New enhancements to Qlik AutoML, a no-code automated machine learning platform, streamline the development and deployment of machine learning models, while offering real-time insights into predictions. By providing native analytics and full model explainability, it bolsters businesses’ ability to make decisions with confidence.
Building trust in AI
The updates focus on enhancing transparency and trust in AI-driven decision-making processes.
“At Qlik, we understand that trust and transparency are critical in AI-driven decision-making,” says Brendan Grady, GM of Qlik’s analytics business unit.
“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.”
Brendan Grady, GM of Qlik’s analytics business unit
Key enhancements:
- Intelligent model optimisation: Automates model iteration and applies data science best practices.
- Native machine learning analytics: Auto-generated dashboards provide real-time comparisons of model performance.
- Seamless Qlik cloud integration: The new features are fully integrated with Qlik Cloud.
- Comprehensive MLOps capabilities: Automated monitoring, retraining, and lifecycle management.
Real-time insights and global accessibility
The updates provide businesses with tools for proactive decision-making through predictive analytics. They include real-time API access, scenario planning through what-if analysis, and improved security for safeguarding data. Multi-language support further expands accessibility for global users.
Mikkel Hecht Hansen, head of BI at Nordisk Film, says: “The focus on model explainability will allow us to trust the insights and make data-driven decisions with greater confidence. This transparency is crucial for our business, as it helps us understand the drivers behind the predictions and act proactively, ultimately leading to better business outcomes.”
* For more information on Qlik AutoML, visit here.