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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 8: Implementing a Data Lakehouse on Microsoft Azure

We have come a long way on our journey in exploring modern data analytics architecture through the concept of the data lakehouse. All seven layers of the data lakehouse are covered in detail in the preceding chapters. Although you can employ the same architecture in any cloud service or even on-premises, I will implement a data lakehouse on the Microsoft Azure platform.

This chapter will start by refreshing the concepts covered in Chapter 1, Introducing the Evolution of Data Analytics Patterns, and Chapter 2, The Data Lakehouse Architecture Overview, and establishing the advantages of using cloud computing. The following three sections of the chapter will focus on the cloud services used to bring to fruition the data lakehouse architecture. Finally, the chapter will explain the services in Microsoft Azure that you can use to realize the data lakehouse architecture. We will discuss the key features of each of these services...

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