Why Your Next Data Catalog Should Be a Marketplace

At Dataminded, we have helped many organizations set up data catalogs. The story is often the same: initial excitement and high demand are followed by a slow decline in adoption. When we ask why, the feedback is consistent.

The catalog is too complex, too technical, and feels like a massive warehouse of parts with no assembly instructions.

In this blogpost, we will explore why traditional data catalogs are failing to meet business needs and share our vision for the solution: a Data Product Marketplace.

The Challenges with traditional data catalogs

Business problems require connecting data from across the entire organization, but the tools meant to help often end up adding friction. This is because traditional data catalogs suffer from a few fundamental flaws.

The Catalog Paradox: More Data, Less Clarity

The rise of tools like dbt has empowered more people to produce data, leading to an explosion of tables. A catalog’s job is to index everything, but this creates a paradox for business users. The more data you add, the harder it becomes for them to find anything of value. While this comprehensive technical map is a powerful asset for engineers debugging complex, cross-domain data issues, it leaves most consumers scrolling through thousands of tables with vague names like tbl_reg_sls_frc, feeling lost and overwhelmed. The focus remains on technical inventory, not business value.

A Lack of Trust and Context

Finding a table is only the first step. The real challenge for a data consumer is answering the question: “Can I trust this data for my high stakes project?” Without clear ownership, quality scores, version history, or business context, analysts cannot be sure if the data they find is reliable. This lack of trust wastes weeks of time and puts strategic business goals at risk.

Principles for a Modern Data Marketplace

To solve these challenges, we need to shift our thinking from managing technical assets to cultivating a portfolio of valuable products. Our approach is grounded in a few key principles.

Manage Value, Not Just Tables

The fundamental shift is one of abstraction. Instead of managing thousands of individual tables, we should group them into logical Data Products. A data product has a clear purpose, a defined owner, and a lifecycle. It represents a real business concept, like “Vehicle Diagnostics Telemetry” or “Dealer Service Records,” turning a technical inventory into a curated collection of business ready assets.

Should we offer the parts or the product?

Design for Two Distinct Experiences

A modern platform must recognize that producers and consumers have different jobs. It needs to provide two tailored experiences: a user-friendly marketplace for consumers to shop for data, and a powerful management cockpit for producers to own and improve their products. This dual focus ensures both sides have the tools they need to succeed.

Embed Trust at Every Step

Trust cannot be an afterthought. It must be built into the platform itself. Every data product needs at a glance trust indicators like quality scores, user ratings, and clear ownership. By making this information visible and accessible, we empower consumers to move forward with confidence and encourage producers to maintain a high standard of quality.

The Next Generation: A Data Product Marketplace

Building on these principles means re-imagining more than just the tool. It requires a cultural shift away from treating data work as a series of disconnected projects and toward managing a portfolio of products with real customers. The marketplace becomes the hub that enables this change.

For the Consumer: A Journey of Discovery

The consumer experience moves from a frustrating hunt to an intuitive journey.

Discover: Find the right data through conversation The way we find information has changed in every other domain, now it is data discovery’s turn. Instead of needing to know explicit table names, consumers can use a chat-like interface to describe their intent in natural language. An AI assistant can then recommend relevant data products. A quality engineer, for instance, can ask, “I need to find data to predict battery failures in our new EV model.” The system understands this business need and provides a curated list of starting points. This transforms the discovery process from a lengthy search through technical metadata to a focused, business-level conversation.

Discover data through natural language

Evaluate: Build trust through transparent context An AI recommendation is a great boost, but a human must remain in the loop to make the final call. The marketplace provides a clear, comprehensive overview for each data product, but evaluation is more than just a static review; it’s an interactive process.

Crucially, a dedicated Q&A section allows consumers to ask clarifying questions directly on the product page, creating a living document of community knowledge. This direct line of communication with the producers transforms evaluation from a solitary task into a collaborative one. This is complemented by quality metrics, usage statistics, peer reviews, and a transparent version history and product roadmap. Seeing a product that is actively maintained and improved in response to community feedback builds immense trust, while the roadmap offers clarity for cross-departmental planning.

Evaluate on more then just the data

Access: Request data with purpose and clarity Gaining access is more than just getting permission; it’s about establishing a contract for responsible use. The process should be clear and context-rich. By defining the purpose of the request, consumers clarify whether it’s for a short-term experiment or a long-term production integration. This step also serves as a crucial moment for self-evaluation, encouraging consumers to think critically about their needs before making a request. This often leads to more focused justifications and faster feedback loops. U

For the Producer: A Cockpit for Product Management

The producer experience shifts from being a technical gatekeeper reacting to tickets to a strategic product owner proactively managing a portfolio.

Manage Data as a Product

The cockpit becomes their central command center, where they are evaluated on the success of their data products. It provides a clear, holistic view of which products are performing above or below expectations, based on crucial metrics like usage, consumer satisfaction, and direct business impact. This data-driven perspective allows owners to make strategic decisions about their portfolio: which products need more investment, which are stable and require maintenance, and which may need to be retired. This strategic oversight is what transforms data management from a reactive cost center into a proactive, value-driving function.

Connect to Customers

Great products are built on a deep understanding of customer needs. The cockpit provides powerful consumer analytics, combining access requests as well as questions and reviews into a single, unified view. A question from a consumer is no longer just a support ticket buried in an inbox; it is a potential feature, a signal of an unmet need. The producer can take this direct feedback and turn it into a public-facing roadmap item, closing the loop with the consumer. This simple act of transparently acknowledging feedback provides clarity on when a new feature will become available, builds incredible rapport, and shows consumers that their input directly shapes the future of the data they rely on.

Connect to your customers

Conclusion

The promise of a data driven organization cannot be realized with tools that create friction and confusion. By moving from a technical data catalog to a business focused Data Product Marketplace, we can finally bridge the gap between producers and consumers.

This new approach empowers consumers to find the data they need with confidence, enables producers to manage the value of their work, and builds a collaborative culture that accelerates innovation. It is how we transform data from a technical byproduct into a key driver of measurable business value.

Are you interested to help us in making this vision a reality? Clap, comment this the post or learn more and get in touch with us here.