Qlik Enhances AutoML Capabilities for Real-Time Predictive Analytics

Qlik, a global data integration, analytics, and artificial intelligence (AI) provider, has announced new updates to its AutoML (Automated Machine Learning) capabilities. These enhancements are aimed at simplifying the process for analytics teams to build and deploy high-performing machine learning models.

Real-Time Predictions with Native Analytics

The updated AutoML features enable native analytics to explain predictions in real-time, allowing businesses to make informed decisions. The integration of these capabilities into Qlik Cloud allows companies to transition from reactive to proactive decision-making.

Focus on Proactive Decision-Making

With these enhancements, businesses can better anticipate trends, address challenges, and optimize outcomes. The new capabilities are designed to provide greater confidence in decision-making, moving beyond traditional reactive approaches.

"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.

Qlik Introduces Key Enhancements to AutoML for Better Business Outcomes

Qlik has introduced several updates to its AutoML (Automated Machine Learning) capabilities, designed to help businesses improve performance and gain clearer insights from AI-driven models. The key features of these enhancements include:

1. Intelligent Model Optimization
The updated AutoML simplifies the process of building and deploying machine learning models by automating iterations and applying data science best practices, ensuring better performance with minimal effort.

2. Native Machine Learning Analytics 
Auto-generated dashboards allow users to easily analyze and compare model performance, offering deeper insights into predictions and the factors influencing them.

3. Seamless Integration with Qlik Cloud
The enhanced AutoML is fully integrated with Qlik Cloud, leveraging existing data infrastructures to create a unified, user-friendly experience for efficient data-driven decision-making.

4. Comprehensive MLOps Capabilities  
With automated monitoring, retraining, and lifecycle management, businesses can ensure ongoing model accuracy and maintain confidence in their AI outputs.

These updates aim to help organizations maximize the value of their AI initiatives, delivering reliable, understandable, and actionable predictive insights.

"The enhancements Qlik is introducing to AutoML promise to significantly accelerate the value we derive from our AI initiatives,” said Mikkel Hecht Hansen, Head of BI at Nordisk Film. “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."

Qlik Enhances AutoML to Improve Predictive Analytics and Decision-Making

Qlik has introduced new enhancements to its AutoML capabilities, empowering analytics teams to make proactive, data-driven decisions with predictive analytics and full model explainability. The updates offer a no-code interface that simplifies the process, providing real-time API access for timely insights, associative exploration, and what-if analysis to support scenario planning.

Enhanced security measures ensure robust data protection, while multi-language support makes the platform accessible globally. AI model monitoring and retraining features help maintain prediction accuracy. These enhancements integrate seamlessly into business operations, enabling organizations to respond quickly and make confident decisions based on reliable data.

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