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  • Book Overview & Buying Engineering Lakehouses with Open Table Formats
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Engineering Lakehouses with Open Table Formats

Engineering Lakehouses with Open Table Formats

By : Dipankar Mazumdar, Vinoth Govindarajan
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Engineering Lakehouses with Open Table Formats

Engineering Lakehouses with Open Table Formats

By: Dipankar Mazumdar, Vinoth Govindarajan

Overview of this book

Engineering Lakehouses with Open Table Formats provides detailed insights into lakehouse concepts, and dives deep into the practical implementation of open table formats such as Apache Iceberg, Apache Hudi, and Delta Lake. You’ll explore the internals of a table format and learn in detail about the transactional capabilities of lakehouses. You’ll also get hands on with each table format with exercises using popular computing engines, such as Apache Spark, Flink, Trino, and Python-based tools. The book addresses advanced topics, including performance optimization techniques and interoperability among different formats, equipping you to build production-ready lakehouses. With step-by-step explanations, you’ll get to grips with the key components of lakehouse architecture and learn how to build, maintain, and optimize them. By the end of this book, you’ll be proficient in evaluating and implementing open table formats, optimizing lakehouse performance, and applying these concepts to real-world scenarios, ensuring you make informed decisions in selecting the right architecture for your organization’s data needs.
Table of Contents (15 chapters)
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13
Other Books You May Enjoy
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Index

Data Governance and Security in Lakehouses

Data governance and security represent critical pillars in modern lakehouse architecture, especially those built on open table formats such as Apache Iceberg, Apache Hudi, and Delta Lake. This chapter provides a comprehensive examination of governance practices, quality frameworks, lifecycle management, and security protocols essential for enterprise-grade lakehouse implementations.

Organizations implementing data lakehouses face unique challenges as they attempt to maintain the flexibility of data lakes while ensuring the governance capabilities traditionally associated with data warehouses. The following sections will guide you through establishing robust governance mechanisms, implementing comprehensive data quality measures, managing complete data lifecycles, securing access to sensitive information, and navigating the complex landscape of regulatory compliance.

By implementing these practices, organizations can ensure that their...

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