Alteryx vs Denodo

• It has a very intuitive interface
• It enables working with very large data sets
• It is a really useful tool for data preparation work to pilot and design dashboards
• It is easy to explain the data processing workflow to your colleagues

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• Flat learning curve.
• Does not need brilliant developers.
• Less need for custom denodo wrappers, even if needed is not very complex.
• Denodo stored procedures and functions helped address complex, not straightforward requirements.
• Export/import deployment between environments was very helpful.

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• It is very hard to scroll within a workflow--it goes from slow to fast and no medium speed.
• I would love a feature to "pop out" the workflow to view in a full size window.
• Sometimes there are errors in the workflow that appear out of nowhere and resolve themselves. But it can cause the workflow to error out.

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• Lack of Documentation and user community: Denodo continues to have a small community of super users, therefore there is not a lot of documentation out there in the event you get stuck.
• Cost: Data virtualization isn't cheap, so smaller organizations might shy away from this technology due to the high licensing costs.
• Caching strategy: Some slower datasets will require caching... which argues, why not just do traditional ETL if you need to do this?

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• Alteryx does an excellent job of integrating consumer and spatial data to calculate and visualize things like locations within a certain drive-time radius.
• For visualization purposes I had to move the data to excel for some decent graphs.
• It can become very expensive.

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• Improved time-to-market. We addressed new requirements in less than 2 person days.
• Very agile. Easy to handle changing requirements. Like a new requirement, a change in requirement was not expensive either.
• Platform issues were difficult to diagnose and debug.

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