About Data Products
Evolution
As organizations scale their data estates, traditional data management approaches—centered around centralized data lakes, warehouses, and purely technical datasets—begin to show limitations. Data is often difficult to discover, poorly contextualized for business users, inconsistently governed, and tightly coupled to platform teams for access and delivery. While metadata management and data catalogs address discoverability, they alone do not fully address ownership, accountability, usability, or governed consumption.
Data Products address this gap by defining data as a governed asset with clear ownership, quality standards, governance controls, and defined consumption methods.
Data Products and the Influence of Data Mesh
Data Mesh is a decentralized data architecture where data is treated as a product and owned, governed, and shared by domain teams. The concept of Data Products is strongly influenced by Data Mesh, a modern architectural and organizational approach that promotes decentralization while maintaining enterprise-wide governance. Data Mesh introduces four core principles:
Domain-Oriented Ownership: Business domains own and manage their data with accountability.
Data as a Product: Data is packaged with quality, usability, and value metrics.
Self-Serve Data Platform: Domains are empowered with standardized tools and infrastructure.
Federated Computational Governance: Governance is automated, standardized, and enforced consistently across domains.
Within this model, Data Products serve as the primary mechanism for domains to operationalize data ownership, balancing autonomy with governance. Instead of data being exposed as raw tables or unmanaged datasets, it is delivered as a curated, governed, and consumable offering.
Data Products
A Data Product is a governed, reusable data asset packaged with metadata, business context, semantics, and access controls for consumption by business and technical users.
Unlike standalone datasets, a Data Product includes:
Defined ownership and governance roles
Business and technical context
Quality and readiness indicators
Controlled access and delivery methods
A lifecycle covering creation, curation, publication, consumption, and ongoing operations
In essence, a Data Product is not just data—it is data with intent, accountability, and usability, designed to deliver measurable business value.
Example: A raw table stores transactional sales records with technical column names and a limited business context. A Data Product package the data with clear descriptions, defined ownership, quality expectations, and access rules, making it ready for consistent business use.
Purpose in OvalEdge
The Data Products capability in OvalEdge enables organizations to implement Data Products within an enterprise data governance framework. It connects metadata management, governance, and data consumption, enabling organizations to:
Package data assets (tables, files, reports, APIs) into a single governed unit
Embed governance, quality, lineage, and semantics into the product
Standardize data discovery, approval, and consumption through a Marketplace
Align data domain ownership with federated governance at scale
Support modern architectures such as Data Mesh while remaining compatible with centralized and hybrid data platforms
By introducing Data Products, OvalEdge enables enterprises to move from cataloging data to delivering trusted, business-ready data products, ensuring that governance is not a bottleneck—but an enabler of scale and self-service.
User Roles and Responsibilities
Data Browser
Discover published Data Products, review summary and quality details, view metadata and lineage, add to the Watchlist, submit questions, and request a subscription.
Data Consumer
Access subscribed Data Products, preview data if enabled, follow Access Instructions, accept updated Data Contracts, provide ratings and feedback, and monitor subscription status.
Data Product Manager
Create Data Domains, register Data Products within Domains, curate Data Products (summary, detailed description, tags, Criticality, Sensitivity, Data Contract details, and related relationships, manage the lifecycle (Draft → Curation → Update), configure subscription settings, and manage Nine Dots actions.
Governance Roles (Owner, Steward, Custodian)
Ensure metadata completeness and quality; review publishing readiness; monitor the Metadata Curation Score; manage governance role assignments; respond to user queries; and oversee compliance and lifecycle updates.
Copyright © 2025, OvalEdge LLC, Peachtree Corners, GA, USA.
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