In this article, discover how data products, data mesh, and data marketplaces are redefining the strategic value of your data assets.
Digital transformation has radically changed the way companies manage their data. Gone are the days of passively storing information—today, data is conceived, industrialized, and commercialized. Data-product thinking treats each dataset as a true product, while data mesh offers a more agile and decentralized approach to organization. At the same time, the rise of data marketplaces is ushering in a new era of monetization and value creation.
From raw data to data product: bringing data to life
Traditionally, data was seen as a byproduct of business activities, often underutilized. With the emergence of data-product thinking, a new approach has taken shape: treating data as a full-fledged product. This means giving it a structured lifecycle—with a roadmap defining its creation, maintenance, potential evolutions, and even its deprecation. Like any software product, data must be documented, tested, and validated to ensure its usability by business teams.
Once enriched and rigorously managed, data becomes a high-quality resource ready for optimal use. This shift in mindset is also about maximizing the added value of data by aligning it with specific use cases. Whether to enhance decision-making, transform the customer experience, or support innovation initiatives, data products offer targeted responses to strategic needs—turning raw data into a true performance driver.
Data mesh: breaking silos and distributing governance
Monolithic architectures (centralized data warehouses) and massive but unstructured systems (data lakes) are reaching their limits in terms of agility and speed. To overcome these challenges, the data mesh proposes a decentralized model, where business domains become fully responsible for their own data products. This accountability ensures that data remains fresh, relevant, and quickly updated.
By standardizing and documenting these data products, interoperability between domains is guaranteed, enabling efficient collaboration. Finally, this architecture supports organic scalability: the platform is no longer constrained by a single central team but evolves naturally as new domains are added or developed—allowing seamless adaptation to the organization’s needs.
Data marketplace: entering the data centeric economy
Data-product thinking and data mesh naturally pave the way for the rise of true data marketplaces, whether internal or external. These platforms enable the buying, selling, or exchanging of data products, turning data into a strategic asset. Internal data—once underexploited—can now generate revenue through APIs, enriched datasets, or analytical services.
These marketplaces also foster open innovation by expanding the collaborative ecosystem: partners, suppliers, and customers gain access to data products, multiplying opportunities for value creation. Built-in governance and security policies ensure quality, compliance, and transparency in exchanges, strengthening user trust and driving adoption.
Governance, security and open source
This new era demands “by design” governance, where controls are embedded from the start rather than retrofitted. Security and compliance—especially regarding GDPR—become essential, with practices such as strict access management, pseudonymization, data encryption, and rigorous usage traceability.
At the same time, open standards and open-source tools—central to Smile’s approach—enable the development of flexible, sustainable solutions while limiting vendor lock-in. This ensures both system interoperability and long-term viability of technology choices.
Data-product thinking, data mesh, data marketplaces… these trends are reshaping the data landscape. Far from being just buzzwords, they provide a strategic framework to fully unlock the value of data, foster collaboration, stimulate innovation, and generate new revenue streams.
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