Systems | Development | Analytics | API | Testing

Use Qlik Answers to manage and create your Data Products!

The challenge for most data teams isn’t a lack of ideas—it’s the time it takes to turn those ideas into something usable. In this session, Steffen Bischoff, Chief Architect Data at Qlik, follows a single dataset from a core system through its entire journey to becoming a governed data product. You’ll see pipelines created by describing intent instead of writing code, versioned in Git, then curated, quality-checked, and documented with the help of specialized agents. From there, the data product is made available to the AI tool of your choice through the Qlik MCP Server.

Qlik CEO Saugata Saha sits down with Jessica DuBois, Senior Director of Global Tech Partners, for his first external conversation since joining the company. Saugata discusses what drew him to Qlik, the opportunity he sees at the intersection of data and AI, and why bringing increasingly capable AI together with trusted, governed data remains one of the most important challenges facing organizations today.

Managing your data pipelines shouldn't mean leaving the tools you already work in. In this video, Qlik Solution Architect, Joe Easley, shows how Qlik's declarative pipelines let you build and manage your integration ecosystem right alongside your own LLM and IDE — no switching platforms, no extra UI to learn. The benefit: faster iteration, fewer handoffs, and pipelines that live where your code already does.

In this video, Mike Tarallo shows you a simple Qlik Automate workflow with defined inputs, then uses the Automate Agent in Qlik Answers to pass those inputs directly into the automation. This demonstrates how users can move beyond simply asking questions and begin taking action based on their data—all from a conversational experience. You’ll see how Qlik Answers and Qlik Automate work together to turn natural-language requests into real, automated workflows with minimal setup.

In Part 3, we keep things simple with a “Hello World” example that shows how to create a basic Qlik Automate workflow and trigger it directly from Qlik Answers. You’ll see how an insight can quickly become an action—all within Qlik, without a complicated setup. Check out Parts 1 and 2 for the full series.

With the Data Quality Agent in Qlik, AI can guide data engineers through a full dataset quality assessment using natural language prompts. The agent can identify trusted catalog definitions, generate intelligent data quality validation rules, and provide transparent reasoning behind every recommendation.

With Declarative Pipelines in Qlik, teams can use tools like Claude Code, GitHub Copilot, and integration with VS Code, to build and update Qlik Talend Cloud data integration pipelines using natural language prompts.

With the Data Product Agent in Qlik, AI can automatically generate curated Data Products using trusted catalog definitions, datasets and metadata. It defines the specification, contract, and reasoning behind the data, while also providing action confirmation before anything is changed.

Join Ouadie Limouni and Mike Tarallo on this week's Qlik Live Stream Friday for a look at Choose Your Champion 2026, an interactive World Cup prediction experience powered by. Ouadie will walk through the application, highlighting how machine learning, interactive analytics, and conversational were combined to create a unique fan experience for World Cup 2026 predictions.