Years of disorganized on-prem customer data restructured into clean, Salesforce-ready records — so the move fixed the problem instead of relocating it.
Six moves took years of inconsistent customer data from on-prem SQL into Salesforce — most of the work happening before anything touched the new platform. Follow the pipe.
Scroll to run the migrationThe on-prem system did what it was built to do — what it didn’t do was hold data in a shape that could move into Salesforce. Records were inconsistent, formatting varied across years of manual entry, and none of it was structured the way Salesforce expects.
The legacy system held what it needed. Salesforce expects something else entirely.
The decision to migrate had been made, but the data itself wasn’t ready. Moving it as-is would have rebuilt the same mess inside a new system — this time inside the platform the business was counting on to fix it.
A straight transfer carries every defect across. New platform, same problems.
Data was extracted directly from the legacy on-prem SQL systems — a stable source to reason about rather than a moving target, and the first step in a sequence where nothing reached Salesforce untested.
A stable source to reason about — nothing reaches Salesforce untested.
Data models were designed against Salesforce’s object and field architecture, so every variation in the source data had one defined destination — including the fields Salesforce required that the legacy system never captured.
Every variation in the source has one defined destination in Salesforce.
Transformation logic was built in code to clean and reshape the data at scale: erroneous records removed, inconsistent text standardized, required fields derived, and every source variation mapped to the right place in Salesforce.
What most migrations underestimate — and what separates one that sticks from one that moves the problem.
Integration ran through Salesforce APIs for controlled, repeatable loads, orchestrated by pipelines that managed and sequenced the whole migration flow — the same pipeline the business can re-run for future loads.
A migration structure that produces a consistent result every time it runs.
We engaged Dataracity to lead the design and recommendation phase of one of our client's enterprise data architecture projects on the Microsoft platform. From the outset their expertise was evident — they introduced us to Microsoft Fabric and provided a robust framework rooted in industry best practices. Beyond high-level strategy, they delivered tangible assets including detailed system architecture diagrams, data flow charts, and comprehensive price modeling. Their technical execution is just as impressive as their strategic planning. I highly recommend Dataracity for any organisation looking to modernise their data stack with precision and clarity.
Shelly JantzenFounder · E2 ConsultingA small delivery team, named and accountable from kickoff to go-live.
Luke Matthews
Co-Founder, Head of Project Delivery & Data Architecture
Amanda Buthelezi
Co-Founder, Project Lead (BI & Data Strategy)
Estella Doulis
Business Intelligence Consultant
Bring us your source systems and your target platform. We'll map the data models, the transformation work, and the load sequence in one conversation.
