This concise yet comprehensive guide explains how to adopt a data lakehouse architecture to implement modern 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 governance and security measures. Lakehouse architecture is one such modern architectural pattern that has evolved in the last few years. It has become a popular choice for data architects who are designing data platforms. In the Chapter 1, I’ll introduce you to fundamental concepts related to data architecture, data platform and its core components, and how data architecture helps build a data platform. Once you have understood these, I’ll explain why there is a need for new architectural patterns like lakehouse, lakehouse fundamentals, its characteristics, and the benefits of implementing a data platform using lakehouse architecture. I’ll conclude the chapter with key takeaways to summarize everything we discuss and help you remember the key points while reading the subsequent chapters in this book.

Practical Lakehouse Architecture (5ER) PDF

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