Cloud Infra, Data & AI Platform
Data Platform Foundation
A foundation engagement that carries scattered data through ingestion and ETL into one governed data warehouse for reporting and analytics.
Data Platform Foundation brings data from separate source systems, through ingestion and ETL, into a data warehouse on Microsoft Fabric and Azure SQL Database under a single governance model, so reporting and analytics stop depending on which system's export someone happened to use. The engagement is scoped to the source systems and reporting needs in play, and lays the groundwork that later analytics or AI work can build on directly.
Work modules
- Source system review and ingestion designReview existing source systems and current reporting to identify where figures diverge and why, then design the ingestion and ETL flow that reconciles them, orchestrated in Azure Data Factory or in the pipelines of Microsoft Fabric.
- Governed data warehouse buildDesign and build the data warehouse on Microsoft Fabric, or on Azure Synapse Analytics and Azure SQL Database where the estate is already Azure native, including the ETL pipelines and a governance model applied from the start.
- Dashboards, reporting and handoverBuild the Microsoft Power BI dashboards and reporting on that model, published through the Power BI Service or through Power BI Report Server where the estate has to stay on-premises, validate them against real reporting needs, and hand over to the teams that will maintain it.
What you receive
- An ingestion design and ETL pipelines from each source system in scope
- A governed data warehouse built on Microsoft Fabric, or on Azure Synapse Analytics and Azure SQL Database where the estate is Azure native
- A validated data model reflecting the source systems in scope
- A set of Microsoft Power BI dashboards and reporting on that model
What changes for the business
- Reporting, analytics, and future AI work start from one consistent, governed data source