Part 7/11:

• Microservices for KPIs and Aggregations: Instead of monolithic queries susceptible to schema changes, KPIs are computed through independent microservices, often containerized (e.g., on Kubernetes). This separation allows scaling, parallel processing, and resilience.

• Reusable Components and Metadata Management: Centralized schema registries, CI/CD pipelines, and parameterized ETL components promote consistency and efficiency, enabling teams to accelerate development while maintaining governance.

Handling Growth and Scaling Challenges

As data volume and organizational complexity increase, the architecture must evolve:

• Scaling Pipelines: The design supports adding new data sources, KPIs, and products without disrupting existing flows.