The workflow before
A Core's analytics ran on a single data source. Adding more sources and giving each client a view of only its own data was not possible with the existing setup. The team wanted to fix this once, without building technical debt it would have to pay down later.
What we built
We built an Azure data lake designed around the five pillars of the Azure Well-Architected Framework: operational excellence, security, reliability, performance and cost.
The pipeline carries a security pattern that segregates data by client, enforced through Entra ID, so each client's access is scoped to its own records.
A Power BI engineer built per-client dashboards on the secure layer, and we brought two additional data sources into the analytics.
Before and after
| Measure | Before | After |
|---|---|---|
| Data sources in analytics | 1 | 3 |
| Client data access | No per-client segregation | Each client sees only its own data |
| Adding a new source | Rework of the pipeline | Added without refactoring |
What's next
With client data segregated and governed, A Core can add a Level 2 assistant that answers each client's questions from that client's data only.
