Qlik and Starburst Turn Fragmented Enterprise Data into Governed, AI-Ready Intelligence

Bengaluru , June 4 : Qlik recently announced a strategic partnership with Starburst to help enterprises turn fragmented data into governed, AI-ready intelligence. The collaboration will pair Qlik’s data integration, replication, analytics and agentic workflows with Starburst’s federated query engine, context layer and agentic capabilities, giving customers more choice in how they query, move, prepare and use data across cloud, on-premises and hybrid environments.

Enterprise AI is running into a structural data problem. Models, agents and applications are advancing quickly, but the data they depend on remains spread across clouds, warehouses, lakes, SaaS applications and on-premises systems. Centralizing everything can add cost, latency, compliance exposure and lock-in. Leaving data fragmented, without shared definitions or governed context, limits what AI can understand and do.

Qlik and Starburst address that gap by connecting federated access, shared business context and data operationalization. Starburst helps customers query distributed data and apply consistent context and governance. Qlik and Starburst both contribute to preparing and transforming trusted data, with Qlik orchestrating the workflow and logic and Starburst serving as the execution engine across distributed environments. Qlik also helps replicate, analyze and operationalize that data for business intelligence and AI. Together, the companies help customers keep data where it belongs, move it when it creates value, and give AI the trusted context it needs to act.

"The bottleneck for enterprise AI isn't the models - it's the data architectures they're asked to work with. Fragmented, ungoverned data doesn't just slow AI down; it makes the outcomes untrustworthy,” shared James Fisher, Chief Strategy Officer, Qlik “ What enterprises need is a way to give AI access to the right data, in the right context, with the right controls — without being forced into a single architecture or a costly re-platforming exercise. That's what this partnership will be built around. Qlik and Starburst give customers the freedom to keep data where it belongs, move it when it creates value, and trust what AI does with it."

“Enterprises need more than access to data: they need AI that understands what that data means,” said Matt Fuller, Founder and VP of AI & ML, Starburst. “Starburst gives customers governed, federated access to data wherever it lives, with the business context and semantic layer that makes AI answers trustworthy and consistent. Together with Qlik, we give enterprises a practical path from distributed data to trusted business intelligence and AI, without unnecessary data movement, replatforming or vendor lock-in.”

What’s new

• Federated access for analytics and AI: The companies are developing integration patterns that combine Starburst federated access, context and analytics capabilities with Qlik data integration, replication, transformation and analytics to support trusted BI and AI across distributed environments.
• Hybrid and on-premises reference architectures: The companies have validated joint solution patterns combining Qlik Replicate®, Starburst Enterprise and Qlik analytics for customers operating across regulated, hybrid and multi-cloud environments.
• Context for BI and agents: Starburst’s context layer, analytics and agentic capabilities, paired with Qlik’s integration, replication, transformation and analytics strengths, help business users and agents work from governed data and shared business definitions.
• AI-assisted data pipelines: Qlik and Starburst are working on agentic pipeline capabilities that translate natural language requests into optimized SQL workflows, helping data engineers accelerate pipeline creation while maintaining validation and control.

For customers, the value is architectural choice. They can use the data platforms, applications and deployment models already in place, query data where it lives, move it when the workload requires and preserve the lineage, policy and business meaning AI needs for reliable outcomes.