Part 10/13:

The discussion acknowledged the tendency for data architecture to grow overly complex, especially with incremental data modeling and layering. To prevent this, data engineers are encouraged to maintain a simple, clear architecture with well-defined metadata. Proper metadata management—covering source details, technological stack, costs, and data lineage—empowers teams to discover data efficiently, manage changes, and optimize resource allocation.

Collaboration Across Teams and Stakeholders

Effective communication and collaboration are critical to ensure data quality, security, and alignment with business goals. Including stakeholders in alert systems, sharing insights, and establishing feedback loops enhances transparency and shared understanding.