For CIOs and CDOs, Data Marketplaces Can Be the AI Strategy Hub

Many organizations lack an easy way for all of their staff (not just data scientists or data engineers) to find and leverage that data. As they look to scale AI and go Agentic, one question becomes critical – can everyone that needs to efficiently find, trust, and use data across your organization?

This is where data marketplaces shine – bringing a familiar, everyday ecommerce experience to enterprise data. We’ve invested heavily in upgrading our data marketplace experience because we see it as the central hub around which the AI spokes of the business can operate.

Think of it as Amazon, but for Data

Just like at home where you browse for products, check reviews, and get exactly what you need delivered right to your door, a data marketplace allows internal teams (or external partners) to search, discover, assess, and subscribe to data products, all within the guidelines of data governance.

There are three key stakeholders in a data marketplace. The consumer, the producer and the data governance function in an enterprise.

For the consumer, the key needs are:

• Trust through data quality indicators, lineage, and user ratings
• Speed via automated pipelines and delivery
• The search experience – its speed and ability to help find data that is useful in the context of business need

For the producer, it is the ability to:

• Streamline requests for data through a single portal
• Insights into what data is useful, what data is in demand
• Experience of building and listing data to the marketplace.

For the data governance organization, it is the ability to ensure every user can find the data they are entitled to use to solve a given business problem, providing:

• Control with governance, access workflows, and lifecycle management
• Insights through consumption tracking and usage telemetry

The data marketplace uniquely bridges the gap between data producers (data engineers, stewards) and consumers (analysts, data scientists, business users), enabling faster decision-making, innovation, and AI readiness.

Data Products: The Core of the Marketplace Experience

Data products are the goods that are listed and consumed in a data marketplace. Data products are not just data, but data with a contract. This contract ensures that it is relevant; in the right shape and quality; that freshness of data is measured and is acceptable to the consumer; and that data is easily delivered to those who are eligible to use it. Data products further reduce complexity for the regular data users, and save a significant amount of time that a data scientist today spends in finding the right data.

Data products are fast becoming the building blocks behind AI/ML models, dashboards and reporting, APIs and data-driven services, and even monetizable offerings through a DaaS (Data-as-a-Service).

At the heart of a powerful data marketplace lies a system to manage data products from onboarding to retirement, ensuring discoverability, security, and usefulness at every step.

Yes, AI means Data Marketplaces Matter Even More Now

Every CDO or CIO knows the pain of siloed data, redundant efforts, and slow data delivery before AI. Now with AI and Agents on the way, leaders are seeing their analysts and data scientists spending too much time just finding data. Duplication of similar datasets with no clarity on which models can trust. AI projects stuck in POC due to data costs. A data marketplace addresses all of these through:

• Discovery & Self-Service: Users can search by keywords, tags, domain, or use case – no more guesswork or ping-ponging between teams.
• Data Trust & Governance: With indicators like freshness, quality scores, lineage, and user reviews, consumers know exactly what they’re working with.
• Delivery & Monitoring: Automated pipelines handle provisioning, while consumption data and telemetry help track usage, retirement needs, and opportunities for reuse.

Going Beyond AI Datasets to Full AI Enablement

Should the data marketplace include only raw data? Or should it evolve to offer ETL pipelines, models, dashboards, and pre-built reports?

The answer is a resounding yes.

By offering not just data but also its applications and outcomes, the marketplace becomes a hub and true enabler of enterprise AI. Consumers don’t just get access to data; they get access to solutions.

Imagine a data analyst in a healthcare firm searching for “allergy treatment spending.” They find a curated data product, “Skin Allergy Spending,” enriched with quality metrics, reviews, and HIPAA compliance flags. They subscribe, pass through a workflow integrated with ServiceNow, and within hours, the data is delivered—ready for analysis.

On the other side, a data product creator browses available datasets, reviews lineage and sensitivity, attaches domain logic and metadata, and publishes a governed, gold-rated data product to the marketplace.

This closed-loop ecosystem enables not just data access—but data confidence.

The Pentaho Differentiator: End-to-End Enablement

Many platforms claim to offer a marketplace, but few go beyond basic data cataloging. A truly differentiated data marketplace, like one powered by our platform and driven by Pentaho Data Catalog, offers the full lifecycle.

1. Data Mastering & Onboarding – Seamless integration from disparate systems using ETL/ELT, complete with job stats and transformation history.
2. Quality & Lineage- Real-time updates on data quality, trust scores, and provenance give confidence in what’s consumed.
3. Product Creation & Governance – Data stewards can define access policies, business domains, regulatory tags (HIPAA, GDPR), and terms of use before publishing.
4. Marketplace Experience – Both publishers and consumers have intuitive views of data products, usage metrics, and workflows—from discovery to approval and subscription.
5. Intelligent Feedback Loop – Usage insights, AI-powered recommendations, and activity patterns drive decisions to retire, update, or promote data products.

Why A Data Marketplace?  Let’s Count the Ways

Data marketplaces aren’t just another tool – they’re the hub around which AI, analytics, and data culture can be built. They represent where scalable, governed, and democratized data access needs to be headed.

As you evaluate or evolve your data strategy, ask yourself:

• Are we enabling true self-service for data consumers?
• Can we trust and track our data assets?
• Are we reducing time-to-insight—or extending it?
• Are our AI and analytics teams equipped with not just data, but ready-to-use data products?

If the answer is anything short of “yes,” it may be time to prioritize the data marketplace.

And when done right—with quality, governance, and delivery baked in—it doesn’t just empower your data teams. It empowers your entire enterprise.

Need help accelerating your marketplace vision? Let’s talk.