QLIK AUTOML®

Deliver No-code, Automated Machine Learning to Analytics Teams

Create ML experiments, identify key drivers in your data, and train models — all to see what might happen, and why.

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Give analysts the power of predictive analytics

Generate models easily

Identify key drivers in your data and generate models with unlimited experimentation.

Make predictions

Reports include full explainability so you can understand what might happen and why.

Test scenarios

Experiment without the risk of failure or the need for excessive effort — like coding.

Publish your experiments

Publish data quickly to Qlik Cloud® Analytics for interactive exploration, real-time models, and what-if analyses.

How no-code machine learning works

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Auto-generate machine learning models

Identify key drivers in your historical data and use the best algorithms to generate machine learning models. Simply select a target field in your data set and let Qlik AutoML do the work:

Determine key drivers in your historical data
Auto-generate predictive models with unlimited tuning and refinement
Select and deploy the best-performing models based on scoring and ranking

A flowchart illustrating the steps of a machine learning process: ML-ready dataset, feature selection, model generation, model tuning and iteration, model deployment, predictions, scenario exploration, and informed actions.

Predict potential outcomes

Just load data to automatically generate likely outcomes based on your predictive model. And more importantly, get explainability data (SHAP values) at the record level, so you know why predictions were made and how to best influence outcomes.

A data dashboard displays charts and graphs for customer churn prediction. An overlay shows a flow from current data to a deployed model with a confirmed territory selection.

Explore predictive data and test what-if scenarios

Qlik's Associative Engine provides real-time, instant calculations to explore. Make interactive selections and shift parameters in what-if scenarios, then evaluate the results to get a feel for what actions will lead to the best outcome.

Illustration of a Qlik dashboard titled 'Customer Churn - What-if Analysis' showing 'Prediction Influencers' and a 'What-if' customer churn metric with a value of 35.98% and selectable plan types.

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Here are some important AutoML use cases

Sales

Sales pipeline – win/loss forecasting
Customer churn / retention
Customer prospecting / targeting

Marketing

Demand / revenue forecasting
Customer lifetime value
Customer next best offer

Finance

Capital investment optimization
Expense management
Risk management / reduction

Operations

Workforce demand prediction
Capacity allocation
Appointment cancellations

HR

Employee retention / attrition prediction
Employee satisfaction
Recruiting / creating an ideal candidate profile

IT

Software / licensing usage
Infrastructure performance prediction

Supply Chain

Inventory stock-outs prediction
Supply chain performance / bottlenecks
Transportation optimization

Service and Support

Support case prediction
Predictive maintenance

AI and Machine Learning Connectors

Easily connect with top AI and machine learning tools like Open AI, Amazon Bedrock, Azure ML, or Databricks ML.

AI and Machine Learning Connectors

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By building AI into everything they deliver, while still maintaining a cloud agnostic approach, Qlik is meeting customers where they are in their AI journey while providing the flexibility needed to expand AI where and how it makes sense.

Dan Vesset

Group Vice President, Analytics and Information Management Market Research & Advisory Practice, IDC