Data Engineering Design Patterns

This audiobook is narrated by a digital voice. DESCRIPTION Data engineering has gained even more relevance than before, and data engineering patterns are key to the successful implementation of data engineering projects. This book enables a data engineer to not only become familiar with data engineering patterns but also understand their application in real world use cases. This book presents a comprehensive collection of data engineering patterns, each illustrated with relevant enterprise use cases to highlight their value and simplicity. It showcases both open-source and cloud technologies, guiding readers in building data systems for on-premise and cloud environments. The book covers patterns for data ingestion, transformation, storage, and serving, while also offering insights into performance engineering for data pipelines. Once we understand fundamental data engineering patterns, we then shift focus to patterns that help us build high-performance low latency data systems. We cover data caching, partitioning, replication, and how to select the technology stack for building out the patterns in this book. By the end of the book, readers will have a deep understanding of various data engineering use cases and will be able to map the appropriate patterns to address them. They will also be equipped to choose the right technical stack for implementing these patterns, enabling them to create robust and efficient data systems in a secure and a cost-effective manner. WHAT YOU WILL LEARN ? Key data engineering patterns. ? Data ingestion and processing patterns. ? Modern architectures like Lambda. ? Explore time-tested data patterns of ETL and ELT. ? Modern data systems like data lake and medallion architectures. ? Domain-specific patterns and also on data orchestration, observability, and security. ? Overcoming performance challenges in building complex data systems.