Data analytics trends, latest news, upcoming workshops, and more

Alteryx Community Version 19.3

This article is by Alex Koszycki  and originally appeared on the Alteryx Nation Blog here:

Customer Support Improvements
We're happy to provide a few new features and enhancements to the Customer Support Case portal, including a more streamlined case submission process and a sharp new look for your open cases.

Qlik’s next move in AI -The CrunchBot/Crunch Data Acquisition

Qlik has expanded our AI capabilities again, while also growing our existing natural language capabilities, with the acquisition of CrunchBot and the Crunch Data Inc. team of experienced AI and solution development professionals. These capabilities and resources will help enterprises further drive analytics adoption across their organization, and increase data’s value through conversation-driven interactions.

Livewired vs. Hardwired Data

In the digital age, business users need analytics tools that surface anomalies, the unexpected connections in the data. Unfortunately, these unexpected connections would not be seen if the analytics tool uses a relational data layer, where the data is connected by a human based on pre-canned business questions.

We All Start Somewhere

This article is by Ian Wi and originally appeared on the Alteryx Engine Works Blog here:


Many users try Designer and never look back. In fact, many users try Designer, never look back, and go around telling folks they know about their experiences with Designer.

How Ironside Uses DataRobot
A typical Ironside client is a mid-size to large enterprise or a semi-autonomous business unit, brand, or corporate function within a very large enterprise. Because great data scientists are in high demand and still very hard to come by, their clients usually do not yet have a data science function and are seeking to develop this capability internally.

Bias Versus Variance

This article is by Sydney Firmin and originally appeared on the Alteryx Data Science Blog here:


There are two types of model errors when making an estimate; bias and variance.