Databricks migration and modernisation — UK

That may be possible for a small, well-understood scope, but it should not be the default assumption. Group workloads by dependencies and business risk. A representative pilot can expose data, performance and access issues before a broader cutover, while a phased plan preserves a clearer route to investigation and rollback.

Use representative workload runs and include the full operating picture: compute, storage, licences, engineering and support effort. Compare equivalent outputs and service expectations. A short test or a discounted environment can be misleading, so record assumptions and validate them before treating a projected saving as a realised result.

A platform change does not resolve inconsistent definitions, missing ownership or unreliable source records on its own. Assess the current problem and the intended workloads first. Some organisations need a better pipeline or operating process; others need a different architecture. The recommendation should connect each proposed change to an observed limitation and an agreed acceptance measure.

The estimate depends on sources, access methods, transformations, history, freshness, governance and operational expectations. Representative samples help expose complexity that a list of system names cannot show. Separate initial delivery from recurring compute, licences and support. A bounded discovery or representative workload can establish a more useful scope before a wider implementation commitment.

Agree reconciliation rules with the people who own the business meaning. Compare representative records, totals and exceptional cases against authoritative sources, and document acceptable differences. Technical success signals are useful but insufficient: a job can finish successfully while applying the wrong definition. Acceptance should cover both processing behaviour and the decisions the information is intended to support.

Map who may view, change and approve information across sources, processing, models and reports. Test the actual access paths, including service accounts, exports and derived datasets. A permission applied in one layer does not automatically protect every copy. The design should make ownership and review responsibilities clear without assuming that a platform setting provides complete governance.

The handover should match your team’s responsibilities and skills. Include source and transformation documentation, access ownership, failure investigation, recovery and change procedures. Where ongoing support is required, agree its scope and service expectations separately. A useful acceptance exercise is to have the nominated operator investigate a representative failure using the supplied documentation and agreed access.

Describe the business question, source systems, current refresh process and the decisions delayed by poor information. Approximate scale and known exceptions help, but confidential datasets are not needed in a website enquiry. Start with a synthetic or approved sample and agree secure access only after the purpose, scope and responsible owners are clear.