New Roadmap Suggestion: Data Governance

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Aptitud para principiantes
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Nueva funcionalidad
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Read the repository’s existing roadmap proposals and roadmap authoring guidance to understand how an accepted roadmap is structured. This issue proposes a broad Data Governance roadmap but names no implementation files or tests; first determine whether the proposal is accepted and where roadmap content belongs. Done means the roadmap is accepted and its proposed topics are represented in the project’s roadmap format.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

roadmap contribution
What is the title of the roadmap you are submitting?

Data Governance

Roadmap Link

Hi team,

I'd like to suggest a Data Governance Roadmap. roadmap.sh has excellent maps for Data Engineer, AI & Data Scientist, DBA and Software Architect, but there is no roadmap for data governance — even though governance is now a named requirement in most enterprise data/AI job postings, and AI adoption has made it a board-level topic.

Proposed audience: data stewards, data/platform engineers moving into governance roles, data architects, and data leaders (Director/VP Data, CDO track).

Proposed top-level structure:

  1. Foundations — what data governance is/isn't, business drivers, DAMA-DMBOK knowledge areas
  2. Operating Model — governance council, data owners & stewards, RACI, decision rights, federated vs centralized models
  3. Policies, Standards & Controls — policy lifecycle, standards, control design, exception handling
  4. Data Quality — dimensions (accuracy, completeness, timeliness…), rules, profiling, monitoring, issue remediation
  5. Metadata, Catalog & Lineage — business glossary, technical/business/operational metadata, cataloging, end-to-end lineage
  6. Master & Reference Data Management
  7. Privacy & Regulatory Compliance — GDPR, CCPA/CPRA, HIPAA basics, classification, consent, retention & deletion
  8. Data Security Governance — access governance, least privilege, masking, audit trails (working with security teams)
  9. Data Lifecycle Management — retention schedules, archival, disposal
  10. Governance for Analytics & AI — dataset readiness, data contracts, model/AI governance basics, responsible AI checkpoints
  11. Metrics, Maturity & Communication — governance KPIs, maturity models, reporting to leadership
  12. Tools Landscape — Collibra, Alation, Microsoft Purview, Atlan, Informatica, Unity Catalog, Apache Atlas (vendor-neutral coverage)
  13. Roles & Career Path — steward → governance lead → Head of Data Governance/CDO; certifications (DAMA CDMP, IAPP CIPP/CIPM overview)

I'm a data & AI architect with 21+ years in enterprise data platforms, including regulated-industry governance programs (GxP/SOX/HIPAA), and I'm happy to author the initial content for the nodes if the topic is accepted.

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