docs: add FinTech data quality framework use case guide#347
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mitalidaduria wants to merge 6 commits into
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docs: add FinTech data quality framework use case guide#347mitalidaduria wants to merge 6 commits into
mitalidaduria wants to merge 6 commits into
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Expanded the metadata standard documentation to include detailed explanations of machine learning concepts such as model drift, data lineage, feature engineering, label skew, and data quality SLA.
add business-friendly ML glossary with payments domain examples
… and styling per review
ayush-shah
reviewed
Jul 21, 2026
| <a href="https://openmetadatastandards.org/" target="_blank" rel="noopener noreferrer" className="link">Visit openmetadatastandards.org</a> | ||
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| You'll find quick starts, schema references, semantic web resources, and contribution guides on the official site. | ||
| ## Machine Learning & Data Governance Expansion |
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docs.json redirects this modified route to the unchanged canonical v1.13.x/api-reference/main-concepts/metadata-standard page, so none of this replacement is published; the PR also adds no FinTech guide matching its title. Add the guide under a current versioned path with frontmatter and register it in docs.json, and revert this redirected duplicate.
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This PR adds a comprehensive 'FinTech Data Quality Framework' guide to the documentation under data quality features.
It outlines how to handle 3 critical financial data failure modes (settlement mismatches, orphaned records, and latency violations) using OpenMetadata's native profiling and test suites (such as
columnValuesToBeBetween,columnValuesToBeUnique, and null prevention tests). This bridges platform capabilities with a highly requested industry use case.