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246974456
Ultimate Data Engineering Design Patterns: Design and Build Scalable Data Pipelines Using Proven Patterns for Modern Data Platforms (English Edition)
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Nº de artículo:
246974456
NIO 2419
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- Build data pipelines that perform, scale, and last in production.Key Features● Get a free one-month digital subscription to www.avaskillshelf.com● Comprehensive data engineering pattern coverage spanning ingestion, storage, transformation, batch processing, and stream processing.● Hands-on implementation using Apache Spark, Kafka, Airflow, and cloud-native tools across real-world industry case studies.● Production-grade pipeline engineering with DataOps, governance, observability, and scalability strategies for modern data platforms.Book DescriptionData engineering is the backbone of every modern data-driven organization — and the ability to design scalable, reliable pipelines is the most in-demand skill across analytics, AI, and platform engineering. Ultimate Data Engineering Design Patterns provides a comprehensive, pattern-driven guide to building robust data infrastructure, from foundational ingestion and storage to stream processing, governance, and cloud-native deployment.You begin with core architectural patterns and data engineering fundamentals, then progressively work through ingestion, storage, batch processing, stream processing, and transformation patterns using tools such as Apache Spark, Kafka, and Airflow. Each chapter grounds concepts in hands-on exercises and industry case studies drawn from finance, healthcare, and e-commerce, ensuring every pattern is immediately applicable to real engineering scenarios.The final section covers data quality, governance, compliance, scalability optimization, and DataOps practices with end-to-end pipeline implementation and future trends. Thus, by the end of the book, you can design, build, and operate production-grade data pipelines with confidence, applying proven patterns to solve real-world data challenges at scale.What you will learn● Design scalable batch and real-time data pipelines using proven engineering patterns.● Implement reliable data ingestion workflows across diverse sources and formats.● Build efficient data lakes, warehouses, and lakehouse architectures for modern platforms.● Apply data governance, quality, and observability practices to production pipelines.● Optimize pipeline performance and scalability using cloud-native tools and strategies.● Implement DataOps practices for operationalising and maintaining enterprise data platforms.Table of Contents1. Introduction to Data Engineering2. Data Engineering Fundamentals3. Architectural Patterns in Data Engineering4. Data Ingestion Patterns in Data Engineering5. Storage Design Patterns in Data Engineering6. Batch Processing Patterns7. Stream Processing Patterns8. Data Transformation and Enrichment Patterns9. Machine Learning Engineering Patterns10. Data Quality Patterns11. Data Governance and Compliance12. Scalability and Performance Optimization13. Building End-to-End Data Pipelines14. Operationalizing Data Pipelines15. Future of Data Engineering Index
| Publisher | Orange Education Pvt Ltd |
| Publication date | 24 April 2026 |
| Language | English |
| Print length | 387 pages |
| ISBN-10 | 9349887290 |
| ISBN-13 | 978-9349887299 |
| Item weight | 490 g |
| Dimensions | 19.05 x 2.24 x 23.5 cm |
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Data Warehousing Editorial Review
Ultimate Data Engineering Design Patterns Design And Build Scalable Data Pipelines Using Proven Patterns For Modern Data Platforms English Edition is an essential resource for anyone involved in data engineering. This comprehensive guide, published by Orange Education Pvt Ltd, is set to release on 24 April 2026 and spans 387 pages, making it a substantive text for those looking to design and build scalable data pipelines effectively. The book covers proven patterns that are vital in modern data platforms, enabling engineers to enhance their workflows and tackle complex data processing challenges. Readers can expect valuable insights to optimize data architecture and enhance their technical proficiency.
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- Comprehensive guide for data engineering best practices
- Covers proven patterns for scalable data pipelines
- Published by a reputable educational publisher
- High-quality print with substantial page length
- Helpful for modern data platform development
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características y beneficios
- Learn to design scalable and reliable data pipelines.
- Hands-on implementation with tools like Apache Spark and Kafka.
- Comprehensive coverage of data engineering patterns.
- Real-world applications across finance, healthcare, and e-commerce.
- Focus on data quality, governance, and observability.
- Develop skills to confidently operate production-grade pipelines.
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