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Alteryx - a solid legacy product
Updated June 25, 2020

Alteryx - a solid legacy product

Christopher Penn | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Alteryx Analytics

Alteryx Analytics was used in my organization for the preparation and processing of datasets prior to handing them off to a BI tool or for additional processing. It ran locally on a Windows server within the firewall so that we could process customer data without violating customer data leaking or being exposed off premises.
  • Data preparation - many of the most common methods built in
  • Data processing and blending - able to to merge datasets
  • Some modeling using statistical methods
  • The techniques included for machine learning are far behind the times
  • The interface can be confusing and overwhelming at times
  • The software integrates but not cleanly with many advanced machine learning platforms
Alteryx Analytics and IBM's legacy SPSS modeler are very comparable, but Alteryx lacks many of the built-in integrations that Watson Studio offers, such as AutoAI, Neural Network modelers, Spark engines, etc. If you were comparing IBM SPSS and Alteryx, it would be a close call. If you are comparing Alteryx to Watson Studio, Watson Studio is the superior product.
Alteryx leverages the built in ODBC capabilities of Windows, which means that it's limited by Microsoft's limitations in Windows. Alteryx isn't cloud-native, and thus offers no hybrid cloud, private cloud, or public cloud support without significant jumping through hoops to make it work. Once you get data into it, it's easy to work with, but it's a heavy lift to get there.
Alteryx outputs can be quite difficult to work with, and its visualization capabilities for reporting and sharing data leave much to be desired. Almost all Alteryx users I know must pair it with visualization tools like Tableau Software.
Tableau Desktop, IBM Watson Studio (formerly IBM Data Science Experience)
Alteryx is excellent in a Windows environment where you need to process data, especially on-premises data. It handles structured data well; it struggles with unstructured data. If you have a heterogenous environment with Mac and Linux workers, you will need to either provision dedicated hardware or use virtual machines in order to run Alteryx.

Alteryx Feature Ratings