OpenAI Academy How data science teams use Codex
Use Codex to turn dashboards, metric definitions, exports, and experiment notes into root‑cause briefs, impact readouts, analytics requests, KPI memos, and dashboard specs.
Integrate Codex into data science pipelines by drafting prompts for root‑cause and impact readouts, and validate outputs against live dashboards.
Summary
Codex can turn dashboards, metric definitions, exports, experiment notes, and stakeholder context into root‑cause briefs, impact readouts, analytics requests, KPI memos, and dashboard specs.
Root‑cause analysis produces charts, confirmed drivers, hypotheses, caveats, source links, open questions, and recommended actions.
Business impact readouts quantify lift, guardrails, segment findings, methodology notes, caveats, and a clear recommendation.
Analytics request agents scope the analysis, identify missing inputs, run a first pass, and deliver charts, validation notes, source links, and open questions.
Executive KPI reviews provide charts, anomalies, risks, data‑quality checks, and owner follow‑ups.
Dashboard builders generate KPI hierarchy, chart specs, filters, QA checks, owners, monitoring plans, and publication risks.
Key changes
- Root‑cause briefs include charts, confirmed drivers, hypotheses, caveats, source links, open questions, and recommended actions.
- Business impact readouts quantify lift, guardrails, segment findings, methodology notes, caveats, and a clear recommendation.
- Analytics request agents scope the analysis, identify missing inputs, run a first pass, and deliver charts, validation notes, source links, and open questions.
- Executive KPI reviews provide charts, anomalies, risks, data‑quality checks, and owner follow‑ups.
- Dashboard builders generate KPI hierarchy, chart specs, filters, QA checks, owners, monitoring plans, and publication risks.
- Supports plugins such as Google Drive, Spreadsheets, Slack, Gmail, Documents, and Presentations.