AI agent blueprints for Data & Analytics.
Data workflows that make definitions, lineage, evidence, and uncertainty explicit before a human approves changes or conclusions. Each pattern defines the evidence it reads, the artifacts it produces, the authority it may exercise, and the human who makes the consequential decision.
Data platform, analytics engineering, business intelligence, and experimentation teams
data owner
private · read/propose · human-gated
Nine jobs with a crisp acceptance test.
These are implementation patterns, not generic “AI for Data & Analytics” pages. Open one to see its exact trigger, topology, grants, approval boundary, failure modes, and KPI.
Data quality incident triage
Correlate a data-quality alert with pipeline, lineage, freshness, and change evidence and prepare a bounded response packet.
time to reviewed data incident plan
Metric definition review
Compare a proposed metric with source fields, grain, filters, time rules, and existing definitions before governance approval.
duplicate or conflicting governed metrics
Dashboard quality review
Review a dashboard against approved metric definitions, queries, filters, freshness, accessibility, and decision purpose.
certified dashboards passing first review
Data lineage impact analysis
Trace a proposed upstream change through documented datasets, transformations, metrics, and owners and prepare an impact packet.
unanticipated downstream breakages
Data schema change review
Classify a schema change, compare compatibility and quality expectations, and prepare a versioned rollout decision.
schema changes with consumer sign-off
Data anomaly investigation
Decompose an anomalous movement across dimensions and source changes and prepare ranked explanations with uncertainty.
material anomalies with reviewed explanation
Analysis request scoping
Turn a broad stakeholder question into a decision, metric, population, evidence, limitation, and delivery brief.
analysis requests accepted without rescoping
Experiment readout review
Check an experiment readout against the approved design, metric definitions, exclusions, uncertainty, and decision rule.
experiment readouts passing methodology review
Data access request review
Compare a data-access request with purpose, classification, minimization, role, and approval policy and prepare a least-privilege packet.
time-bounded data grants
The workflow is autonomous. The authority is not.
- 01
Attach evidence
Put only this case’s approved inputs in a scoped workspace.
- 02
Run specialists
Each bounded node produces an artifact the next node can challenge.
- 03
Stop at proposal
External writes stay outside the agent’s default authority.
- 04
Record the decision
Keep the human approval as a decision record beside the signed evidence from the agent run.
Pick one expensive, inspectable job.
Start with real evidence, a named decision owner, and a measurable result. Expand the agent only after the receipt and acceptance test prove the workflow holds.