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I have been using Alteryx designer and Alteryx server for a while mainly for modelling and some ETL works. Our company uses Tableau, so one of the benefit is to generate tde files.
Recently there are discussions that we will not be using Alteryx anymore as IT promotes the use of Google Cloud Platform. I do not know much about Google Cloud Platform. My concern is that they are not the same thing.
If you can please let me know if there is an Alteryx equivalent in Google Cloud Platform? And where exactly in your IT roadmap does Alteryx sits? To me, it is an ETL tool, but it is also a modelling tool and also an analytic tool and sometimes a reporting tool. I would like to make a case that Alteryx itself is a unique tool but I really don't have enough talking points to explain it. Help if you can.
Alteryx provides significant value through its platform because of the workflows that are created that both automate and self document processes. As you mentioned, it does a bit of ETL, modeling, analytics, reporting, as well as integrating different systems that wouldn't otherwise be talking, and even leveraging Python and R programming languages or kicking off external commands with the Run tool. It is an easy to use platform that grows with your companies need to develop more advanced analytics.
Maybe the question isn't Alteryx vs Google, but more along the lines of how can you benefit from the strengths of both alongside each other?
Good question I have been doing my own similar comparison to see how cloud options stack up against Alteryx and Tableau (or other data viz/bi tools).
There is a similar GCP product called Cloud Dataprep which is a data workflow application with prep/transformations like Alteryx. They call their workflows "recipes" and are a combination of sequential formulas, renames, and many other data related operations. It reminds me more of Tableau Prep, than it does Alteryx.
The tool is pretty good in terms of common transformations, formulas, and all around options. It is pretty easy to get up and running with, and it charges by compute time so be careful of rapid prototyping where you click "run" every so often as you might in Alteryx. I think GCP is a great option for large at scale data integrations of full blown data applications, but for more ad-hoc analysis, common workflows, and basic apps I would choose Alteryx everyday. The onboarding time of new devs is much lower in Alteryx than GCP. GCP requires intermediate programming skillets and is much easier to architect potentially in-efficient and costly applications if not done properly
Another good use case I found is where you may not have Alteryx server, but are concerned with resources of local machine handling data size/complexity of batch job. GPC can be a great option for throwing more compute power at large complex datasets and only paying for what you need.