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Data Hubs, Data Lakes and Data Warehouses: How They Differ and Are Used in Supply Chain

Many supply chain technology leaders think of data hubs, data lakes and data warehouses as interchangeable. In reality, each of these architectural patterns has a different primary purpose. When they are combined or sequenced, they can support complex, diverse and distributed supply chains.

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Many supply chain technology leaders think of data hubs, data lakes and data warehouses as interchangeable. In reality, each of these architectural patterns has a different primary purpose. When they are combined or sequenced, they can support complex, diverse and distributed supply chains.

Read the Gartner report and learn recommendations to: 

  • Maximize your ability to support a broader range of diverse use cases by identifying the ways that these structures can be used in combination.  
  • Distinguish between these structures by recognizing their differences in focus.  
  • Eliminate confusion and ensure alignment of approach with business requirements by communicating the characteristics and common use cases for each of these structures to your supply chain stakeholders. 
Peek inside
Gartner, Predicts 2022: Analytics, BI and Data Science Ecosystems Drive New Perspectives, Peter Krensky, Rita Sallam, Farhan Choudhary, Julian Sun, David Pidsley, Carlie Idoine, Gareth Herschel, Soyeb Barot, Erick Brethenoux, Donald Feinberg, Andrew White, 9 December 2021

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and is used herein with permission. All rights reserved.
Gartner, Data Hubs, Data Lakes and Data Warehouses: How They Differ and Are Used in Supply Chain, Christian Titze, Noha Tohamy, 19 October 2021

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and is used herein with permission. All rights reserved.