Abstract
This chapter introduces the motivation for looking into data architectures. It shares an overview about data architecture evolution transitioning from traditional data warehouses to big data and data lakes and their main characteristics, values, and challenges. It outlines industry requirements in a data-driven world that ultimately led to the concept of a Data Fabric.
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Notes
- 1.
See Reference [1] for more information on the evolution of data architectures.
- 2.
See Reference [2] for more information on RDBMS and SQL.
- 3.
See Reference [3] for more information on the data lakehouse architecture.
- 4.
See Reference [4] for more information on a data warehouse.
- 5.
See Reference [5] for more information on the Apache Hadoop project with further links to HDFS, MapReduce, and YARN.
- 6.
See Reference [6] for more information on data lake challenges.
- 7.
See Reference [7] for more information on data lakehouse and delta lake concepts.
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© 2023 The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature
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Hechler, E., Weihrauch, M., Wu, Y.(. (2023). Evolution of Data Architecture. In: Data Fabric and Data Mesh Approaches with AI. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-9253-2_1
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DOI: https://doi.org/10.1007/978-1-4842-9253-2_1
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Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-9252-5
Online ISBN: 978-1-4842-9253-2
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