Need help optimizing an Alteryx workflow that’s taking too long to run!

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Oscar

Updated 10 hours ago in

Hey everyone,

I’m working on an Alteryx workflow that processes a large dataset with several joins, filters, and formula tools. The workflow works correctly with smaller datasets, but when I run it on the full dataset containing over a million records, it takes significantly longer than expected.

I’ve tried removing a few unnecessary tools, but the performance improvement has been minimal.

Are there any best practices for optimizing Alteryx workflows when working with large datasets? Would using In-DB tools, reducing unnecessary joins, or changing the workflow structure help?

I’d appreciate any suggestions from people who’ve faced a similar issue!

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Kushwaha 10 hours ago

One thing I’d recommend is checking whether you’re filtering the data as early as possible in the workflow. Reducing the number of records before performing joins can make a noticeable difference in execution time.

I’d also check for duplicate join keys, as they can unexpectedly increase the number of output records. If your data comes from a database, In-DB tools might help by pushing some of the processing back to the database. The Performance Profiling tools can also help identify which steps are taking the most time.

Have you checked which specific tool is consuming the most execution time? That would be a good starting point before restructuring the entire workflow.