Modernize your data platform without stopping the business

The usual failure is scope. A team commits to a full replatform, disappears for nine months, and re-emerges with something that handles the easy 80% of cases and none of the exceptions the business actually cares about. Meanwhile the legacy platform kept changing, so the two have drifted and the cutover keeps slipping.

The alternative is to migrate in vertical slices. Pick one domain, take it all the way through to a consumer someone uses daily, and run it beside the old pipeline until the numbers reconcile. You get a working reference implementation in weeks, every subsequent domain is cheaper than the last, and there is never a single terrifying cutover weekend.

It also front-loads the unpleasant discoveries. The undocumented business logic buried in a stored procedure, the source that silently changed its timezone convention in 2021 — these surface in week four on one domain, not in month eight across all of them.

A cloud warehouse like Snowflake or BigQuery is excellent at what it does: fast, governed SQL over structured data with almost no operational burden. It gets expensive when you push large-scale ML, streaming or unstructured data through it, because you are paying warehouse prices for workloads that don't need warehouse guarantees.

A lakehouse keeps data in open formats on cheap object storage and layers ACID transactions on top, so the same tables serve SQL engines and ML frameworks alike. The trade is operational: you own more of the stack, and skipping governance produces a data swamp rather than a lakehouse.

Most organizations land somewhere in between, and the right split depends on your workload mix, team size and existing commitments rather than on which architecture is fashionable. We'll tell you plainly if your warehouse is fine and the real problem is that nothing is tested.

We don't recommend a rewrite when the platform is structurally sound and the actual problem is missing tests, absent lineage or an unowned pipeline. Those are cheaper problems, and it's not in your interest to solve them with a migration.

We also don't leave you dependent on us. Every engagement is built around handover — your team pairs with ours throughout, the documentation is written as the work happens rather than assembled at the end, and success means your engineers ship faster after we've gone.