Using machine learning to infuse data operations
summary
IBM describes a pipeline that uses metadata‑based machine learning to automate data discovery and classification, deployable as part of an analytics stack with a dashboard that maps sensitive data across the enterprise. Built models detect GDPR and industry‑specific sensitive fields and can ingest regulatory text to flag rules. A customer example claims reduced curation from six months to weeks and days by replacing manual stewarding with automated data classification and lineage tracking.
AI-written summary · about
chapters (4)
- 0:00Introduction
- 0:30Data scientists need access to the right data
- 2:50Data discovery is a manual process
- 4:53GDPR
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