Practice · Data & Databricks

SAS to Databricks migration

SAS to Databricks migration is the move of analytics, data-processing and reporting workloads off the SAS platform and onto the Databricks Lakehouse — translating SAS programs, macros and jobs into Spark SQL, Python and Databricks-native pipelines, migrating the data, and proving the results match before the old system is retired.

Strategys supplies the senior consultants who do this work — as a project team or embedded specialists — for organisations that cannot afford to get the numbers wrong.

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Who it's for

Built for the heaviest SAS estates in the Nordics

The organisations with the most SAS to migrate are those where analytics has run the business for years — financial services and the public sector. They share the same constraint: the numbers feed regulated reporting, so the migration has to be exact.

  • Banks

    Retail and corporate banks running risk, regulatory reporting, fraud and analytics on large SAS estates that now sit under DORA operational-resilience scrutiny.

  • Insurers

    Life, P&C and health insurers with actuarial, pricing and reserving models built in SAS that need a modern, governed platform without breaking the numbers.

  • Public sector

    Agencies and institutions with long-standing SAS analytics and statistical reporting looking to modernise on open, auditable foundations.

How we work

A phased migration that keeps the numbers safe

We migrate in waves, not big-bang. Each phase is deliberately small and reversible, so regulated reporting keeps running throughout and the risk of any single cut-over stays contained.

  1. Assess and inventory

    Catalogue the SAS estate — programs, macros, stored processes, scheduled jobs, data sources and downstream consumers — and map dependencies so nothing is migrated blind.

  2. Prioritise and design the target

    Agree a target architecture on the Databricks Lakehouse, group workloads into migration waves by risk and value, and decide where to re-engineer versus translate like-for-like.

  3. Convert and re-engineer

    Translate SAS logic — DATA steps, PROC steps and macros — into Spark SQL, Python and Databricks-native patterns, modernising where it pays rather than a blind lift-and-shift.

  4. Validate in parallel

    Run the legacy and new pipelines side by side and reconcile outputs so regulatory, actuarial and financial figures are proven equivalent before anyone relies on them.

  5. Cut over and enable

    Retire the migrated SAS workloads, hand over governance and documentation, and upskill your team so the platform is owned in-house, not left dependent on us.

Experience

Senior consultants, not a training ground

Every consultant we place on a migration is a senior specialist with hands-on data-engineering and Databricks experience. We work across financial services, life sciences, the public sector and manufacturing, with senior specialists who bring both Danish and international experience.

FAQ

SAS to Databricks migration — questions we get

What is a SAS to Databricks migration?

It is the move of analytics, data-processing and reporting workloads off the SAS platform and onto the Databricks Lakehouse. In practice it means translating SAS programs, macros and jobs into Spark SQL, Python and Databricks-native pipelines, migrating the underlying data, and validating that the new outputs match the old before the legacy system is retired.

Why are banks and insurers moving from SAS to Databricks?

Financial-services firms hold some of the heaviest SAS estates in the Nordics, and they are consolidating analytics onto open, cloud-native platforms to lower cost, unlock AI and machine learning on the same data, and meet governance and operational-resilience expectations such as the EU DORA regulation. Databricks gives them one governed platform for data engineering, analytics and AI.

Do you rewrite the SAS code or lift and shift it?

It depends on the workload. We translate SAS logic into Databricks-native patterns, and where a program is business-critical or overdue for a rework we re-engineer it rather than carry old constraints forward. Low-risk, stable jobs can be converted more directly. The choice is made per workload during the assessment.

How do you avoid breaking regulatory or actuarial reporting during a migration?

We run the legacy SAS pipeline and the new Databricks pipeline in parallel and reconcile their outputs, so figures that feed regulatory, actuarial or financial reporting are proven equivalent before the old system is switched off. Migrating in waves keeps each cut-over small and reversible.

Can Strategys work as embedded specialists or as a full project team?

Both. We supply senior consultants either as embedded specialists who join your team, or as a project team that owns delivery end to end. Engagements can be hourly staff augmentation or fixed project delivery, depending on what suits your organisation.

Which regions and languages do you cover?

We are based in Copenhagen and deliver across Denmark and the Nordics, working in Danish, English, Arabic, Urdu and other European languages. We support international and cross-border programmes as well as local Danish engagements.

Planning a SAS to Databricks migration?

Tell us about your estate and the reporting it feeds. We will talk you through how a phased, validated migration would work for your organisation.

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