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Data Lakehouse in Action

Data Lakehouse in Action

By : Pradeep Menon
4.2 (10)
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Data Lakehouse in Action

Data Lakehouse in Action

4.2 (10)
By: Pradeep Menon

Overview of this book

The Data Lakehouse architecture is a new paradigm that enables large-scale analytics. This book will guide you in developing data architecture in the right way to ensure your organization's success. The first part of the book discusses the different data architectural patterns used in the past and the need for a new architectural paradigm, as well as the drivers that have caused this change. It covers the principles that govern the target architecture, the components that form the Data Lakehouse architecture, and the rationale and need for those components. The second part deep dives into the different layers of Data Lakehouse. It covers various scenarios and components for data ingestion, storage, data processing, data serving, analytics, governance, and data security. The book's third part focuses on the practical implementation of the Data Lakehouse architecture in a cloud computing platform. It focuses on various ways to combine the Data Lakehouse pattern to realize macro-patterns, such as Data Mesh and Data Hub-Spoke, based on the organization's needs and maturity level. The frameworks introduced will be practical and organizations can readily benefit from their application. By the end of this book, you'll clearly understand how to implement the Data Lakehouse architecture pattern in a scalable, agile, and cost-effective manner.
Table of Contents (14 chapters)
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1
PART 1: Architectural Patterns for Analytics
4
PART 2: Data Lakehouse Component Deep Dive
10
PART 3: Implementing and Governing a Data Lakehouse

Summary

We have covered a lot of ground in this chapter. The data governance layer, one of the vital layers in the Data Lakehouse, was covered in depth. We started by emphasizing the importance of data governance. The 3-3-3 framework for data governance provides a holistic framework for looking into data governance in a structured manner. As part of the 3-3-3 framework, must-have objectives for data governance were covered. The section also covered the key roles that enable data governance and the critical aspects of data governance policies, and the characteristics of technologies that allow it.

The next section of the chapter focused on the three components of the data governance layer, that is, data governance policy management, the data cataloging service, and the data quality service. The section then drilled down into what each component means and how the parts come to fruition in the Data Lakehouse architecture.

The next chapter will focus on the final layer of the Data...

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Data Lakehouse in Action
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