Data Product Maturity Checklist
Use this tool to assess a data product/productization's maturity level against DPCH01–DPCH14, calculate a maturity %, and get prioritized recommendations. Your selections are saved locally.
This Data Product Maturity Checklist may be used, shared, and adapted freely, including for commercial purposes, provided attribution is given to KaizenXOne (Founding Architect of BPS).
“Data Product Maturity Checklist — KaizenXOne, Base Product Specification (BPS), licensed under CC BY 4.0.”
📊 Data Product Maturity Checklist
0.0% — Maturity Level 0: Data Asset (Basic Productization)Mark each characteristic as Yes, Partial (50%), or No. Add optional evidence links/notes for governance.
| # | DPCH | Characteristic | Checklist Item | Satisfied only when ... | Weight | Status | Evidence (URL or note) | Pts |
|---|---|---|---|---|---|---|---|---|
| 1 | DPCH01 | Domain-Owned | Named Data Product Owner (DPRO) Assigned | ... a Data Product is owned by the business domain that is the authoritative source of truth for the underlying business concept and its semantically accountable for defining, maintaining, and evolving that meaning—rather than by technology teams or downstream consuming domains, regardless of who builds, operates, funds, or heavily uses the product. | 8% | 0 | ||
| 2 | DPCH02 | Deployable | Independently Deployable Unit | ... a Data Product can be ideated, designed, deployed, and managed end-to-end by the domain using intent-driven self-service automation, with all technical and infrastructural complexity fully abstracted by the platform. | 10% | 0 | ||
| 3 | DPCH03 | Declarative | Defined via Declarative Specification | ... a Data Product is defined through a domain-authored, intent-based declaration using business constructs and assertions, with all technical specifications fully derived and hidden by the platform. | 7% | 0 | ||
| 4 | DPCH04 | Discoverable | Registered in Data Marketplace or Catalog | ... a Data Product is intentionally published into an enterprise discovery surface where unknown consumers can find, understand, and evaluate it without prior relationships or tribal knowledge. | 7% | 0 | ||
| 5 | DPCH05 | Self-Describing | Rich Metadata Embedded | ... a Data Product embeds sufficient business meaning, structure explanation, lineage context, and usage guidance to be understood and evaluated independently by consumers. | 6% | 0 | ||
| 6 | DPCH06 | Trustworthy (via Trust Signals) | Emits Trust Signals | ... a Data Product emits objective, measurable trust signals, metrics there by enabling independent, automated assessment of quality, lineage, compliance, and reliability. E.g DPP | 8% | 0 | ||
| 7 | DPCH07 | Reusable | Reused Across Use Cases or Domains | ... a Data Product is intentionally designed for reuse beyond a single predefined consumer and demonstrates independent adoption across multiple consumer contexts without bespoke producer delivery. | 5% | 0 | ||
| 8 | DPCH08 | SLA–SLO Backed & Observable | Observable with SLAs and Quality Guarantees | ... a Data Product is continuously observable through defined SLAs/SLOs and automated Product Maturity Driven Development (PMDD) enterprise tests that monitor and trend its productization maturity over time. | 7% | 0 | ||
| 9 | DPCH09 | Compliant by Design | Policy-as-Code and Entitlement Controls Enforced | ... federated computational governance (global → divisional → domain → product) is visible to the DPRO during design, bound to the product through deployment and publishing, and executed automatically at runtime via "policy as code" and entitlement enforcement. | 8% | 0 | ||
| 10 | DPCH10 | Addressable | Provides Well-Defined Output Interfaces | ... a Data Product exposes explicit, governed output ports aligned to diverse consumer needs, with experience interfaces acting solely as consumers of those ports rather than as the product itself. | 7% | 0 | ||
| 11 | DPCH11 | Semantically Aligned | Aligned to Enterprise Vocabulary / Ontology | ... a Data Product’s meaning is explicitly aligned to shared enterprise or domain vocabularies and conceptual ontologies, enabling consistent interpretation and safe interoperability across products and consumers. | 8% | 0 | ||
| 12 | DPCH12 | Consumption-Driven Intent | Built for Clear Business or Analytical Purpose | ... a Data Product is intentionally designed and evolved around explicit consumer needs and business outcomes, with its structure and interfaces directly traceable to declared consumption intent. | 7% | 0 | ||
| 13 | DPCH13 | Testable & Versioned | Version-Controlled and Contract-Tested | ... a Data Product evolves through explicit versions protected by automated, consumer-facing contract tests that preserve intent, semantics, quality, and policy expectations over time. | 8% | 0 | ||
| 14 | DPCH14 | Economically Accountable | Included in Chargeback/Showback Model | ... a Data Product operates with full economic visibility, shared producer–consumer accountability, and continuous FinOps-driven optimization, ensuring sustainable cost-to-value alignment over its lifecycle. | 4% | 0 | ||
| TOTAL | 0.0 | |||||||
🎯 Prioritized Recommendations
High Priority — Not Met
- DPCH02 - Deployable (10%): Adopt the HDIP intent driven self-service lifecycle so the domain can independently ideate, design, validate, deploy, and evolve the Data Product through intent-driven automation, without relying on central engineering teams or writing technical deployment code.
- DPCH01 - Domain-Owned (8%): Formally establish a domain-aligned owning collective; nominate a Pillar Lead as DPRO accountable for meaning, outcomes, and evolution; publish ownership and accountability metadata in the catalog.
- DPCH06 - Trustworthy (via Trust Signals) (8%): Emit objective trust signals via a Digital Product Passport (DPP), including quality metrics, lineage transparency, policy conformance, and reliability indicators consumable by automated governance.
- DPCH09 - Compliant by Design (8%): Bind federated policies (global → divisional → domain → product) declaratively during design; enforce access, residency, and compliance controls automatically at runtime with auditable policy-as-code mechanisms.
- DPCH11 - Semantically Aligned (8%): Align product entities, relationships, and measures to enterprise conceptual ontology and canonical vocabulary; publish semantic contracts and validate conformance.
- DPCH13 - Testable & Versioned (8%): Implement consumer-facing contract tests and semantic versioning; enforce backward compatibility gates and publish transparent changelog and deprecation policies.
- DPCH03 - Declarative (7%): Adopt the platform’s intent-driven self-service flow so the DPRO declares business intent, assertions, and policy selections, allowing the platform to automatically generate all derived declarative artifacts (DPDS, DPROD, DPP, logical plans) without manual scripting.
- DPCH04 - Discoverable (7%): Publish the product to the enterprise marketplace with canonical glossary alignment, clear ownership, usage intent, and consumption examples so unknown consumers can evaluate it independently.
- DPCH08 - SLA–SLO Backed & Observable (7%): Define SLIs and SLOs; implement automated PMDD enterprise tests to continuously assess reliability and productization maturity; publish dashboards and escalation paths.
- DPCH10 - Addressable (7%): Expose explicit, governed output ports aligned to diverse consumption modes; document access contracts and ensure experience interfaces consume these ports rather than embedding logic.
- DPCH12 - Consumption-Driven Intent (7%): Explicitly capture intended business outcomes, target consumers, and measurable value expectations; link the product to defined use cases and success KPIs.
- DPCH05 - Self-Describing (6%): Embed clear business narrative, canonical definitions, conceptual ontology alignment, usage guidance, and quality context so consumers can understand meaning without workshops.
- DPCH07 - Reusable (5%): Design interfaces generically without consumer-specific coupling; expose stable output ports and monitor independent adoption across domains to validate reuse.
- DPCH14 - Economically Accountable (4%): Integrate FinOps telemetry to expose cost, usage, and value metrics; establish shared producer–consumer accountability and continuously optimize cost-to-value alignment.
ℹ️ Scoring Guidelines
- Yes = full weight
- Partial = 50% of weight
- No = 0%
≥ 80%: Maturity Level 2: Production-Grade Data Product · 50–79%: Maturity Level 1: Evolving / MVP Product · < 50%: Maturity Level 0: Data Asset (Non-Productized)
🔐 Governance Tips
- Store evidence links to DPDS/DPROD files, dashboards, and policy repos.
- Export JSON for audit trails; attach to PRs or catalog entries.
- Review prioritized recommendations to plan next quarter improvements.