The original title is "Designing Enterprise Data Architecture: Lessons Beyond ETL"

Short summary

Enterprise data architecture succeeds by managing complexity through layered design, standardized patterns, and flexibility where needed. Best practices include separating concerns across ingestion, validation, transformation, storage, governance, and reporting layers. Design for scalability by anticipating growth, new integrations, and organizational changes.

• •Layer data platform architecture to separate concerns and reduce maintenance burden
• •Standardize common patterns while allowing flexibility for differences across vendors and APIs
• •Design for future scalability by anticipating growth, AI integration, and organizational evolution

Generated with AI, which can make mistakes.