Traditional data architecture patterns are severely limited. To use these patterns, you have to ETL data into each tool--a cost-prohibitive process for making warehouse features available to all of your data. This lack of flexibility forces you to adjust your workflow to the tool your data is locked in, which creates data silos and data drift. This book shows you a better way. Apache Iceberg provides the capabilities, performance, scalability, and savings that fulfill the promise of an open data lakehouse. By following the lessons in this book, you'll be able to achieve interactive, batch, machine learning, and streaming analytics with this lakehouse. Authors Tomer Shiran, Jason Hughes, Alex Merced, and Dipankar Mazumdar from Dremio guide you through the process. With this book, you'll learn: The architecture of Apache Iceberg tables What happens under the hood when you perform operations on Iceberg tables How to further optimize Apache Iceberg tables for maximum performance How to use Apache Iceberg with popular data engines such as Apache Spark, Apache Flink, and Dremio Sonar How Apache Iceberg can be used in streaming and batch ingestion Discover why Apache Iceberg is a foundational technology for implementing an open data lakehouse.