ETL and orchestration
SSIS, Azure Data Factory, Fabric pipelines and dbt. Incremental loads, sane error handling, and jobs that tell you when they fail instead of failing silently.
SERVICE
Pipelines, models and warehouses built by people who have been doing it since before it was called data engineering.
CAPABILITIES
SSIS, Azure Data Factory, Fabric pipelines and dbt. Incremental loads, sane error handling, and jobs that tell you when they fail instead of failing silently.
Star schemas, slowly changing dimensions, conformed dimensions across business areas. The difference between a warehouse and a pile of tables.
Azure SQL, Synapse, Fabric lakehouse and warehouse. Designed around how the business asks questions, not around how the source systems happen to store rows.
On-premise SQL Server and SSIS estates into Azure or Fabric, without the big-bang cutover that keeps everyone awake.
Automated checks that compare your reporting layer against the systems of record, so drift is caught by a job rather than by an angry controller.
Power BI, SSRS and paginated reporting, with a governed model underneath so self-service does not turn into fifty conflicting versions of revenue.
A POSITION WE HOLD
A surprising amount of analytics work is really reconciliation work. Payroll says one thing, the invoicing system says another, and the dashboard quietly picks one.
We do not average discrepancies away or footnote them. We trace them, explain the cause, and tell you which number is correct and why — even when the answer is awkward.
It is slower. It is also the only version of this work worth paying for.
That is usually a modelling problem, and it is usually fixable. Email sales@prodigym.org or start below.