What’s next for Alteryx – product highlights and trends from Alteryx Inspire 2017
As a 'Challenger' in Gartner's 2017 Data Science Platform Magic Quadrant as well as an established player in the BI and Analytics Magic Quadrant, Alteryx remains to be one of the cutting-edge vendors in the space. If your business is currently using Alteryx or is evaluating it as one of the data science platform vendors to choose form, the following highlights from the recent Alteryx Inspire conference might be useful for you.
Becoming a Data Platform for Chief Data Officers
The big news from the Las Vegas conference is that Alteryx is broadening its software landscape, aiming to be an enterprise data platform not just self-service data preparation tool for citizen data scientists. To this end, they have bought two software companies to integrate their platforms into Alteryx Server. Enter Alteryx Connect and YHat. These acquisitions position Alteryx squarely for Chief Data Officers (CDOs), providing an end-to-end analytics platform that will allow you to develop, deploy, curate and collaborate on all your data analytics processes.
For more information about Alteryx Connect and Yhat, click here.
Product Roadmap Highlights
1. Visual reporting layout
A version of this was demonstrated at last year's conference, during UX previews and it's good to see this is finally about to arrive. The visual layout reporting tool gives you the ability to combine and position multiple report items onto a drag-and-drop interface, to easily build up your reports for auto-generation and to preview your report whilst designing it. This makes the design process much easier, especially if you need to publish and circulate static reports.
This functionality lands in Alteryx 11.3, via the laboratory tools.
In recent years, there has been an increase in the number of in-database tools to support more powerful analytics.
A Spark in-db tool has been introduced, as well as a custom Spark tool which allows you to run Spark code written in R, Python or Scala.
A new Python SDK has been developed to allow you to create custom tools in Alteryx using Python.
Alteryx is introducing new French and German language versions of the tools to improve accessibility and use of the tools amongst new user bases in different countries.
Scaling out with Alteryx has also become easier, with Alteryx Server now available on both Azure and AWS platforms, allowing you to deploy and scale instantly.
Alteryx is currently working on their scale-up capability with their new e2 next-generation engine. This promises to take full advantage of SSD and all the cores available, as opposed to their current, mainly single-threaded processes and tools.
4. UX trends
We had an early preview of some of the potential UX changes that will hopefully be making the leap from development to release.
In the same vein as the new Formula tool, other tools are being rewritten so they can display data changes in a preview mode during configuration. The new Pivot tool – which is a drag-and-drop combination of the Transpose and Crosstab tools – will now display the change to the data as you are configuring it, so that you know exactly how the data will be pivoted before running the workflow. This makes using the tool much more intuitive as any configuration errors can be immediately spotted in the data preview.
Additionally, even closer to production is the new Filter tool, which will become a multi-filter tool. This will enable you to enter multiple filter conditions one after the other, removing the requirement to create large custom filter formulas or string multiple Filter tools together.
For a full list of current roadmap developments, click here.
This is a big year for Alteryx with the broadening of their data platform alongside additions to their core capabilities in Alteryx Designer/Server. Alteryx is also shifting its position to become the enterprise data platform of choice, as demonstrated by their recent acquisitions of Alteyx Connect and YHat, as well as their work in making the Alteryx engine capable of fully utilising enterprise hardware.
For more insights, trends and tips on data analytics, read our blog.