Data Lakehouse in Action

Address the limitations of data lakes by moving to a new open and standardized system design - Lakehouse architecture

Key Features

• Understand how data is ingested, stored, served, cataloged, and converted into insights using analytics
• Implement data lakehouse architecture using popular cloud computing platforms such as Azure, AWS, and GCP
• Combine multiple architectural patterns based on an organizations' needs and maturity level

Book Description

Data lakehouse architecture is a new paradigm that enables the adept use of artificial intelligence (AI) and business intelligence (BI) in a scalable and cost-effective manner. This book will guide you in architecting data in the right way to ensure your organization's success.

You'll start by understanding the challenges faced while using different architectural patterns and uncover the new paradigm that is data lakehouse. You'll then cover the principles that govern the target architecture, the components that form the data lakehouse architecture, the rationale and need for those components, and the architectural principles adopted to make data lakes scalable and robust. Throughout the book, you'll focus on the architecture, component choices, and principles that need to be implemented to convert data into a strategic asset. The book features various scenarios covering data analytics, artificial intelligence (AI), and IoT to help you adopt practical architectural practices and principles relating to data ingestion, storage, processing, serving, and governance. You'll also learn how to combine multiple architectural patterns such as data lakehouse, lambda, and data mesh architectures based on the organization's needs and maturity level.

By the end of this book, you'll have a clear understanding of 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 architectural pattern for data analytics
• Become well-versed with the data lakehouse pattern and how it adds value to the existing data architecture
• Focus on batch and stream processing and transform your data into a data lakehouse
• Understand each component that makes up the data lakehouse ecosystem
• Implement principles that organizations should adopt to effectively take advantage of each component in a data lakehouse architecture
• Discover how to implement a robust governance framework in a data lakehouse architecture pattern

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 data architecture principles to architect a scalable lakehouse analytics platform. Basic knowledge of data architecture and familiarity with data warehousing is required.

Table of Contents

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