Many data and analytics leaders think of data hubs, data lakes and data warehouses as interchangeable alternatives. In reality, each of these architectural patterns has a different primary purpose. When they are combined, they can support increasingly complex, diverse and distributed workloads.
- Distinguish Between Data Warehouses, Data Lakes and Data Hubs, and Recognize How They Differ in Focus
- Communicate the Characteristics and Common Use Cases for Each of These Structures
- Maximize Your Ability to Support a Broader Range of Diverse Use Cases Through Combinations of These Structures
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