Alteryx Analytics vs Denodo

• Alteryx democratizes data and quickly allows analysts the ability to turn data into intelligence. Data exploration can take new depths as users are capable of interrogating larger sets of data in reduced timeframes. Processes timeframes are reduced to fractions of their legacy counterparts.
• Innovation has been accelerated by using Alteryx to develop quick prototypes that can rapidly be deployed for production use. Similarly, we have used Alteryx to replatform legacy systems. The transition to Alteryx not only reduces the infrastructure requirements, but also places the application/product into a new paradigm for processing, allowing innovative enhancements that were once limited by the legacy system(s).
• Alteryx is a viral application. We've used Alteryx course training, in-house training, webinars and videos and our user community continues to grow. Alteryx is feature rich and each version of software builds reliably on prior versions. New users quickly come to speed on Alteryx and supoprt requirements for new users is minimal.

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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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• I would love better training videos on their website.
• Trying to automate the workflow is at an additional cost.
• If we happen to skip a few versions of Alteryx then it gets difficult to get accustomed to newer versions.

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• Caching - but I am sure it will be improved by now. There were times when we expected the cache to be refreshed but it was stale.
• Schema generation of endpoints from API response was sometimes incomplete as not all API calls returned all the fields. Will be good to have an ability to load the schema itself (XSD/JSON/Soap XML etc).
• Denodo exposed web services were in preliminary stage when we used; I'm sure it will be improved by now.
• Export/Import deployment, while it was helpful, there were unexpected issues without any errors during deployment. Issues were only identified during testing. Some views were not created properly and did not work. If it was working in the environment from where it was exported from, it should work in the environment where it is imported.

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• It gets the job done fast.
• It lends itself well for people with a less-technical aptitude to understand the data process.
• It empower the user to come up with any possible solution to a problem.

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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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