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Ontology vs semantic layer decided with four questions. What a data ontology is, who owns what, and the vendor documentation behind every claim.
by
Jatin S
Updated on
September 9, 2026
Nine Informatica alternatives for data governance, compared on catalog, lineage, quality, monitoring and published pricing, with every vendor claim cited to the documentation it was read from.
By
Unity Catalog governs everything inside Databricks and stops at its edge. What it covers, the documented limits on lineage and quality, and when it is genuinely enough.
Microsoft Purview vs Collibra for banks, insurers and healthcare: audit log retention, lineage as evidence, access control and cost, cited to vendor documentation and primary regulation.
OvalEdge vs Alation for a mid market data team, compared on licensing, stewardship load, time to first alert and how far each quality engine reaches, with every claim cited to vendor documentation.
When Snowflake Horizon is enough and when it is not: the edition gates, the coverage limits and a decision rule, every claim cited to Snowflake documentation.
Collibra vs Informatica compared on catalog, lineage, quality, observability, deployment and cost, with every claim cited to the vendor documentation it was read from.
Atlan vs Microsoft Purview as a data catalog: source coverage, lineage, classification limits and billing, every claim cited to the vendor documentation.
Alation vs Collibra compared on catalog, lineage, quality, governance and cost, with every claim cited to the vendor documentation it was read from.
Alation vs Atlan compared from both vendors own documentation: column level lineage, native data quality, the anomaly detection each one runs, and the gap they share.
Collibra fits regulated enterprises with a governance team. Atlan fits cloud native teams on Snowflake, Databricks or BigQuery. Here is how to decide, from the documentation.
The 9 capabilities GDPR and HIPAA each require of a data platform, cited to the article and CFR section that sets them, plus what no vendor can do for you.
An AI governance maturity model with five stages, a self assessment checklist and what to fix at each stage to advance enterprise AI governance.
August 22, 2026
What is an AI governance framework and how do you build one? A practical AI governance policy structure, controls and evidence pack for regulated teams.
Compare 17 AI governance tools and platforms for 2026, with pricing, strengths and trade offs for each. See which AI governance software fits your stack.
What data silos are, the three types and why they form, which ones to break and which to leave, and how to fix them by centralising context rather than moving data.
Compare 18 data lineage tools for 2026, with pricing, column level support and trade offs for each. See which data lineage software fits a regulated data team.
August 17, 2026
Compare OpenMetadata, DataHub and Amundsen against commercial data catalogs, with the real cost of self hosting and which one fits your team.
Why OJK compliance has become a weeks-long data governance exercise—and how Decube makes traceability easier.
Jatin Solanki
August 10, 2026
Sneak peek from the data world.