In 2025, data isn’t just a byproduct of operations—it’s a product in itself. As businesses continue to navigate the data-driven economy, one trend is becoming increasingly clear: organizations are moving beyond just storing data—they’re commercializing it. Welcome to the Data Product Economy, where internal data marketplaces are reshaping how companies discover, share, and monetize their own data assets.

Just like product listings on Amazon or software in an app store, companies are now creating e-commerce-like ecosystems for enterprise data. These internal platforms treat datasets as products, complete with ratings, documentation, and usage licenses. The shift is opening up entirely new revenue streams and operational efficiencies for modern businesses.

And leading this transformation are platforms like Opendatabay—a powerful bridge between internal data providers and those seeking usable, compliant, and AI-ready datasets.

 

 

From Data Silos to Data Products

Historically, most enterprise data sat unused in departmental silos—locked away in CRM systems, cloud warehouses, and operational dashboards. Getting access often meant dealing with outdated protocols, lack of ownership, or unclear permissions. Valuable data was trapped, and innovation suffered.

But in today’s competitive landscape, treating data as a product changes the game. It means applying product thinking to data assets:

  • Defining ownership (data product owners)

  • Ensuring discoverability and usability

  • Providing clear documentation and usage policies

  • Tracking demand, usage metrics, and feedback

  • Monetizing externally or allocating value internally

This approach not only unlocks the full value of internal data but also creates a structured path to data monetisation—especially when paired with platforms like Opendatabay.

 

 

The Rise of Internal Data Marketplaces

Internal data marketplaces are now being built across Fortune 500 companies, government agencies, and tech startups alike. These marketplaces function as centralized hubs where teams can publish, search, and acquire data without bureaucratic delays.

Here’s how the model works:

  • Business units (marketing, operations, R&D) become data providers

  • Other departments act as data consumers

  • The platform provides tools for browsing, rating, and requesting datasets

  • Usage and performance are tracked, creating visibility into impact

This e-commerce-like experience makes it easier to extract insights, fuel AI development, and reduce redundant data engineering efforts.

But what happens when companies want to take this a step further and generate actual revenue from their internal data assets?

That’s where external platforms like Opendatabay become essential.

 

 

Opendatabay: Enabling Enterprise Data Monetisation at Scale

While internal marketplaces improve operations, Opendatabay helps turn internal data into a revenue-generating product by providing a global AI data marketplace for curated, compliant, and structured datasets.

Organizations can act as verified data providers and list datasets that:

  • Have been anonymized or synthesized for compliance

  • Serve niche industries like healthcare, fintech, logistics, and retail

  • Are labeled and documented for machine learning applications

  • Are updated periodically for real-time modeling

Once listed, these datasets can be:

  • Licensed to startups, researchers, or AI developers

  • Bundled into subscription packages

  • Sold to external buyers with clear usage rights

In essence, companies can monetize data products the same way they monetize SaaS or APIs—without giving away sensitive information.

 

 

The Benefits of Internal and External Data Productization

🔄 Improved Data Reuse

Instead of recreating datasets across departments, teams can access versioned, reusable data products, saving time and money.

📈 Clearer ROI on Data Projects

With usage tracking and monetization, companies can assess which data products deliver the most value—and double down.

🛡️ Compliance Built In

Platforms like Opendatabay enforce licensing and usage transparency, ensuring all shared or sold datasets meet privacy standards.

💰 New Revenue Streams

Data that was once sitting idle in logs or dashboards can now be packaged, listed, and sold to a global audience.

 

 

Real-World Use Cases

Healthcare Providers
Hospitals anonymize patient outcome data and sell predictive health models via data marketplaces, creating new income while contributing to research.

Retail Chains
E-commerce platforms publish purchasing trend datasets internally for marketing teams—and externally for academic research or competitor benchmarking.

Logistics Companies
Fleet management data is turned into synthetic traffic pattern datasets that are sold to city planning and AI mobility startups.

Fintech Firms
Financial behavior models created from transaction data are productized and offered to third-party fraud detection developers.

These use cases demonstrate the revenue potential of enterprise data, especially when paired with secure marketplaces like Opendatabay.

 

 

Why Data Providers Should Embrace Opendatabay

Becoming a verified data provider on Opendatabay comes with major advantages:

  • Global exposure to buyers in AI, academia, and enterprise

  • Tools for creating compliant, high-quality listings

  • Analytics to track views, downloads, and performance

  • Custom licensing for different user groups (open, academic, commercial)

Whether you're a solo developer, a research lab, or a corporation with years of behavioral data—Opendatabay gives you a turnkey solution to join the data product economy.

 

 

Final Thoughts: Data as a Product Is Here to Stay

The rise of internal data marketplaces marks a major shift in how organizations think about and manage information. No longer just a resource to be hoarded, data is now a product—meant to be discovered, rated, shared, and sold.

Platforms like Opendatabay are making it easier than ever for data providers to tap into the data monetisation economy, offering seamless listings, built-in trust, and real commercial potential.

If your organization is sitting on valuable, structured, and underutilized data—it’s time to stop storing it and start selling it.

The data product economy isn’t the future. It’s now.