Qlik Joins Snowflake-Led Open Semantic Interchange to Bring Consistent Business Meaning to Analytics and AI

If you have ever asked three teams for the definition of the “same” metric and gotten three different answers, you have already met one of the most expensive, least talked about problems in modern data.

It is not a lack of data. It is a lack of shared meaning.

As analytics and AI spread across more tools, clouds, and teams, business context often fails to travel with the data. A metric defined one way in a dashboard gets redefined in a notebook. A feature used to train a model gets interpreted differently in a downstream report. Over time, “metric drift” becomes inevitable, and with it comes confusion, rework, governance risk, and decisions that do not line up across the business.

This is exactly why Qlik is joining the Open Semantic Interchange (OSI), an open source initiative led by our partner Snowflake to improve semantic interoperability across the data and AI ecosystem.

The semantic gap is now an AI gap

For years, many organizations have accepted that definitions vary by team, tool, and context. The problem is, AI does not accept that gracefully.

AI applications, copilots, and agents rely on context to answer questions reliably and to take actions safely. If “active customer,” “net revenue,” or “risk exposure” means different things across systems, AI can confidently return the wrong answer, or worse, automate the wrong decision at scale.

In other words, the semantic layer is no longer “nice to have.” It is a foundation for trustworthy analytics and AI.

What OSI is trying to solve

OSI is focused on creating an open, vendor-neutral specification for semantic metadata, a common way to represent metrics, dimensions, and definitions so they can be exchanged across environments and reused across tools.

The ambition is straightforward and overdue, reduce fragmentation so business logic can move with the same flexibility as data does. When semantics are portable, organizations can:

• Reduce metric drift across dashboards, notebooks, and models

• Accelerate reuse of business definitions across teams and tools

• Strengthen governance by aligning on common definitions and lineage

• Move faster from data to insight, and from insight to action

OSI brings together partners across the ecosystem, including BI, governance, data engineering, and AI, to define this common approach in the open.

A Natural fit: Qlik and OSI

I’ve always believed open, flexible architectures matter because customers need choice, and they need interoperability as their data estate evolves. OSI fits that belief. It’s a practical way to reduce ambiguity, increase consistency, and help organizations scale analytics and AI with more confidence.

As I said in today’s announcement, “Analytics and AI only create value when people can trust that metrics mean the same thing wherever they are used.” By joining OSI, we are supporting an open approach that helps customers reduce ambiguity, strengthen governance, and speed decisions, so business meaning stays consistent from data products to analytics and AI.

This work matters because semantic consistency is a multiplier. It reduces duplicated effort. It lowers friction between teams. It reduces time spent reconciling definitions. It helps analytics, operational reporting, and AI initiatives align on the same foundation.

What this means for customers

Our goal is simple, help customers keep meaning consistent as they scale.

By participating in OSI, Qlik will contribute to a transparent, community-driven standard for semantic model sharing. Over time, we will align our solutions to support OSI-based semantics so customers can apply consistent definitions across their data architectures and the tools their teams use.

Practically, that means customers should be able to:

• Define a metric once and apply it consistently across analytics and AI workflows

• Reduce rework caused by conflicting definitions across tools and teams

• Improve confidence in dashboards, reports, and AI outputs because the underlying meaning is consistent

• Maintain flexibility as platforms and strategies evolve, without rewriting business logic from scratch

OSI is also an important signal to the market. Semantic interoperability should not be locked into any single platform or vendor. It should be portable, inspectable, and governed in the open, especially as AI use cases become more widespread and higher stakes.

What Qlik will focus on in the OSI community

There is a lot of excitement in the industry about semantics right now, and rightly so. The difference between progress and hype will be execution, clarity, and real interoperability across real tools.

Our focus in the OSI community will be on making the specification practical, usable, and aligned with how organizations actually operate. That includes:

• Consistency and governance so semantic definitions remain reliable as they scale

• Interoperability across workflows so meaning stays consistent across BI, notebooks, and AI

• Real-world usability so teams can adopt the standard without heavy translation layers

• Community collaboration so the standard stays vendor-neutral and customer-led

As Snowflake has said, OSI is about building a unified, vendor-neutral semantic foundation so organizations can simplify operations, foster innovation, and prepare for next-generation AI applications. We share that goal, and we believe open standards are the fastest path to broad ecosystem progress.

A more dependable path from data to decision

In the end, the promise of analytics and AI depends on trust. Trust depends on consistency. Consistency depends on shared meaning.

OSI is an important step toward making semantic interoperability real across the ecosystem. We are excited to contribute, and we believe customers will benefit from a future where business logic is as portable and reusable as the data itself.

To learn more about OSI and the initiative’s direction, check out the Snowflake blog.