Data Migration Services
Data warehouse migration services — SQL Server to Databricks, Oracle to Snowflake, and legacy ETL re-platforming. We validate every row and leave you with a clean, modern platform.
Migration Paths We Deliver
We have delivered SQL Server to Databricks migration, Oracle to Snowflake, and Teradata modernisation projects for UK and international clients.
SQL Server to Databricks migration is one of our most common engagements. We migrate T-SQL stored procedures, SSIS packages, and SQL Agent jobs to dbt models, Delta Live Tables, and Databricks Workflows. SQL Server to Snowflake migrations follow a similar pattern using dbt as the transformation layer.
Oracle migrations involve converting PL/SQL stored procedures, Oracle-specific syntax, and complex partition strategies to cloud-native equivalents. We handle the dialect differences and re-architect where the original design was constrained by Oracle limitations.
Teradata migrations often involve large-scale re-architecture. We convert BTEQ scripts, FastLoad, and MultiLoad utilities to modern ELT patterns. Complex Teradata SQL dialects are re-written for Spark SQL or Snowflake SQL.
SSRS report migration to Power BI or Looker. We migrate the data models, rebuild the semantic layer in dbt or Power BI dataflows, and recreate reports with modern visualisations.
Stored Procedure to dbt Conversion
Migrate stored procedures to dbt — converting procedural SQL logic into modular, testable, version-controlled dbt models is one of our core specialisms.
The Problem with Stored Procedures
- No version control — changes are invisible
- No automated testing — failures are discovered in production
- No documentation — knowledge lives in people's heads
- No lineage — impossible to understand data flow
- Procedural logic is hard to optimise and refactor
The dbt Solution
- Git-versioned SQL models with full history
- Built-in testing framework catches failures early
- Auto-generated documentation and data dictionary
- Column-level lineage graphs across the entire project
- Declarative SQL that is easy to review and optimise
Validation Methodology
We validate every row. Our migration validation framework ensures the new platform produces identical results to the legacy system before cutover.
Row Count Reconciliation
Exact row counts matched across source and target for every table in every period.
Aggregate Validation
SUM, COUNT, and key metric comparisons between legacy and new platform outputs.
Sample Row Comparison
Column-by-column comparison of sampled rows to catch data type and precision issues.
Business Logic Validation
End-to-end report output comparison — the reports that your business relies on must produce identical numbers.
Zero-Downtime Migration Approach
We migrate without disrupting your existing data operations. Legacy and new systems run in parallel until confidence is established.
Parallel Run Phase
New platform runs alongside legacy for an agreed validation period. Both are compared daily until all differences are resolved.
Phased Consumer Migration
Report consumers and downstream systems are migrated in phases — low-risk first, business-critical last.
Rollback Plan
Every migration engagement includes a documented rollback plan. Legacy system remains operational until formal sign-off.
Planning a data warehouse migration? Contact Us