Fabric changed what a data platform costs to run and what it costs to get wrong. Most of the difference is decided in the first fortnight - in how the Lakehouse is laid out, how loads are parameterised, and whether capacity is sized against real workloads or a guess.
We build Fabric and Azure data platforms at enterprise capacity, and we have taken a live production platform from Synapse to Fabric Lakehouse without stopping the business reporting on it. Where an estate should stay on Synapse or Azure SQL, we will say so rather than sell a migration.
What this includes
- Microsoft Fabric - Lakehouse, Warehouse, EventHouse and OneLake
- Azure Synapse Analytics, Azure SQL Database and SQL Server managed instance
- ETL and ELT with Fabric Dataflow, PySpark, Azure Data Factory and SSIS
- Azure Data Lake (ADLS) storage design and structure
- Synapse-to-Fabric migration of live platforms
- Configuration-driven dynamic loads, so new sources are onboarded by config rather than code
- Integration runtimes, on-premises gateways and refresh scheduling
- Power Apps, Power Automate and Logic Apps where a process needs a front end
- Security, access control and capacity cost management
What you end up with: A platform that loads on schedule, stays inside its capacity budget, and onboards the next data source in a day instead of a sprint.
Every engagement includes detailed documentation of our findings, and all source code and artefacts for any bespoke product - documented for your teams to maintain and understand. We maintain a strict level of confidentiality throughout.