For successful analytics & AI initiatives, your cloud data warehouses and cloud data lakes must work together in a cohesive data management architecture. There is no one-size-fits-all solution for data management architecture. Every data warehouse is unique; thus, every modernization plan is unique. There are, however, several architectural patterns for modernization that help to shift from data warehouse and data lake silos to cohesion and compatibility between data lakes and data warehouses.
Use these patterns individually, in combination, or as mix-and-match for multiple warehouses to develop a modernization plan and drive your analytics and AI projects:
- Data Warehousing Outside the Data Lake
- Data Warehousing Inside the Data Lake
- Data Warehousing in Front of the Data Lake
- Data Warehousing Inside & Outside the Data Lake
