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Artikel #:
232389925
Data Engineering Design Patterns: Scalable data engineering for efficient data systems and workflows (English Edition), (Paperback)
Artikel #:
232389925
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This book presents a comprehensive collection of data engineering patterns, each illustrated with relevant enterprise use cases to highlight their value and simplicity.
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Podrobnosti produkta
- 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 LEARNâ— Key data engineering patterns.â— Data ingestion and processing patterns.â— Modern architectures like Lambda.â— Explore time-tested data patterns of ETL and ELT.â— Modern data systems like data lake and medallion architectures.â— 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.
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | September, 2025 |
| Pages | 348 |
| Subgenre | Data Science |
| Series title | No Series |
| Edition | 1 |
| Publisher | Bpb Publications |
| Original languages | English |
| Language | English |
| Edu focus | Engineering |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 7.50 x 0.72 x 9.25 in (19.1 x 1.8 x 23.5 cm) |
| Assembled product weight | 1.32 lb (600 grams) |
| Bisac subject heading | Computers |
OPIS IZDELKA
Data Engineering Design Patterns: Scalable data engineering for efficient data systems and workflows (English Edition), (Paperback)
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Amit Kulkarni All Books Editorial Review
Data Engineering Design Patterns: Scalable data engineering for efficient data systems and workflows (English Edition) offers valuable insights into creating efficient data systems. This non-fiction title, published by Bpb Publications, runs 348 pages and delves into essential aspects of computing and internet technologies. With a focus on data science engineering, the book is designed for professionals looking to enhance their understanding of scalable data engineering practices. The paperback format makes it accessible for readers who prefer physical copies. Readers have noted its clarity and depth, making it a must-have for anyone in the field of data engineering.
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Prednosti
- Comprehensive guide on data engineering concepts
- Discusses scalable data systems thoroughly
- Clear explanations for complex topics
- Ideal for professionals in data science
- Well-structured for easy understanding
Slabosti
- A bit lengthy for casual readers
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Značilnosti in prednosti
- Comprehensive guide to data engineering design patterns.
- Illustrated with real-world enterprise use cases.
- Covers data ingestion, transformation, storage, and serving.
- Focuses on performance engineering for data pipelines.
- Equips readers to choose the right technology stack.
- Designed for beginner to intermediate data engineers.
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