Upside Briefing: Alteryx
Self-service platform vendor Alteryx is pushing the envelope to offer customers more kinds of advanced analytics. Here is Upside's first impression of Alteryx 10.6.
- By Fern Halper
- July 20, 2016
Name of Company/Solution: Alteryx 10.6
Company Location: California and Global
TDWI Product Market Category: Self-Service Data Preparation/Analytics/Advanced Analytics
Product Vision: To provide self-service data analytics for analysts of all skill levels, including more advanced analytics such as predictive analytics.
Briefing Notes: I recently met with Bob Laurent, VP of Product Marketing at Alteryx, to get an update on its latest release -- Alteryx Analytics 10.6.
If you are not familiar with Alteryx, it provides a platform for self-service analytics. The Alteryx platform enables users to blend data from multiple sources, prepare their data for analysis, and analyze the data. Alteryx provides a drag and drop interface that allows users to build workflows and then reuse workflows developed on the platform.
Release 10.6 is focused on enhancements to predictive analytics. It introduces some new analytics and makes some of its predictive analytics available to more users, such as business analysts.
The highlights of our conversation included:
-- Predictive analytics for business analysts. As part of its strategy to enable business users to utilize more sophisticated analytics, Alteryx is offering a predictive analytics starter kit. The kit allows users to understand the fundamentals of certain kinds of predictive algorithms -- such as regression and A/B testing -- using an interactive, guided approach that includes data samples and macros. It will also be partnering with Udacity to offer online training in business analytics.
-- Introduction of prescriptive analytics functionality. Alteryx is also introducing new analytics to its platform -- specifically around optimization and simulation algorithms that can become a component in a workflow. This is a part of the company's strategy to provide "prescriptive" analytics to users by blending optimization and predictive analytics together in a workflow.
-- Ability to push analytics into Teradata. As part of its big data analytics strategy, Alteryx provides users with the ability to push analytics down to where data resides. With version 10.6, the company is extending this strategy to work with Teradata. Open source R, for instance, can be pushed down into Teradata, along with other data sources (such as a spreadsheet), and models can be built inside the database. The user sees the workflow canvas. The company also announced support for data blending in Databricks.
First Impressions: There were a couple of things I found interesting in the briefing. First, I liked the fact that Alteryx is hoping to train users on more advanced analytics.
Yes, it is moving to position around the "citizen data scientist" -- the business user or analyst who may not have formal training in statistics or math but who performs advanced analytics with easy-to-use software that is currently being marketed by analytics vendors. However, the company realizes that training is important and I like that.
As such, it is helping business analysts learn about advanced analytics -- when to use linear regression versus logistic regression, for instance. This is important as business analysts look to build their skill set. Alteryx is not simply offering "data science in a box."
Second, I like that Alteryx is pushing the envelope in terms of the kinds of analytics it is offering to make its platform more robust for customers. Organizations usually want to act on their data. Prescriptive analytics builds on predictive analytics to suggest or automatically initiate a subsequent action that would produce an optimal result, often using optimization.
In our research at TDWI, we've seen increasing interest in optimization and simulation -- almost on par with predictive analytics. Organizations are also becoming interested in prescriptive analytics. It is early still, but it is coming.
Fern Halper, Ph.D., is well known in the analytics community, having published hundreds of articles, research reports, speeches, webinars, and more on data mining and information technology over the past 20 years. Halper is also co-author of several “Dummies” books on cloud computing, hybrid cloud, and big data. She is the director of TDWI Research for advanced analytics, focusing on predictive analytics, social media analysis, text analytics, cloud computing, and “big data” analytics approaches. She has been a partner at industry analyst firm Hurwitz & Associates and a lead analyst for Bell Labs. Her Ph.D. is from Texas A&M University. You can reach her at firstname.lastname@example.org, on Twitter @fhalper, and on LinkedIn at linkedin.com/in/fbhalper.