Beyond Search: What We've Learned About Data Discoverability

From Research Insights to Real Change

Last year, we set out to better understand how people discover and access data across our organization. We interviewed users, analyzed feedback, and observed discovery journeys from beginning to end.

One insight appeared consistently throughout our research: people rarely rely on a platform alone.

Even when users find a data product quickly, they often reach out to colleagues, domain experts or data producers before deciding whether to use it. They want to understand how the data is used, what limitations exist, and learn from the practical experiences of others. These are insights that metadata alone can’t always provide.

This observation challenged some of our assumptions. While simplifying processes and improving the user experience delivered clear benefits, we learned that discoverability is ultimately about much more than finding data: it’s about finding knowledge. And it’s people who give knowledge meaning.

These findings led us to three important conclusions.

Realization #1: From Platform to Network

Perhaps our biggest realization is that discoverability behaves less like a search engine and more like a network.

Think about your own experience. When you need data for an important use case, what gives you the most confidence: a search result or a recommendation from someone you trust? In many cases, discovery starts with a conversation.

Your colleague points you to a data product. A domain expert provides business context. A data producer helps answer questions and clarify expectations. As you can see, in practice, data often travels through people before it travels through platforms.

This shouldn’t surprise us, as we know that important decisions rarely rely on information alone. There’s another level: people naturally seek perspectives from others to reduce uncertainty, validate assumptions and gain confidence in their choices.

This doesn’t mean discoverability is failing. In fact, it reinforces an important reality: finding data is only one step in the journey. Before adopting something new, people want to understand how it’s used in practice, what limitations exist and whether others have had success with it.

As a result, we’ve expanded our focus. Instead of just helping users find data products, we’re helping them connect with the people and expertise behind those products.

In conclusion, a Data Marketplace’s value isn’t only the data it contains, but also the relationships, knowledge and collaboration it enables.

What remains to be explored is how this dynamic will evolve in the age of Agentic AI. We’re interested to see how agents become part of the interaction between people and data and how this shapes the way information is discovered, understood and – ultimately – trusted.

Realization #2: Towards a Stronger Data Product Mindset

Making data discoverable is important. Making it valuable is essential.

Through our work on the Data Marketplace, we’ve invested significantly in improving discoverability through better metadata, search capabilities and user experience. These capabilities improve discoverability, but you need more than discoverability to drive adoption.

Over the past year, we’ve learned that many discoverability challenges are data product challenges in disguise. When consumers struggle to find the right data product, oftentimes the issue isn’t search functionality. More often, the product’s purpose, audience or value proposition is unclear.

• Who is this for?
• What problem does it solve?
• Why should you use it?

A strong data product mindset helps answer these questions clearly.

Just as any successful product serves a specific customer need, a data product should serve a specific audience and deliver measurable value. The clearer that value proposition becomes, the easier it is for consumers to understand the product and decide whether it meets their needs.

I often compare this to a library. Even if every book is perfectly organized, finding the right one will be difficult if the title and description fail to explain why the book is relevant. The same principle applies to data products.

Discoverability helps users find data. Value helps them choose it.

Realization #3: Becoming the First Place Users Look

As our understanding of discoverability matured, we found ourselves asking a different question:

Is the Data Marketplace the first place users look when they need data?

Today, many discovery journeys still begin elsewhere: a Teams message, an email, a meeting, a recommendation from a colleague.

This made us realize that there’s more to discoverability than helping users find data products after they enter the platform. It’s also about establishing the Data Marketplace as the natural starting point of their journey.

Our ambition is for our Data Marketplace to be more than a place to search for data. It should be where users discover opportunities, connect with experts and build confidence in the data products they find.

Of course, the value of a Data Marketplace lies in the data it contains. But it also lies in how effectively it brings together data, context, expertise and community. Why? Because people can’t benefit from something they don’t know exists.

This remains one of our biggest opportunities and a key focus as we continue to enrich the experience.

The Next Evolution of Discoverability

A year ago, we started with a simple question: How do people find data? What we've learned since then has significantly expanded our perspective.

Making data easier to search is just one part of discoverability. Another part is connecting people with expertise, providing context and helping consumers understand the value of the data they find.

Our journey has shown that successful discoverability relies on more than search capabilities or metadata quality. It’s about people. It’s about expertise. It’s about providing enough context for consumers to understand whether a data product can help them achieve their goals.

And most importantly, it’s about trust.

Throughout our conversations with data consumers, one question kept returning: "Can I rely on this?"

Data consumers may find the right data product. They may understand its purpose and value. But before they use it to make decisions, they need confidence that it’s trustworthy, reliable and fit for purpose.

That realization is shaping the next phase of our Data Marketplace journey as we explore the role of trust in discoverability, adoption and decision-making. As the era of Agentic AI unfolds, we’re equally interested in understanding how trust, transparency and confidence will evolve when agents become part of the discovery experience.

Because discoverability doesn’t end when you find data you were looking for.

Finding data creates awareness. Understanding creates value. Trust drives adoption.