Abstract
This chapter walks through several use cases for implementing a Data Fabric and Data Mesh that also represent business-relevant entry points. Data governance and privacy initiatives are ongoing in almost every organization, enabling access to enterprise data and AI artefacts across platforms to the people who have a business need. Other use cases are driven by hybrid cloud data integration; the need for a comprehensive view on customers, vendors, and other parties for better business outcome; and development and integration of trustworthy AI into business processes.
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Notes
- 1.
We prefer to use the term knowledge catalog, because it does justice to the broad AI-related artefacts that go far beyond just traditional data.
- 2.
See Reference [1] for more information on GDPR.
- 3.
See Reference [2] for a comprehensive treatment on data governance.
- 4.
See Reference [3] for an example on the impact of implementing data governance.
- 5.
Please, refer to chapter 15 on Data Governance in the Context of Data Fabric and Data Mesh for more details.
- 6.
See Reference [4] for an introduction into IBM zSystems.
- 7.
See Reference [5] for more information on a hybrid cloud.
- 8.
See Reference [6] for more information on gaining analytical insights using the cloud.
- 9.
We elaborate further on the role of a Data Fabric in a hybrid cloud landscape in Chapter 12.
- 10.
See Chapter 9 for more details.
- 11.
See Reference [7] for the McKinsey survey.
- 12.
We elaborate more on this topic in Chapter 8.
- 13.
In Chapter 8, we provide some examples.
- 14.
See Reference [8] for the IBM IBV survey.
- 15.
See Reference [9] for more information on trustworthy AI.
- 16.
See more on MLOps in Chapter 9.
- 17.
Please, see the section on trustworthy AI in Chapter 5 for more details.
- 18.
See Reference [10] for more information on trustworthy AI and ethics in AI.
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Hechler, E., Weihrauch, M., Wu, Y.(. (2023). Data Fabric and Data Mesh Use Case Scenarios. In: Data Fabric and Data Mesh Approaches with AI. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-9253-2_3
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DOI: https://doi.org/10.1007/978-1-4842-9253-2_3
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