Data Platform Migration: The CTO's Pre-Flight Checklist

Every data platform migration looks straightforward on a slide deck. “We’ll move from Oracle to Snowflake in Q2.” Then reality hits: data quality issues surface, downstream pipelines break, and the migration timeline doubles.

The difference between migrations that succeed and those that become multi-quarter nightmares is preparation. Here’s the checklist we use with every client before writing a single line of migration code.

The Pre-Flight Checklist

1. Data Quality Baseline

Before you migrate, know what you have. Run profiling against your current platform to establish a quality baseline. Document null rates, cardinality, distribution patterns, and known anomalies. If you don’t know what “correct” looks like in the old system, you can’t validate the new one.

Action: Run automated data profiling tools (Great Expectations, dbt tests, or custom queries) against your top 20 most critical tables. Document the results.

2. Downstream Dependency Map

Every pipeline, report, and application consuming your data needs to be cataloged. This is where most migrations fail — not in moving the data, but in breaking the things that depend on it.

Action: Create a complete dependency graph. For each table being migrated, document every consumer: dashboards, applications, ML models, exports, and manual queries.

3. Data Governance & Compliance Audit

Does your target platform meet your regulatory requirements? Consider data residency (where will the data physically reside), encryption requirements, access control models, and audit trail capabilities.

Action: Map your compliance requirements (PIPEDA, SOC 2, HIPAA, etc.) to the specific features of your target platform. Identify gaps early.

4. Schema & Data Model Assessment

Don’t lift-and-shift a bad data model. Migration is your opportunity to fix years of accumulated schema debt. But you need to decide which changes happen during migration vs. post-migration.

Action: Classify each schema change as “migrate as-is,” “migrate and transform,” or “redesign post-migration.” The more transformations you include during migration, the higher the risk.

5. Performance Baseline & Benchmarks

Establish concrete performance benchmarks before migration. What are your current query response times for critical reports? What’s the acceptable SLA? If the new platform is slower for key workloads, you have a problem even if the migration is technically successful.

Action: Identify your top 25 most critical queries and benchmark them. These become your acceptance criteria for the new platform.

6. Rollback Strategy

What happens if the migration fails? You need a documented, tested rollback plan that can restore service within your RTO (Recovery Time Objective). “We’ll figure it out” is not a rollback plan.

Action: Define rollback triggers (what constitutes a failed migration), rollback procedure (step-by-step), and rollback timeline (how long does it take).

7. Dual-Write Period Planning

For critical systems, plan a dual-write period where data flows to both old and new platforms simultaneously. This gives you a safety net and allows consumers to migrate gradually rather than in a big-bang cutover.

Action: Design your dual-write architecture. Determine which system is the source of truth during the transition. Plan for reconciliation between systems.

8. Team Readiness & Training

Your team needs to operate the new platform on day one. Don’t wait until post-migration to train people. Start training on the target platform in parallel with migration planning.

Action: Identify skill gaps between current and target platforms. Create a training plan that runs in parallel with migration prep.

The Biggest Mistake

The biggest mistake in data platform migrations isn’t technical — it’s scope creep. Teams try to fix every data problem during migration, turning a focused infrastructure move into a multi-quarter data transformation initiative.

Keep migration and transformation separate. Migrate first (as cleanly as possible), then iterate on the new platform. This reduces risk dramatically and keeps timelines realistic.

Planning a data platform migration? Our Data Platform Migration Strategy engagement provides the complete pre-flight assessment — risk analysis, rollback planning, and a phased migration roadmap. Let’s discuss your migration.