LinkedIn·Tuesday, 11 August 2026·15d ago

Metadata is now growing beyond passive documentation. It has the potential to become "active". Active metadata is metadata that is…

Maarten Masschelein

CEO & Co-Founder @ Soda | Data and Context Management for AI

Metadata is now growing beyond passive documentation. It has the potential to become "active". Active metadata is metadata that is continuously collected, updated, and used to automate operations in the data environment. Some practical applications for data governance: 👉 Access control: if a dataset is labelled “Confidential,” access restrictions are enforced automatically across platforms. 👉 Data quality management: lineage and usage records can generate alerts when a pipeline fails. 👉 Resource optimisation: performance and usage statistics can drive archival of unused datasets. 👉 Business self-service: glossary terms, ownership details, and lineage are embedded directly into analytics tools. For governance leaders, the significance is straightforward. Active metadata transforms metadata from reference material into operational infrastructure. There is now a fifth application: AI-based data quality. Soda's anomaly detection reads metadata only. It never reads the records themselves. Contract Autopilot works the same way. It analyzes pipeline metadata to generate quality coverage across data sources. This detail decides adoption in many companies. A team can apply AI to its data quality without granting that AI access to customer records. Which of these five applications does your team run today?