2019: Week 34
When in Manchester talking about Tableau Prep and Preppin' Data, an attendee asked if we have done anything about Supply Chain data. This week is a significant challenge so you have the attendee and Jack Parry to blame for helping us with this challenge.
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Chin & Beard Suds Co has some stock level challenges...basically our inventory is down to nothing as our customers are just loving our products. We need to restock our stores but firstly, we have to deal with our Suppliers.
Sadly, our suppliers can only guarantee delivery based on a day of the week and a certain week within the month. This causes us issues as we need to know how much stock we are going to have by certain dates (more on that next week).
This week's challenge is to merge together these two datasets to allow us to do analysis in future weeks. We need to understand how much stock will be available when each month until the end of the year.
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Chin & Beard Suds Co has some stock level challenges...basically our inventory is down to nothing as our customers are just loving our products. We need to restock our stores but firstly, we have to deal with our Suppliers.
Sadly, our suppliers can only guarantee delivery based on a day of the week and a certain week within the month. This causes us issues as we need to know how much stock we are going to have by certain dates (more on that next week).
This week's challenge is to merge together these two datasets to allow us to do analysis in future weeks. We need to understand how much stock will be available when each month until the end of the year.
Requirements
Delivery Schedule
Date Scaffold
- Input this data set:
- Delivery Schedule
- Date Scaffold
- Create date parts to allow both data sets to be joined on the delivery schedule
- You will need to create:
- Week number
- Weekday
- Month
- Week number within the month
- Adjust this value to ensure you capture the 1st, 2nd, 3rd, 4th and 5th instance of each weekday in the month
Output
One file: 7 columns, 48 rows (49 including headers)
Columns:
- Month Name
- Weekday
- Date
- Product
- Scent
- Supplier
- Quantity
The output can be found here for comparison. Don't to forget to fill in our participation tracker and share your solutions with us using #PreppinData on Twitter!