Book Image

Data Lakehouse in Action

By : Pradeep Menon
5 (1)
Book Image

Data Lakehouse in Action

5 (1)
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)
1
PART 1: Architectural Patterns for Analytics
4
PART 2: Data Lakehouse Component Deep Dive
10
PART 3: Implementing and Governing a Data Lakehouse

Enabling analytics capabilities in a data lakehouse

The previous section defined the different types of analytics that need to be fulfilled by a data lakehouse. Now, let's focus on how a data lakehouse enables these capabilities. Recall that in Chapter 2, The Data Lakehouse Architecture Overview, we defined the logical architecture of a data lakehouse. One of the layers of the architecture was the data analytics layer, which interacts with the data lake layer and the data serving layer. The following figure illustrates this interaction between the layers of the data lakehouse architecture:

Figure 5.4 – The interaction between the data lakehouse layers

The three components of the data analytics layer are as follows:

  • Analytical sandbox service
  • Business intelligence service
  • AI/ML service

The following figure maps the required analytics capabilities to the components that fulfill them:

Figure 5.5 –...