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Data Migrations

We move data platforms and analytics workloads to modern cloud environments with minimal downtime, validated results, and careful coordination across every team downstream. A migration is judged by what did not break.

When to bring us in

The problems this solves

The clock is running

A legacy platform’s costs, contract renewal, or end of support is forcing a decision on your schedule or theirs.

Key-person risk

One administrator understands how everything works, and that is the whole disaster recovery plan.

The stalled attempt

A previous migration got 80 percent done and stopped at the hard part, and now you have two platforms.

No room for downtime

Reporting cannot go dark, not even for a weekend, and the board meets on Monday.

How it fits together

Old and new run side by side until the numbers match

We build the new platform alongside the old one, validate outputs line by line, and cut over when the evidence says so. Cutover becomes an event you schedule, not a risk you absorb.

Diagram of a phased data platform migration across two tracks. The legacy platform track runs then fades out after cutover. The modern platform track builds up, overlaps with the legacy system during a parallel run with automated parity validation, then continues as the system of record. A marker labels the scheduled cutover point, followed by decommissioning of the legacy platform.

The legacy platform winds down as the modern one comes up, with an overlapping parallel run where automated parity checks compare outputs before cutover.
What’s included

What our migration services include

Planning is most of the risk management. The build is engineering; the confidence comes from validation.

  • Migration assessment: inventory, dependencies, and effort ranking
  • Platform selection guidance without a vendor-lock bias
  • Pipeline re-platforming, including legacy ETL to modern ELT
  • Logic translation into version-controlled, tested data models
  • Parallel runs with automated parity validation, line by line
  • Cutover planning, communications, and rollback paths
  • Downstream repointing: dashboards, extracts, and integrations
  • Legacy decommissioning and cost wind-down
Our approach

How we work

01

Assess

Inventory what exists, what is used, and what can be retired instead of moved. Usually a lot can.

02

Build alongside

The new platform comes up next to the old one. Nothing is torn down to make room.

03

Validate in parallel

Automated checks compare old and new outputs until the differences are zero or explained.

04

Cut over & decommission

A scheduled event with a rollback path, then the legacy costs actually stop.

Outcomes

70%

reduction in data ingestion costs after migrating an enterprise customer’s pipeline infrastructure to Airbyte

Migrations should pay for themselves. This one started to before the legacy contract even ended.

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Questions we hear

Frequently asked questions

How do you avoid downtime?

By never needing a hard switch. Old and new run in parallel, outputs are validated continuously, and cutover happens per domain on a schedule with a rollback path. Reporting stays live throughout.

Lift-and-shift or rebuild?

Usually neither extreme. We translate high-value logic into tested, version-controlled models where it pays off, and move simpler workloads directly. A migration is also the cheapest moment to retire what nobody uses.

How long does a data platform migration take?

It depends on the inventory, which is why we assess first and return a ranked plan in weeks. We sequence by domain, so value lands progressively rather than at the end of a long program.

What happens to the old platform?

It runs in parallel until parity is proven, then gets decommissioned deliberately, contracts, compute, and all. The wind-down is planned from day one, because that is where the savings actually live.

A migration you can schedule, not fear

Tell us what you are running and what is forcing the move. We will give you an honest read on effort, sequence, and what can simply be retired.

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