Capstone: Present & certify
Deliver the readout, submit the full trail, meet the rubric, and claim the Certified AI Business Analyst credential.
Final step: deliver the readout — live to your real stakeholder if you have one (strongly encouraged; nothing sharpens a one-pager like a real audience), or as a 10-minute recorded walkthrough. Then submit the trail.
Submission package
- Scoping doc (question, signed definition, sources, labeled hypothesis) — dated before the work.
- Discovery pack: syntheses with verbatim quotes, cross-interview pass, verification checklist.
- Analysis trail: the pre-committed plan, findings memo with all five sections, and the numbers log.
- Readout package: charts, one-pager, Q&A prep, both re-framings.
- Process recommendation: annotated map, scored steps with AI seats, the to-be page.
- The AI appendix (unique to this certification): 3-5 prompts that did real work in your capstone, plus one place AI got something wrong and how you caught it. Analysts who can show where the machine failed and how they knew are demonstrating the exact judgment this credential certifies.
Certification rubric
- Discovery (20%) — grounded synthesis (quotes check out), beliefs vs. facts separated, contradictions surfaced rather than smoothed.
- Analysis (30%) — plan pre-committed; findings localized, timed, and mechanism-checked; alternatives killed with named cuts; every quoted number logged and sourced.
- Communication (25%) — one-pager passes the 10-second test; charts honest with claim-titles; uncertainty stated plainly and survives the Q&A simulation.
- Process & judgment (25%) — map verified by a human inside the process; automation scored not vibed, with at least one defended keep-it-human call; recommendation sequenced and owned; the AI appendix shows real oversight.
Passing earns the Certified AI Business Analyst credential (ID format EDOVA-BA-2026-XXXX, independently verifiable at edova.ai/verify). It attests the full arc: AI-accelerated discovery, analysis that survives hostile review, stories that move decisions, and process fixes that hold.
The next course in the AI Business Analyst track is AI for Finance & Accounting — the same investigate-and-defend discipline pointed at budgets, close cycles, and financial forecasts. Beyond it, three natural next steps: Prompt Engineering & Context Design if you want your templates to become production-grade prompt systems; Data Foundations for AI if your capstone's data quality fought you (it teaches the warehouse-side fixes, hands-on); and the Conversational Analytics Agent course if you want to see the governed-metrics interface your Module 3 dashboard spec pointed toward, built end to end. And when your team starts wiring AI into recurring workflows for real, the guardrail principles from Module 4 scale up through LLMOps and AI Governance, Risk & Compliance.