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ABC Cookies is a well-known cookie company having distribution all part of the country. They have 20 territories and each territory is having more than 2 towns. Some products issue as bonus quantity without invoice quantity. Customers could return goods if they not satisfy with the product. At that time, they have to return both invoiced and bonus quantity that they have received. The company used to store most of the records of the invoice and return notes. In the data base they have stored following information on movement of quantities. They want to predict the quantity for each town for certain period with minimum of 80% accuracy.
There are more than 20 territories but here we consider only one territory
Each territory has 2 or more towns
Stock territory is each stock code pertaining to each territory
Each customer can place many orders
Every order has unique order number
Date of invoice
Retailer code used to track retailer details
In charger code
Product cod is unique for each product
Return Bonus quantity
Training dataset consist of data 2018/2019 and validating data consist only 2020 data. We should be couscous when validate data for certain period. I suggest to take Jan – Feb data for validation as we had to face global pandemic period thereafter.
Please check how Alteryx help to achieve this as It's more towards ML based model.