data engineering design patterns di kulkarni amit (11 risultati)

Paperback or Softback. Condizione: New. Data Engineering Design Patterns: Scalable data engineering for efficient data systems and workflows (English Edition). Book.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condizione: New.

paperback. Condizione: New.

Condizione: New. 2025. paperback. . . . . .

Condizione: New. 2025. paperback. . . . . . Books ship from the US and Ireland.

Condizione: NEW.

Paperback. Condizione: New.

Paperback. Condizione: Brand New. 346 pages. 7.50x0.78x9.25 inches. In Stock. This item is printed on demand.

Paperback. Condizione: new. Paperback. 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.WHO THIS BOOK IS FORThis book is designed for data engineers with beginner to intermediate experience in building enterprise-grade data systems. ETL developers transitioning into data engineering roles will also find this book valuable for understanding essential data engineering patterns. The code snippets provided throughout the book are written in Python or Scala, so a basic understanding of either language will help readers more easily grasp the concepts presented.