AI-Assisted Analytics Workflows: Intake to Audit Pack
A guided, multi-course journey that builds this skill from the ground up. Work through the chapters in order, or jump to any lesson.
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From Ask to Contract: What “Done” Must Mean Before You Touch DataClarifying Questions That Lock Metric, Grain, and ScopeDefine the KPI So It Can’t Wiggle: Numerator, Denominator, and Inclusion RulesTurn an AI Draft Into a Human-Owned Analysis PlanAcceptance Tests, Audit Logs, Privacy Redaction, and Escalation Triggers
Give AI Just Enough Schema to Draft Safe ExtractionProve the Extraction Matches the Metric GrainCatch Join Multiplication Before It Corrupts TotalsLock Down Filters and Time Windows With Boundary TestsBuild a Reconciliation Checklist You Can ReuseMake Transformations Deterministic and Reconcile Before vs After
Select EDA Questions and Segments You Can Actually ProveBuild Gold Summary Tables as Your Single Source of TruthPressure-Test Statistical Interpretations Without Becoming a Stats CourseUse an Interpretation Checklist to Catch Denominator and Seasonality TrapsDraft Chart Specs and Reconcile Every Visual Back to a Gold TableWrite an Evidence-Cited Executive Summary With Privacy Guardrails
A Pipeline That Runs Is Not a Pipeline You Can TrustMake the Environment a First-Class Deliverable (venv + Dependencies)Refactor the Notebook Into a Parameterized Script With an I/O ContractEliminate Hidden State: Ordering, Seeds, and Time ZonesBuild Logging Checkpoints That Double as Regression SignalsEquivalence Tests: Prove the Refactor Preserved ResultsWhen Tests Fail: Tolerances, Silent Refactor Bugs, and the Reproducibility Record
Assemble Front Matter: The Analysis Contract a Reviewer Can ExecutePackage SQL and Transformations With Executed QA EvidenceMake Claims Traceable: Map Dashboard and Narrative to EvidenceCompile the Prompt, Assumptions, and Equivalence Evidence Into a Review TrailRun the Privacy Review and Publish an Audit-Pack Index and Self-Critique