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  • Book Overview & Buying Data Lakehouse in Action
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Data Lakehouse in Action

Data Lakehouse in Action

By : Pradeep Menon
4.1 (9)
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Data Lakehouse in Action

Data Lakehouse in Action

4.1 (9)
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

Chapter 6: Applying Data Governance in the Data Lakehouse

The journey so far has covered five layers of Data Lakehouse. This chapter will focus on the final two layers, that is, data governance and data security layers. Data governance and security is an essential aspect of the modern data analytics platform. We will start this chapter by discussing the need for a data governance framework and how the 3-3-3 framework outlines the three components of data governance. The next section of the chapter will discuss implementing the data governance components in the Data Lakehouse. The sections will first cover implementing the three data governance components. Then, the sections will include key constructs for each of the data governance components and practical methods to implement them.

We will cover the following topics in the chapter:

  • The 3-3-3 framework for data governance
  • The three components of data governance
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Data Lakehouse in Action
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