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Data Lakehouse in Action

You're reading from Data Lakehouse in Action Architecting a modern and scalable data analytics platform

Product type Paperback

Published in Mar 2022

Publisher Packt

ISBN-13 9781801815932

Length 206 pages

Edition 1st Edition

Languages

Python

Tools

AWS IoT

Concepts

Big Data

Author (1):

Pradeep Menon

View More author details

Table of Contents (14) Chapters

Preface

1. PART 1: Architectural Patterns for Analytics

2. Chapter 1: Introducing the Evolution of Data Analytics Patterns FREE CHAPTER

3. Chapter 2: The Data Lakehouse Architecture Overview

4. PART 2: Data Lakehouse Component Deep Dive

5. Chapter 3: Ingesting and Processing Data in a Data Lakehouse

6. Chapter 4: Storing and Serving Data in a Data Lakehouse

7. Chapter 5: Deriving Insights from a Data Lakehouse

8. Chapter 6: Applying Data Governance in the Data Lakehouse

9. Chapter 7: Applying Data Security in a Data Lakehouse

10. PART 3: Implementing and Governing a Data Lakehouse

11. Chapter 8: Implementing a Data Lakehouse on Microsoft Azure

12. Chapter 9: Scaling the Data Lakehouse Architecture

13. Other Books You May Enjoy

Implementing a data lakehouse in a macro-architectural pattern

The building block for both these patterns is a node. The following figure depicts the formation of a node:

Figure 9.1 – A node – the building block for the macro-architecture pattern

A node is the data lakehouse architectural component implemented in the organization's sub-units and the central unit. The hub-spoke and the data mesh patterns differ in how the data is discovered and shared between the nodes. Let's discuss these patterns in detail.

The hub-spoke pattern

The first pattern that we want to discuss is the hub-spoke pattern. The following figure depicts the conceptual architecture of the hub-spoke pattern:

Figure 9.2 – The conceptual architecture of the hub-spoke pattern

A central node acts as a hub in the hub-spoke pattern, and many edge nodes act as the spoke. The hub is the central node that orchestrates and governs the...

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Authors (1)

Pradeep Menon

Pradeep Menon

Pradeep Menon is a seasoned data analytics professional with more than 18 years of experience in data and AI. Pradeep can balance business and technical aspects of any engagement and cross-pollinate complex concepts across many industries and scenarios. Currently, Pradeep works as a data and AI strategist at Microsoft. In this role, he is responsible for driving big data and AI adoption for Microsoft's strategic customers across Asia. Pradeep is also a distinguished speaker and blogger and has given numerous keynotes on cloud technologies, data, and AI.

See other products by Pradeep Menon

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