Data migration

Data migration

Data migration services for the move you've been putting off: warehouse, database, and cloud migration onto a governed foundation, reconciled to the row.

Overview

Moved. Proven. Kept.

Our data migration services move your data from wherever it lives, legacy databases, on-premise warehouses, SaaS platforms, spreadsheets, into a governed cloud data foundation, with every row reconciled against its source before anything is switched off. Migration, staging, validation, cutover, and the support afterwards, from one team.

Data migration has a deserved reputation as the project nobody wants. It runs long, it surfaces every data quality sin of the last decade, and the vendor who quoted it is rarely the one explaining the missing records at the end. The reason is usually the same: the migration was treated as a copying exercise. Copy the mess and you keep the mess, with a bigger bill.

We treat migration as a foundation move. The data lands in a medallion architecture, bronze as it arrived, silver cleaned and conformed, gold ready for the business, so the migration that starts as a systems chore ends as the platform your reporting and AI run on. Same effort, twice the return.

What you get

What our migration services cover

Warehouse and database migration

Legacy warehouses and databases moved to Snowflake, Databricks, BigQuery, or Fabric, restructured for the platform rather than pasted into it.

Cloud data migration

On-premise to cloud, or cloud to cloud when the first choice stopped fitting. Costs modelled before you commit, not discovered after.

Legacy system retirement

The systems you're paying to keep alive purely for their history: data extracted, archived queryably, licences finally cancelled.

Pipelines and models

The ETL jobs, reports, and ML models around your data rebuilt on the new platform, so cutover day doesn't orphan them. See the data foundation.

Proof

Proof it works

It was always a manual, non-automated process. As soon as the button's pushed, that data's out of date.

Jason Southwell, CEO, Smarter Services, on life before the move
Read the Smarter Services case study

7 systems

migrated and unified into one governed cloud platform at Smarter Services.

14 weeks

from kick-off to live, including the migration, the model, and the dashboard on top.

1.5 days a week

returned to the team once the manual export ritual ended.

Method

How a migration runs

  1. Audit and map

    Every source, table, and owner mapped before anything moves. This is where the surprises live, and we'd rather meet them in week one than week ten.

  2. Strategy before movement

    Phased or parallel-run, what moves first, what gets cleaned in transit, and what gets left behind on purpose. In writing, with a rollback path.

  3. Stage and clean

    Data lands in the bronze layer exactly as it arrived, then is cleaned and conformed into silver. Nothing is altered without a record of what changed.

  4. Reconcile and prove

    Counts, checksums, and line-level comparison against the source. You get the reconciliation report; your auditors will like it more than you expect.

  5. Cut over and stay

    The switch happens when the data is proven, not when the calendar says so. And we stick around past cutover, so the new platform beds in properly.

Strategy

A data migration strategy that survives contact

Most migration horror stories start with a plan that only covered the happy path. A working data migration strategy answers the awkward questions before they're urgent: what happens to the records that fail validation, who owns the sign-off per domain, how long the parallel run lasts, and what triggers a rollback.

Our default is phased migration with a parallel run. One business domain moves at a time, the old and new systems run side by side, and each domain is reconciled and signed off before the next begins. It takes marginally longer than the big-bang weekend, and it removes the mode of failure where everything is broken at once and the old system is already gone.

The strategy also decides what not to migrate. A decade of dead columns, duplicate customers, and abandoned test records doesn't deserve a seat on the plane. Deciding that deliberately, with the business in the room, is cheaper than paying to move data nobody will ever query and then paying again to govern it.

Phased data migration strategy diagram showing the old platform and new governed foundation running in parallel while domains move one at a time, each reconciled, with cutover only when the data is proven
A phased migration: both platforms run in parallel, each domain is reconciled before the next moves, and cutover waits for proof.
The destination

Cloud migration that leaves you AI-ready

A lift and shift moves your data estate to the cloud and changes nothing else: the same silos, the same disagreeing numbers, now on rented hardware. It's the most common form of cloud migration, and the most commonly regretted.

Migrating onto a governed foundation costs similar effort and leaves you somewhere better. The warehouse, the medallion layers, and a semantic layer with one definition of your business go in as part of the move, which means the migration project quietly becomes the platform your dashboards, forecasts, and AI tools run on. Every build we do, from forecasting to conversational AI, stands on this same foundation, so nothing has to be rebuilt when you're ready for what's next.

If you're comparing data migration consultants, ask each one what the data looks like the day after cutover. If the answer is "the same as before, but in the cloud", you're buying a removal van. Our data consultancy exists to make the answer "better than it went in".

FAQ

Questions we hear most

What do data migration services include?

Everything between the system you have and the system you want: auditing and mapping the source data, designing the migration strategy, staging and cleaning the data in transit, reconciling every row against the source, cutting over, and supporting the new platform afterwards. At Shipshape Data the destination is a governed cloud foundation, not a copy of the old mess in a new place.

Should we migrate in one go or in phases?

Phased, almost always. A big-bang migration bets the business on one weekend; a phased data migration strategy moves one domain at a time, proves each one against the source, and keeps a rollback path open. The exception is small, simple estates where the overhead of phasing outweighs the risk it removes. We'll tell you which yours is.

Will there be downtime?

Cutover downtime depends on how long your systems can run in parallel. Where source and target can run side by side, migrations land with no user-facing downtime: the switch happens after the data is proven. Where a hard cutover is unavoidable, we schedule it, rehearse it, and time-box it in writing first.

How do you make sure no data is lost?

Reconciliation, not reassurance. Every migrated table is counted, checksummed, and compared against its source, and the differences are explained line by line before anything is switched off. The reconciliation report is a deliverable you keep, which also keeps your auditors happy.

Which platforms do you migrate to?

Snowflake, Databricks, Google BigQuery, and Microsoft Fabric, with dbt and Fivetran in the pipeline layer. Sources can be almost anything: legacy databases, on-premise warehouses, SaaS platforms, spreadsheets, or another cloud. We recommend the target that fits your estate; we don't resell licences.

What does a data migration cost?

It depends on the volume, the number of sources, and the state of the data, so we scope before we price and put the number in writing. Migration is usually delivered as the first phase of a foundation build, which is why our engagements are priced as fixed, scoped outcomes rather than open-ended day rates.

The best time to plan a migration is before the old platform's renewal date starts making decisions for you. Talk to us and we'll tell you plainly what a clean move would take, and what it depends on.

Next steps

What happens when you get in touch

  1. You tell us what's moving

    The systems, roughly how much data, and what's driving the move. A few lines through the form is plenty; we reply personally, usually within one working day.

  2. A scoping conversation

    Thirty minutes on your sources, your target, and your constraints. No deck, no pitch.

  3. A straight answer

    The migration strategy we'd recommend, the phasing, the timeline, and the cost, in writing.

Not ready to talk yet? The Smarter Services case study covers a seven-system migration end to end, including the parts that were hard.

Start at your core.

Tell us where your data is today and what you want AI to do. We'll come back with a straight answer on what your foundation needs and where the quickest real win is.

Talk to us