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Error checking

8 - Asteroid

I use Alteryx to prepare survey data for Tableau. I also have a workflow that combines data from many (near identical) surveys together to create a benchmark database. 


The surveys are live and also subject to change. The workflow is run monthly. So It isn't a case of getting the workflow working and then forgetting about it. As surveys are modified or new surveys come on line,  errors can creep in. So I want to build something that is robust. 


Can you please point me to posts / resources that show workflows that incorporate error checking e.g. "Have I lost any fields through the workflow in the attached screenshot?". I go the idea from an excellent training session at Inspire17 in London but I can't find the reference in the recorded materials. 


Thanks in anticipation




19 - Altair
19 - Altair



The place to start is with a field info tool.  Given a read of new data, are the incoming fields what you expect?  Join it to a known source and see if there are new fields present and if you've lost any data along the way.  What comes next is bespoke.  Do you want to check for:


  • Data types - Is it still the same?
  • Domain values - Are values missing or new values present?
  • Content distribution - Is there a skew to the data?
  • Expected values - Is the date or other content what you're expecting for new data?

You might want to run these checks in a workflow and conditionally (CReW) execute the staging of the data.




Something like this will check to see what fields have changed.




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8 - Asteroid

Thanks for your suggestion. The workflow comparing old and new is neat. 

8 - Asteroid

How would I put a check into the existing workflow that takes the field count at the beginning of a series of transformations and then again at the end; compares them and returns an alert (ideally an error message or warning). 


Would I create a new field = count(id) at the beginning, another at the end, compare them?