Analytics

Qlik AutoML – The Power of Machine Learning for Analytics Teams

Headshot of blog author James Fisher. He is bearded and in a navy blue suit and white shirt. He smiles while posing outdoors with greenery and buildings in the background.

James Fisher

3 min read

Screenshot of a Qlik AutoML dashboard showing model metrics, graphs for permutation and SHAP importance, a ROC curve, and a confusion matrix. The best model is auto-selected.

Machine learning is used across industries and user communities for a wide variety of predictive analytics needs – use cases ranging from sales forecasting to churn reduction, customer lifetime value, inventory optimization, capital allocation and more.

Typically, professional data scientists only focus on the top several priorities – in a very deep and sophisticated manner. But what happens to the rest? This is where Qlik AutoML comes in – it brings the power of predictive analytics to the “other 90%” of use cases – allowing your analytics teams to generate tremendous value for your organization.

We can now take advantage of machine learning and AI to move business analytics from purely historical to predictive and prescriptive in nature. With traditional analytics, you’d look at past data and seek to understand what happened. You’d then seek some level of insight about why things happened by digging deeper. Ultimately, you’d attempt to apply these learnings to make better decisions and take more effective action going forward.

With Qlik AutoML, you follow the same logic. It’s just that you utilize machine learning to analyze the historical data and construct models that can predict future outcomes. So instead of guessing, you get a much more concrete and tangible way to make decisions. With both predictions and explainability data, you can see what is likely to happen, and more importantly, why. Armed with insight into possible outcomes and the levers driving them, you can determine how to best take action. And then, you can trigger that action.

A graphic of a lightbulb with an arc above it, illustrating stages: Bring Data Together, Rapidly Experiment, Full Explainability, Explore and Discover, Take Action, and For Analytics Users.

Now fully integrated into Qlik Cloud, Qlik AutoML provides a simple, code-free way for analytics users and teams to leverage automated machine learning – to train ML models, make predictions, and plan decisions. You can leverage the power of our unique analytics engine to explore predictive data and test what-if scenarios in Qlik Sense. And with our end-to-end platform, you can trigger alerts and automations to initiate action.

We’ve included unlimited experimentation and 2 deployed models in every enterprise SaaS subscription so you can experience the power of Qlik AutoML today. We predict you’ll love it once you try it.

Go beyond data science and bring the power of predictive analytics to the “other 90%” of use cases.

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