Data Hubs, Data Lakes and Data Warehouses

How They Are Different and Why They Are Better Together


Gartner says, “Data and analytics leaders are often unclear about the differences between data lakes, data warehouses and data hubs. Positioning them as competing approaches creates confusion.”

Ted Friedman, Distinguished VP Analyst and Nick Heudecker, VP Analyst at Gartner published a report which states: “Data warehouses and data lakes are structures supporting analytic workloads. Data hubs are different — their main focus is enabling data sharing and governance.”

Gartner further states, “As a result, data and analytics teams should think of data warehouses and data lakes as similar types of structures. Their primary purpose is to support analytics (albeit of different styles). In contrast, data and analytics leaders should think of data hubs as more operational structures, focused on enabling data sharing and governance.”

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Data Hubs, Data Lakes and Data Warehouses<br />

According to Gartner, “Without a clear understanding of the specific roles and capabilities of each structure type, data and analytics teams miss opportunities to provide the best support for specific business requirements”.

Gartner, Data Hubs, Data Lakes and Data Warehouses: How They Are Different and Why They Are Better Together, Ted Friedman and Nick Heudecker, 13 February 2020.

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