Master data lineage, quality, and discovery. Build trustworthy, traceable data pipelines with impact analysis, taxonomy, and observability frameworks for 2026.
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111 articles on data governance and management
Data fabric vs data mesh, honestly compared: what each architecture actually is, how governance works in each, and how to decide which fits your organization.
The six data quality dimensions — accuracy, completeness, consistency, timeliness, validity, uniqueness — explained with real examples and how to measure each.
A practitioner's MDM buyer's guide: deployment model, domain depth, matching engines, integration, and TCO — plus a decision framework you can run this week.
Compare Collibra and Atlan for data governance. See architecture, pricing, metadata approach, and which fits mid-market vs. enterprise needs in 2026.
A complete data steward job description: core duties, required skills, salary ranges, interview questions, and a free downloadable JD template pack.
The genuinely free data governance maturity assessments compared: DCAM, CDMC, DataCamp, public-sector tools, and interactive DAMA-based options - no email gates.
Data governance platforms ranked for 2026: six platforms scored on six criteria, the reasoning behind every number, and how to re-weight for your shortlist.
AI-drafted data quality rules are a review problem, not an authoring one. Here's the prompt contract, four-bucket rubric, and deployment checklist from one run.
Metadata management in data catalogs: what to capture, inheritance patterns, how to reduce manual effort, and keep metadata fresh without burnout.
Collibra vs Purview compared for 2026: catalog depth, lineage, pricing (license vs. Azure consumption), lock-in risk, and which fits your governance maturity.
Data observability explained: the five pillars, how it differs from data quality, tooling, and how to catch pipeline issues before they reach the business.
DSARs explained for data teams: what a data subject access request is, GDPR and CCPA timelines, how to fulfill one, and the governance you need to scale it.
Data profiling explained: column, cross-column, and cross-table techniques, profiling tools, and how to turn profile results into data quality rules.
Microsoft Purview, formerly Azure Purview, explained for data teams: Data Map, Unified Catalog, lineage, sensitivity labels, DLP, pricing, and where it fits.
The four MDM implementation styles explained: registry, consolidation, coexistence, and centralized — trade-offs, fit, and how to choose for your domain.
Build a data retention policy that survives audit: retention schedules, legal holds, defensible deletion, and how to operationalize retention across systems.
Open source data catalogs compared: DataHub, OpenMetadata, and Amundsen — features, lineage, governance fit, and the real cost of self-hosting in 2026.
How to structure a data governance council: the three-tier model, who sits on it, what the charter must contain, a quarterly agenda, and why most councils fail.
Master data quality metrics and monitoring in 2026. Learn what to measure, how to set thresholds, and build a monitoring program that actually scales.