Define the Data Product Before Choosing the Platform

Start with the Decision It Will Support

Describe the intended user, the decision they need to make and how they will consume the information. An operations team reviewing weekly capacity has different needs from an application responding to an individual transaction. Write down the required level of detail, historical coverage, refresh frequency and definitions of key measures.

Microsoft Purview describes a data product as related data assets grouped around a defined use case, with business context and ownership. Our recommendation is to express the purpose in business language before creating a platform requirements list.

Assign Responsibility Beyond the Build

Name the person accountable for business definitions and priorities, the technical lead responsible for implementation, and the team that will support users after release. Agree who resolves conflicting definitions and approves material changes.

Google Cloud's data mesh architecture distinguishes product ownership, technical leadership, data ownership and production support. Its role definitions can inform this discussion without requiring your organization to adopt a data mesh. Keep the responsibilities explicit even when one person performs several roles.

Make Quality Specific to the Use

Replace a broad requirement for clean data with checks tied to the decisions it supports. Google Cloud's data quality guidance distinguishes freshness, completeness, validity, consistency, accuracy and uniqueness, among other dimensions. A correctly formatted value can still be wrong.

Agree which checks are essential, how failures will be detected and what happens next. A late source feed may require a visible freshness warning; duplicate transaction identifiers may require pausing an affected output. Record acceptable thresholds, exclusions and the owner of each exception.

Design Access as Part of the Product

Identify permitted users, sensitive fields, approved purposes and the process for requesting or removing access. Decide where aggregated or masked information is sufficient. Include retention expectations and any restrictions on sharing or reuse in the product definition.

Microsoft's access policy model brings request procedures, terms of use and approval responsibilities together. For your own implementation, document the equivalent decisions and verify that permissions are enforced in the systems serving the data. A catalog description alone is not an access control.

Define the First Usable Release

Choose a bounded release with named consumers, agreed source coverage and measurable acceptance criteria. Demonstrate the complete path from source data to the user's decision, including quality checks, access approval, documentation and support.

Keep dependencies and unresolved definitions in the delivery plan. Establish how consumers will receive notice of changed fields, revised calculations or retired outputs. Review actual adoption, quality exceptions and support demand after release, then use that evidence to prioritize the next increment.

Compare Platforms Against the Agreed Needs

Use the product definition to compare integration fit, latency, scale, governance controls, team skills and operating costs. Include the effort to build and maintain pipelines, monitor quality, support consumers and manage change.

Nyne's recommendation is to bring business ownership, data architecture and delivery governance into the same planning conversation. A concise product definition gives those teams a shared basis for evaluating technology and deciding what to deliver first.

Sources and Further Reading

• Microsoft Learn: Data products in Unified Catalog
• Google Cloud: Architecture and functions in a data mesh
• Google Cloud: Auto data quality overview

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