Data Lakehouse in Action: Architecting a modern and scalable data analytics platform

Propose a new scalable data architecture paradigm, Data Lakehouse, that addresses the limitations of current data architecture patterns

Key Features

- Understand how data is ingested, stored, served, governed, and secured for enabling data analytics
- Explore a practical way to implement Data Lakehouse using cloud computing platforms like Azure
- Combine multiple architectural patterns based on an organization's needs and maturity level

Book Description

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.

What you will learn

- Understand the evolution of the Data Architecture patterns for analytics
- Become well versed in the Data Lakehouse pattern and how it enables data analytics
- Focus on methods to ingest, process, store, and govern data in a Data Lakehouse architecture
- Learn techniques to serve data and perform analytics in a Data Lakehouse architecture
- Cover methods to secure the data in a Data Lakehouse architecture
- Implement Data Lakehouse in a cloud computing platform such as Azure
- Combine Data Lakehouse in a macro-architecture pattern such as Data Mesh

Who this book is for

This book is for data architects, big data engineers, data strategists and practitioners, data stewards, and cloud computing practitioners looking to become well-versed with modern data architecture patterns to enable large-scale analytics. Basic knowledge of data architecture and familiarity with data warehousing concepts are required.

提出一種新的可擴展數據架構範式——Data Lakehouse，以解決當前數據架構模式的限制。

主要特點：

- 了解數據如何進行摄取、存儲、提供、管理和保護，以實現數據分析
- 探索使用Azure等雲計算平台實現Data Lakehouse的實際方法
- 根據組織的需求和成熟度水平，結合多種架構模式

書籍描述：

Data Lakehouse架構是一種實現大規模分析的新範式。本書將指導您以正確的方式開發數據架構，確保組織的成功。

書籍的第一部分討論了過去使用的不同數據架構模式以及需要新的架構範式的原因，以及導致這一變化的驅動因素。它涵蓋了指導目標架構的原則、構成Data Lakehouse架構的組件以及這些組件的理由和需求。第二部分深入探討了Data Lakehouse的不同層次。它涵蓋了數據摄取、存儲、數據處理、數據提供、分析、治理和數據安全的各種情景和組件。書籍的第三部分專注於在雲計算平台上實現Data Lakehouse架構。它關注如何根據組織的需求和成熟度水平，結合Data Lakehouse模式實現Data Mesh和Data Hub-Spoke等宏觀模式的各種方法。介紹的框架將是實用的，組織可以從中受益。

通過閱讀本書，您將清楚了解如何以可擴展、靈活和具有成本效益的方式實現Data Lakehouse架構模式。

學到的知識：

- 了解數據架構模式在分析中的演變
- 熟悉Data Lakehouse模式及其如何實現數據分析
- 關注在Data Lakehouse架構中進行數據摄取、處理、存儲和治理的方法
- 學習在Data Lakehouse架構中提供數據和進行分析的技術
- 掌握在Data Lakehouse架構中保護數據的方法
- 在Azure等雲計算平台上實現Data Lakehouse
- 將Data Lakehouse結合到Data Mesh等宏觀架構模式中

適合閱讀對象：

本書適合數據架構師、大數據工程師、數據策略師和從業人員、數據管理者以及希望熟悉現代數據架構模式以實現大規模分析的雲計算從業人員。需要具備基本的數據架構知識和對數據倉儲概念的熟悉。

1. Introducing the Evolution of Data Analytics Patterns
2. The Data Lakehouse Architecture Overview
3. Ingesting and Processing Data in a Lakehouse
4. Storing and Serving Data in a Data Lakehouse
5. Deriving Insights from a Data Lakehouse
6. Applying Data Governance in a Data Lakehouse
7. Applying Data Security in a Data Lakehouse
8. Implementing a Data Lakehouse on Microsoft Azure
9. Scaling the Data Lakehouse Architecture

1. 介紹數據分析模式的演進
2. 數據湖架構概述
3. 在數據湖中載入和處理數據
4. 在數據湖中存儲和提供數據
5. 從數據湖中獲取洞察力
6. 在數據湖中應用數據治理
7. 在數據湖中應用數據安全
8. 在Microsoft Azure上實施數據湖架構
9. 擴展數據湖架構