As the volume of data and complexity of IT systems continue to grow, organizations increasingly struggle with a lack of transparency and understanding of what data they actually have. Tables, reports, and pipelines exist across systems, but users often don’t know how to use them, whether the data is up to date, who is responsible for it, or what it's actually for.

To address these challenges, the concept of Data Products has emerged — an approach that organizes data as a discreet product. This means clear ownership, thorough documentation, a defined lifecycle, and real business value.

From Technical Artifact to Valuable Product

Traditional data management focuses on individual artifacts: tables in data warehouses, reports in BI tools, or data processing pipelines. Each of these components exists in isolation, often without context or clear ownership.

A Data Product is a set of data packaged in a complete, functional, and understandable way. It includes not just the data itself, but also its usage context, creation process, quality, limitations, business purpose, and the person or team responsible for maintaining it.

Key Characteristics of a Data Product

The product-oriented approach to data is based on several core principles:

Ownership

Every Data Product has an assigned owner responsible for its quality, freshness, availability, and ongoing development. This eliminates situations where data exists but no one can answer questions about its meaning or reliability.

Contract Between Producer and Consumer

A Data Product acts as a contract — it clearly defines what is delivered, how to use it, any known limitations (e.g. missing data during specific periods), and who to contact for support.

Lifecycle and Status

Each product has a defined lifecycle. Users can see if the product is in development, active in production, or deprecated. This reduces the risk of using outdated or invalid data.

Clear Business Purpose

Data Products are not created just for the sake of it. They must serve a defined purpose - supporting analytical needs, business decisions, or operational processes. This helps users understand not just what they are analyzing, but why.

How is a Data Product Different from Other Artifacts?

A Data Product is not just another table or report. It is a logical layer that integrates various technical components and embeds them in a business context. Unlike:

• Physical objects like tables or ETL processes, which are raw technical elements,
• Data domains, which describe organizational structure and responsibilities,
• Business glossaries, which define terms and concepts but don’t define actual data,

…a Data Product brings all these elements together into a single, coherent, functional tool for working with defined portions of your data system.

Value for Data Producers and Consumers

Data Products bridge the gap between data creators and data users.

• For data producers (e.g., data engineers, analysts, pipeline developers), they provide a clear way to define responsibility and quality. Creators start to think of their work as services — complete, well-documented, and ready to be consumed.
• For data consumers (e.g., business analysts, managers, finance, marketing, or operations professionals), they ensure that data is complete, current, and understandable. There's no need to guess whether data is trustworthy — it comes with documentation and support.

Example Use Cases

In practice, Data Products can take many forms. Here are two examples:

• Exchange Rates - Instead of a single table with central bank API data, a Data Product includes the data retrieval process, procedures to handle missing days (like weekends), quality information, and a detailed usage description. The user knows the data is updated daily, verified, and ready for financial analysis.
• Unified Payments Table - Transaction data comes from multiple sources — credit cards, PayPal, bank transfers. Instead of sharing fragmented datasets, a single product unifies the data into one consistent structure. Consumers don’t need to know the original sources — they have one trusted source of truth.

Driving Cultural Change

The true power of Data Products lies not in technology, but in shifting organizational culture. Organizations begin to treat data not as raw material, but as services delivering value. Each product has an owner, status, purpose, and quality. Teams start working in a more transparent, accountable, and user-centric way.

It’s a shift from “let’s deliver a table” to “let’s build a useful product that truly helps.” It’s the difference between laying bricks and building a cathedral.

Summary

Data Products are a modern approach to organizing data that increases its quality, clarity, and usability. With a clear structure, defined ownership, and business context, they support not just technical teams, but — most importantly — the decision-makers who rely on data every day.

Adopting a product-oriented approach to data helps organizations manage information better — and unlock real business value from it.

Data Products in Dataedo

If the idea of Data Products speaks directly to your data challenges, Dataedo helps you implement it without starting from scratch. You can easily create logical, standalone data units that combine tables, reports, glossaries, data sources, and other assets into one understandable and well-documented product.

With Data Products in Dataedo:

• Users see information in context – each product includes a description, business goal, owner, status, and related technical assets. No more blind searching — everything is in one place.
• Teams know who’s responsible for what – assigned roles (e.g., owner, expert, developer) eliminate confusion.
• Filtering and searching are easy – by name, status, domain, product type – no need to dig through dozens of tables.
• Your documentation is clean and consistent – products become the central point of reference, not just an add-on.

Start organizing your data around real business needs - and see how Data Products can transform your organization. Try Dataedo for free or book a demo.