PHILADELPHIA, PA — Qlik® has unveiled significant enhancements to its AutoML capabilities, aimed at simplifying the process for analytics teams to develop and deploy machine learning models. By integrating these updates into Qlik Cloud, businesses can transition from a reactive to a proactive decision-making approach, allowing them to foresee trends, tackle challenges, and optimize outcomes with increased assurance.
The new features focus on three core areas: intelligent model optimization, native machine learning analytics, and comprehensive MLOps capabilities, all designed to deliver clear, actionable outcomes:
- Intelligent Model Optimization: This feature automates the iteration process and applies best practices in data science, enabling analytics teams to build high-performing models with minimal effort. This optimization ensures that models are not only easier to deploy but also more effective in delivering results.
- Native Machine Learning Analytics: With auto-generated dashboards, users can effortlessly analyze and compare model performance, gaining deeper insights into predictions and the underlying factors. This transparency is crucial for teams to understand the drivers behind predictions and to strategize accordingly.
- Comprehensive MLOps Capabilities: By offering automated monitoring, retraining, and lifecycle management, these capabilities ensure ongoing model accuracy and sustained business value. This continuous oversight helps businesses maintain confidence in their AI outputs and in their ability to make informed strategic decisions.
Brendan Grady, General Manager of Qlik’s Analytics Business Unit, highlighted the importance of these enhancements, stating, “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.”
Qlik’s advancements are designed to maximize the value derived from AI initiatives, ensuring that predictive insights are reliable and comprehensible. The enhancements include real-time API access for immediate insights, associative exploration and what-if analysis for comprehensive scenario planning, and enhanced security measures for data protection. Furthermore, multi-language support broadens accessibility, while AI model monitoring and retraining capabilities keep predictions accurate and relevant.
Mikkel Hecht Hansen, Head of BI at Nordisk Film, noted the impact of these enhancements, stating, “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.”
These updates position Qlik as a leader in providing analytics teams with tools that foster a proactive, data-driven business environment, enabling organizations to respond swiftly and effectively to ever-changing market conditions.
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