Qlik Updates AutoML

Qlik, a data integration, analytics, and artificial intelligence solutions provider, has enhanced its AutoML to help analytics teams build and deploy high-performing machine learning models, providing native analytics to explain predictions in real time.

"At Qlik, we understand that trust and transparency are critical in AI-driven decision-making. Our latest AutoML enhancements ensure full model explainability, providing our users with the confidence that their AI models are reliable and performing well. These advancements foster trust and translate into more informed strategic decisions, enabling better business outcomes," said Brendan Grady, general manager of Qlik's Analytics Business Unit, in a statement.

Qlik's latest AutoML enhancements include the following:

• Intelligent model optimization, which simplifies the process of building and deploying machine learning models by automating iteration and applying data science best practices.
• Native machine learning analytics, with auto-generated dashboards that allow users to analyze and compare model performance, offering deeper insights into the predictions and the factors driving them.
• Integration with Qlik Cloud, leveraging existing data infrastructures to create a unified experience.
• Comprehensive MLOps capabilities through automated monitoring, retraining, and lifecycle management.

The latest enhancements to Qlik AutoML enable analytics teams to make proactive decisions with predictive analytics and full model explainability. They include real-time API access for up-to-date insights, associative exploration, and what-if analysis for scenario planning, and enhanced security for data protection, multi-language support, and AI model monitoring and retraining.