Step 01 of 8 6-10 weeks· advanced
Step 1: Pipeline Inventory and Audit
Inventory every legacy mapping / workflow / package — active vs dead, who consumes it, complexity, criticality, owner. Pipeline counts always come in higher than expected.
Recommended prompts
Use one of these to do the work in your IDE
Open the template to read it in full. Click Copy prompt to grab it (with your stack values pre-filled where they apply) — then paste into Claude Code, Cursor, or wherever you build.
Recommended skills
Drop these into Claude Code for this phase
Skills auto-trigger on the right kind of request. Install once; they apply to every prompt that fits.
Recommended MCP configs
Wire these tools into Claude Code first
MCP servers give Claude Code direct access to external systems (Jira, browsers, databases). Configure once.
When you're done
Verify these in your own work before moving on
This is a checklist for you to mentally tick off in your repo and IDE — the site doesn't track it, you do.
- Complete pipeline inventory (all mappings, workflows, schedules)
- Active vs dead classification (with explicit criteria)
- Consumer mapping for each output (who uses what)
- Complexity score per pipeline (Simple / Medium / Complex / Hairy)
- Critical path identified (jobs that block business operations)
- Dead-pipeline retirement list (don't migrate; just delete)
- SME assignments for migration validation
- Risk register
Common pitfalls
What goes wrong at this step
- Trusting the inventory provided — run actual job-log queries; trust data over documentation
- Missing scheduler dependencies — external schedulers (Tidal, Control-M) often have more coordination than the ETL tool itself
- Ignoring custom code — SSIS Script Tasks, Informatica Java/Python transformations, DataStage routines all hold logic
- Auditing only production — dev / QA may have pipelines running that nobody knows about
- Underestimating dead pipelines — often 20-40% of inventory is dead; retirement is high-leverage work