Automated Machine Learning

The Next Step In Augmented Analytics

Headshot of blog author Josh Good

Josh Good

3 min read

When AI came on the scene in analytics, Qlik took a very different approach than ‘black box’ tools. We felt strongly that AI and machine learning should be utilized to enhance human intuition, instead of replacing it. And of course, the term augmented analytics is now well known. That’s not a coincidence. We led the way for this approach in the industry with our Insight Advisor capabilities in Qlik Sense, combining the power of AI with our unique Associative Engine to support insight generation, automation, and natural language interaction. And now we are bringing the same principle to machine learning.

Machine learning, simply put, is the process of recognizing patterns and drivers in historical data in order to predict future outcomes. In a few short years, ML will go from something exotic (and magical) used by Data Scientists to something broadly used by the wider analytics community. At Qlik, we are leading the way for business analysts to directly utilize AutoML, enabling more areas of your business to get value from predictive analytics. It’s simple, code-free, and transparent – providing not only automated model generation and future predictions, but more importantly, detailed insight into key drivers and why predictions were made.

Of course, Qlik AutoML can’t replace the power of professional data scientists, nor do we aim to. We are looking to put some of the same capabilities into the hands of the business, allowing your analysts to generate tremendous value in more every-day use cases when data science resources are unavailable. This includes areas ranging from sales forecasting to churn reduction, customer acquisition, inventory optimization, spend analysis and more.

And speaking of professional data science, Qlik Sense augments the business user with the power of those investments as well. Real-time Advanced Analytics Integration supports the interactive exploration of calculations from data science and machine learning models within Qlik Sense. Direct, engine-level data exchange with third party data engines delivers new calculations as the user clicks, allowing people to refine context and evaluate the results interactively and visually. We recently released this capability on SaaS, with native connectors for Amazon Sagemaker, Amazon Comprehend, Azure ML, DataRobot, and connectivity for custom solutions built in languages such as R and Python.

So, whether you are looking for a simple, code-free way to generate machine learning models and predictions, or an interactive way to explore professionally built data science calculations, we’ve got you covered. Either way, as a business user, you can now take advantage of predictive analytics and prescriptive analytics to better understand potential business outcomes, plan decisions, and take the right action.

And by the way, we’ve got the action part covered too.

At @Qlik, we are leading the way for business analysts to directly utilize AutoML, enabling more areas of businesses to get value from predictive #analytics.

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