Getting Started with Ethos Cataloger: A Practical Guide

Migrating to Ethos Cataloger: Checklist & Roadmap

Overview

A practical, phased migration plan to move from your current data catalog to Ethos Cataloger with minimal disruption and validated metadata integrity.

Phase 1 — Plan & Assess

1. Stakeholders: Identify owners for data, metadata, security, and operations.
2. Scope: Inventory data sources, schemas, glossaries, lineage, and integrations to migrate.
3. Current-state audit: Export counts and samples for tables, fields, tags, policies, and existing usage metrics.
4. Success criteria: Define KPIs (e.g., metadata coverage %, search precision, time-to-discovery).
5. Risk & rollback: List high-risk items and a rollback strategy.

Phase 2 — Prepare & Design

1. Mapping: Create field-to-field and taxonomy mappings between source catalog and Ethos Cataloger.
2. Data model: Design target metadata model (entities, attributes, relationships, business glossary).
3. Access controls: Map roles, groups, and policies; define onboarding and approval workflows.
4. Integration plan: Decide connectors, ingestion cadence, and transformation rules.
5. Test environment: Provision a sandbox instance and anonymize any sensitive samples.

Phase 3 — Extract & Transform

1. Extract: Export metadata (schemas, tags, lineage, ownership, glossary) using APIs or exports.
2. Normalize: Clean and normalize names, descriptions, and tag taxonomies per mapping.
3. Transform lineage: Convert lineage representations to Ethos-compatible formats.
4. Preserve IDs: Where possible keep stable identifiers or map old→new IDs for traceability.
5. Validation scripts: Create automated checks for completeness and format compliance.

Phase 4 — Load & Validate

1. Ingest: Load metadata into sandbox via Ethos Cataloger APIs or bulk import tools.
2. Smoke tests: Verify entities, fields, tags, lineage, and ownership appear correctly.
3. Quality checks: Run comparisons vs. exported baseline (counts, sample records, tag matches).
4. User acceptance: Have key users validate search, lineage, and glossary workflows.
5. Iterate: Fix mapping or transform logic; repeat until acceptance criteria met.

Phase 5 — Cutover & Sync

1. Cutover window: Schedule low-impact cutover with communication plan.
2. Final delta sync: Capture and migrate changes since the sandbox import.
3. Switch integrations: Point upstream data tools and BI platforms to Ethos Cataloger endpoints.
4. Monitor: Track KPIs and error logs closely for 1–2 weeks post-cutover.
5. Rollback plan: Execute only if predefined critical failures occur.

Phase 6 — Operate & Improve

1. Training: Run role-based training and provide quick-reference docs.
2. Governance: Establish ongoing metadata stewardship and change-management cadence.
3. Automation: Schedule regular scans/ingestions and automated quality checks.
4. Observability: Dashboards for metadata coverage, search usage, and contributor activity.
5. Roadmap: Capture feature gaps and plan phased enhancements (lineage depth, ML tagging).

Checklist (Quick)

• Stakeholders assigned
• Inventory exported (schemas, lineage, glossary)
• Field/taxonomy mapping completed
• Sandbox import successful with UAT signoff
• Final delta sync scheduled and tested
• Integrations switched and monitored
• Training and governance processes in place

Common Pitfalls & Mitigations

• Incomplete mappings → allocate SME time for taxonomy alignment.
• Missing lineage fidelity → prioritize critical pipelines for manual mapping.
• Access mismatches → test RBAC in sandbox before cutover.
• Overlooked downstream integrations → run discovery for all consumers.

Estimated Timeline (example)

• Plan & Assess: 2–3 weeks
• Prepare & Design: 2–4 weeks
• Extract & Transform: 2–6 weeks (depends on scale)
• Load & Validate: 1–3 weeks
• Cutover & Sync: 1 week
• Operate & Improve: ongoing

If you want, I can convert this into a project plan with milestones and task owners for your environment.