Cases / Financial services
An enterprise data warehouse for capital markets, delivered in 12 months
Requirements, business data model, build and hyper-care for capital markets and investment management at a large Danish financial institution.
- Sector
- Financial services
- Duration
- 12 months
- Our role
- Business data modelling, data-warehouse architecture and development
The challenge
Capital markets and investment management at a large Danish financial institution needed an enterprise data warehouse: one modelled, trusted foundation for reporting and analysis across the business area.
What we built
We ran the project end to end over 12 months: requirements analysis, business data modelling, implementation and hyper-care after go-live.
- Business data model as the backbone of the warehouse.
- Automation. A data-warehouse automation framework sped up development and maintenance.
- Microsoft BI stack. SQL Server, SSIS for loading, SSAS for analysis models, SSRS for reporting, Master Data Services for master data, and C#.
The warehouse did not stay a project. It was later extended to new business areas and became the enterprise data warehouse.
How we would build it today
The principles hold: start from the business data model, automate the repetitive work, manage master data deliberately. The platform would change. Today we would build the same model as a lakehouse on Azure Databricks or Microsoft Fabric, with the bronze, silver and gold layers as code, data products per business area, and Power BI on top. That also gives the data science team direct access to the same governed data for forecasting and risk models.