Use case
Use case3 min readBy The Data Workers Team

Data quality and governance, run by agents

Quality rules and access reviews are written by hand for each table, so coverage is partial and audits are painful. Here is how Data Workers runs it instead.

Key takeaways

  • •The problem today. Quality rules and access reviews are written by hand for each table, so coverage is partial and audits are painful.
  • •What changes. Agents write quality rules for every new table, classify sensitive fields on arrival and apply access policy, with every action logged.
  • •What stays with your people. Access to restricted data: need-to-know is a control.
  • •The result. Every table is tested and governed the day it lands.

The problem today

Quality rules and access reviews are written by hand for each table, so coverage is partial and audits are painful.

What changes with Data Workers

Agents write quality rules for every new table, classify sensitive fields on arrival and apply access policy, with every action logged.

The workflow: Quality Monitoring agent (create_quality_tests_for_pipeline) → Data Security agent (scan_pii) → Data Access & Governance agent (provision_access) → Data Access & Governance agent (generate_audit_report).
Fig. 1:The workflow: Quality Monitoring agent (create_quality_tests_for_pipeline) → Data Security agent (scan_pii) → Data Access & Governance agent (provision_access) → Data Access & Governance agent (generate_audit_report).

The workflow, step by step

  1. 1.The Quality Monitoring agent calls create_quality_tests_for_pipeline and writes rules for new tables.
  2. 2.The Data Security agent calls scan_pii and classifies sensitive fields.
  3. 3.The Data Access & Governance agent calls provision_access and applies policy.
  4. 4.The Data Access & Governance agent calls generate_audit_report and exports evidence.

The impact metrics we move

  • •Rules on a new table: from about 2 days to 8-15 min
  • •Sensitive field classified: from about a week to minutes
  • •Audit evidence: from about 2 weeks to 4 h
Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.
Fig. 2:Time to complete, current practice (black) vs. with Data Workers (green). Illustrative.

What goes on autopilot

  • •Rules and classification run on every new table, so coverage is complete.
  • •Every grant is logged, so audits take hours.

Where your people stay in charge

Access to restricted data always go to a named approver, because need-to-know is a control. Everything starts at L1, observing only, and autonomy rises only on evidence.

The pilot

  • •Scope. Quality rules and classification for one domain.
  • •First week. Agents run at L1, observing only, and show the fixes they would have made, with receipts.
  • •By week two. The routine work above runs on its own; anything sensitive stays with a named approver.
  • •At day 30. We review the impact metrics against your baseline:
  • •Rules on a new table: from about 2 days to 8-15 min
  • •Sensitive field classified: from about a week to minutes
  • •Audit evidence: from about 2 weeks to 4 h
  • •Cost. Start with a pilot ($7,500 one-time, credited in full against the first year). Scale is from $1,000 a month and Enterprise from $3,000 a month, billed annually, with unlimited seats, no usage meter and no markup on model spend. See pricing.

Related: The data and IT page · The full team playbook

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