Is it possible to add random string column for example name or nationality in an alteryx workflow ?.
I have used the following workflow to build the entire dummy data-
https://www.theinformationlab.co.uk/2019/04/29/quickly-generate-dummy-data-in-alteryx/
Is it possible to add 2 random text column (name and nationality) as well to the above workflow ?
These text values should make some sense not like too random, any ideas ?
Solved! Go to Solution.
If you already have name data (you could just download most popular baby names for example) and nationality (https://www.gov.uk/government/publications/geographical-names-and-information) you could select and random sample (Random % Sample Tool) and join on Record position (Join Tool).
Follow the suggestion by @PhilipMannering , I modified the original workflow to give random contry name and names.
1. Coutry name is from the link by @PhilipMannering .
2. Person Names are from
https://community.alteryx.com/t5/Weekly-Challenge/Challenge-120-Popular-Baby-Names/td-p/171607
That's amazing, thanks 🙂
@akash_kumar99
Appreciate you would make it as accept if you think this is what you need.
Since the main aim is to create dummy data for a large dataset, is it possible to add the 2 excel files, used above and just have random names and nationality to the same work flow mentioned in my post ?
@akash_kumar99
How large the data is? Maybe need to repeat the country names. But basically it should work.
I need to append the 2 excel files (Name & Nationality) mentioned in your post to the original workflow in my post, like a random distribution, is that possible ?
If you see @Qiu's workflow
He is assigning an RandomID for country and name which in turn is getting random name and country.
The workflow is purely randomized you can run the workflow for 3 or 4 times you can see the name and country changing each time.
If you are saying like to append Name and Country and create a single file its not suggestable because of records in name db is huge around 97k. If we append name and country it would be 97k x 196 records which is very huge data. Hence this method is suggestable.
Hope this gives some clarity and helps 🙂 feel free to ask more questions.
@atcodedog05
thank you for the detailed explaination.