2019: Week 42
In Week 26's challenge, we took the opportunity to use only mouse clicks in Prep to see how far we could prepare some data for Chin & Beard Suds Co. This time, the challenge has more elements as the Tableau Prep development keeping adding wonderful features.
Things you might want to look out for this week to help:
- Data Roles: This 'How to...' post will be useful if you haven't used them before
- Prep's recommendation icon
This week's challenge involves helping Chin & Beard Suds Co. go global. We are looking to expand our stores' footprint overseas and therefore need to look at potential costs and returns from those potential sites. An agency has done lots of the work for us but they aren't the best at data entry. They've sent a messy file that they haven't had time to clean up so any inaccurate data should be removed. Don't worry folks, we won't be using them again!
The outputs can be found here for comparison. Don’t forget to fill the participation tracker and share your solutions using #PreppinData on Twitter.
Things you might want to look out for this week to help:
- Data Roles: This 'How to...' post will be useful if you haven't used them before
- Prep's recommendation icon
This week's challenge involves helping Chin & Beard Suds Co. go global. We are looking to expand our stores' footprint overseas and therefore need to look at potential costs and returns from those potential sites. An agency has done lots of the work for us but they aren't the best at data entry. They've sent a messy file that they haven't had time to clean up so any inaccurate data should be removed. Don't worry folks, we won't be using them again!
Requirements
Sheet 1 - The Main Data Set
Currency Table
- Input the data sets
- DO NOT USE ANY TYPED CALCULATIONS
- Calculations created by Tableau from other features selected is fine
- You are allowed to change data field names
- Add Currency conversion rates (don't change everything to USD)
- Remove the rows of any inaccurate City / Country names (we can't trust this data)
- We only want the store per zip code that could the most sales
- Remove any instances where the Store Cost is higher than Potential Store Sales
- Output Data
Output
One file:
- 10 rows (11 including headers)
- 7 Columns:
- City
- Country
- Zip Code
- Store Cost
- Store Potential Sales
- Currency
- Value in USD