Practical Lakehouse Architecture: Designing and Implementing Mode Data Platforms at Scale

by: Gaurav Ashok Thalpati (Author)

Publisher: O’Reilly Media

Edition: 1st

Publication Date: 2024/8/27

Language: English

Print Length: 283 pages

ISBN-10: 1098153014

ISBN-13: 9781098153014

Book Description

This concise yet comprehensive guide explains how to adopt a data lakehouse architecture to implement mode data platforms. It reviews the design considerations, challenges, and best practices for implementing a lakehouse and provides key insights into the ways that using a lakehouse can impact your data platform, from managing structured and unstructured data and supporting BI and AI/ML use cases to enabling more rigorous data goveance and security measures. Practical Lakehouse Architecture shows you how to: Understand key lakehouse concepts and features like transaction support, time travel, and schema evolution Understand the differences between traditional and lakehouse data architectures Differentiate between various file formats and table formats Design lakehouse architecture layers for storage, compute, metadata management, and data consumption Implement data goveance and data security within the platform Evaluate technologies and decide on the best technology stack to implement the lakehouse for your use case Make critical design decisions and address practical challenges to build a future-ready data platform Start your lakehouse implementation jouey and migrate data from existing systems to the lakehouse

About the Author

This concise yet comprehensive guide explains how to adopt a data lakehouse architecture to implement mode data platforms. It reviews the design considerations, challenges, and best practices for implementing a lakehouse and provides key insights into the ways that using a lakehouse can impact your data platform, from managing structured and unstructured data and supporting BI and AI/ML use cases to enabling more rigorous data goveance and security measures. Practical Lakehouse Architecture shows you how to: Understand key lakehouse concepts and features like transaction support, time travel, and schema evolution Understand the differences between traditional and lakehouse data architectures Differentiate between various file formats and table formats Design lakehouse architecture layers for storage, compute, metadata management, and data consumption Implement data goveance and data security within the platform Evaluate technologies and decide on the best technology stack to implement the lakehouse for your use case Make critical design decisions and address practical challenges to build a future-ready data platform Start your lakehouse implementation jouey and migrate data from existing systems to the lakehouse