesman?
3. What percentage of sales are delivered in just one day using Air shipping mode out of all the orders?
4. How many orders are delivered in New York which using air mode?
Dataset -
Solution sheet -
4.1 Workbook - Pivot Tables solution.xlsx
1.4 MB
