English | 2021 | ISBN: 9781098107857 | 82 pages | PDF,EPUB | 3.24 MB
To gain deeper and richer insights, your organization needs to analyze relevant data from all sources.
That requires moving data easily between your data lake and purpose-built data warehouses. But as these data stores grow, the data they hold only becomes harder to move. This practical book shows you how to overcome this data gravity issue with a new modern data lake house architecture.
Authors Changbin Gong and Raghavarao Sodabathina, solutions architects at Web Services, show you how to connect your data lake, data warehouse, and other purpose-built services into a coherent whole. With this guide, cloud architects and intermediate and senior developers will learn how an AWS data lake provides a single place where you can run analytics across most of your data.
Understand key concepts and components of the AWS data lake house architecture
Get practical guidance for building your data lake house architecture in cloud environments
Define data strategy for both structure and unstructured data
Build efficient data lake house architecture based on your specific requirements
Learn how to gain data insights quickly and at scale
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