One of the challenges that end users regularly face is that in order to really analyze anything, they need to be able to blend data from multiple sources that is often stored in various incompatible formats. The problem is that it often takes a lot longer to extract all the relevant data and then move it into an analytics application than it does to analyze it.
Looking to make it simpler to dynamically blend data across the enterprise, Alteryx today released an upgrade to Alteryx Analytics that makes it simpler to blend data from social media data to legacy and emerging predictive analytics applications.
Alteryx President George Mathew says despite the number of applications that are proliferating across the enterprise, Alteryx views each of those applications as a container that provides yet another potential source of data to be analyzed. Version 9.0 of Alteryx Analytics simplifies that process without requiring end users to enlist the aid of a programmer to accomplish it, says Mathew.
Data sources supported by Alteryx Analytics include social media data feeds such as GNIP and DataShift, Big Data repositories such as Amazon RedShift and HP Vertica, marketing applications such as Marketo and Google Analytics, and predictive analytics applications such as SAS and anything developed using the R programming language.
Across the enterprise today, a new burst of freedom continues to emerge under which end users can now more easily manipulate data and even build their own applications. That’s actually good news for all concerned because programmers would rather spend their time building applications to drive new opportunities for the business than shuffling data sets around the enterprise.