Hi peers,
I am trying to understand how the three tools Alteryx, Denodo and Azure Data Factory overlap or complement each other?
We have lots of different data sources with not much data volume but complex data structures from .xls, DB2, SQL Server, OLAP cubes, data via API's and we are looking to find a new way on how to best extract all this data and have our end users report with Power BI out of it.
I assume the underlying best data warehouse would be MS Azure Synapse Analytics. Or is there another data warehouse solution that would make more sense?
Data load volume should not be an issue but the performance of report creation is still a concern.
Thanks,
Stefan
Greetings, Stefan.
Alteryx is basically an ETL tool that evolved to deliver some Data Viz and ML features too. This means that its main purpose is to extract data from different sources, combine and transform them and finally load them in a different database.
Denodo is a data virtualization tool, which means it does all the transformations without extracting from one place and loading to another one. It´s a cloud-based solution and it charges by the traffic. If your company has specific General Data Protection Regulation that prohibits for instance that you extract the data located in a data center in Europe and loading them in a cluster located in the USA, you will probably need a virtualization tool like Denodo instead of an ETL like Alteryx. Virtualization tools are usually more expensive in a long run
Azure Data Factory is a platform meant to leverage the use of Azure. Microsoft´s objective is to sell its cloud solution as a whole. It contains a Data Studio (to manage and control your data), SPARK (which is a Hadoop in memory) and a data lake storage.
As you see, those are 3 different products that do not make much sense to be used together.
I'd say that there is a misconception in some of the answers (but don't worry, it's a common one).
Alteryx is not an ETL tool, it's an analytics platform with very powerful ETL capabilities (accessing mostly all data sources available and processing them at high speeds among others).
But additionally, Alteryx gives you the ability to carry on with the complete analytics cycle, processing, cleaning, blending those diverse data sources, modeling descriptive, predictive, prescriptive analytics (plus some ML & AI), outputting to another humongous variety of data sources, reporting or visualization tools.
All of the previous can be achieved with no coding at all, but in case you want to code, Alteryx also offers Python, R & Scala native integration. In other words, it can solve business users' use cases and advanced/technical use cases at the same time.
Finally, it's a fixed license, with no additional costs per usage (at least so far, until they release the Cloud Version).
I hope I was able to clarify the role of Alteryx in the analytics landscape.
@Alberto Guisande , all big vendors are placing their products in a higher position. Therefore, Alteryx is not placed as an ETL tool anymore but an Analytics Platform. Likewise, Tableau is not a data viz tool but a analytics platform. That´s a marketing pitch to position the product in the market.So, indeed Tableau may integrate with Python and R, bring some ML analysis using natural language and has an ETL (Tableau Data Prep). Likewise, Alteryx also has data viz capabilities and a ML module that you can purchase it. But the bottom line is that Alteryx was born to be an ETL like Tableau was born to be a data viz tool and that´s what they are really good at.
Tableau ETL tool does not have the power of Alteryx just as Alteryx does not have ML capabilities as a Data robots or other ML tools do. Neither has data viz capacibilities like Tableau does
There are clients that are happy to have just an Alteryx as their only BA tool, or Tableau as a BA tool, but again, that is not state of the art for ML algorithm, data storage, data viz, ETL, data collaboration, etc even they all try to convince they are a full platform for BA needs.
Hi @Rushabh-Shah, @Kevin Monte De Ramos, @Avi Shvartz and @AmitJain.
Can you please assist here and share your knowledge with the community?