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现代数据工程指南:构建云端可扩展数据处理系统
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本书是一本关于数据工程的综合指南,旨在帮助读者掌握构建可扩展、高效且面向未来的云端数据处理系统。书中深入探讨了现代数据工程的技术和最佳实践,涵盖了数据解决方案的架构设计、性能优化、成本效益以及敏捷开发流程。作者结合了超过60年的行业经验,提供了关于数据管道、无服务器计算和微服务等关键主题的实用见解和真实世界示例,帮助读者规避常见陷阱,设计并交付高性能、安全且具备韧性的数据应用。

📚 **核心主旨:** 本书旨在指导读者掌握现代数据工程的最佳实践,以在云平台上构建可扩展、高效且具备未来适应性的数据处理系统。它强调了架构设计、性能优化、成本控制以及敏捷开发流程的重要性,帮助数据工程师应对快速变化的业务需求。

🛠️ **关键技术与方法:** 书中详细介绍了如何设计和构建优化的云端数据解决方案,并探讨了能够平衡角色、技术选择和流程的设计模式,以实现面向未来的数据架构。此外,还涵盖了利用无服务器计算和微服务构建韧性数据应用的方法。

💡 **实践指导与经验分享:** 作者结合了丰富的行业经验,提供了关于数据工程项目中的常见陷阱的规避建议,并通过真实世界的案例研究来阐述潜在的解决方案。读者将学到如何独立研究并掌握各种数据工程工具的能力。

Write a summary from what you are reading. This is where your thinking happens. Where you get something out of your book.

# Notes During Reading

# What’s about

Explore modern data engineering techniques and best practices to build scalable, efficient, and future-proof data processing systems across cloud platforms

# Key Features

    Architect and engineer optimized data solutions in the cloud with best practices for performance and cost-effectivenessExplore design patterns and use cases to balance roles, technology choices, and processes for a future-proof designLearn from experts to avoid common pitfalls in data engineering projectsPurchase of the print or Kindle book includes a free PDF eBook

# Book Description

Revolutionize your approach to data processing in the fast-paced business landscape with this essential guide to data engineering. Discover the power of scalable, efficient, and secure data solutions through expert guidance on data engineering principles and techniques. Written by two industry experts with over 60 years of combined experience, it offers deep insights into best practices, architecture, agile processes, and cloud-based pipelines.

You’ll start by defining the challenges data engineers face and understand how this agile and future-proof comprehensive data solution architecture addresses them. As you explore the extensive toolkit, mastering the capabilities of various instruments, you’ll gain the knowledge needed for independent research. Covering everything you need, right from data engineering fundamentals, the guide uses real-world examples to illustrate potential solutions. It elevates your skills to architect scalable data systems, implement agile development processes, and design cloud-based data pipelines. The book further equips you with the knowledge to harness serverless computing and microservices to build resilient data applications.

By the end, you’ll be armed with the expertise to design and deliver high-performance data engineering solutions that are not only robust, efficient, and secure but also future-ready.

More on : Data Engineering Best Practices: Architect robust and cost-effective data solutions in the cloud era: 9781803244983: Computer Science Books @ Amazon.com.

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相关标签

数据工程 Data Engineering 云数据处理 Cloud Data Processing 可扩展系统 Scalable Systems 最佳实践 Best Practices 敏捷开发 Agile Development 无服务器计算 Serverless Computing 微服务 Microservices
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