数据工程101

English | June 1, 2024 | ASIN: B0D5FLXXX5 | 175 pages | EPUB | 1.36 Mb

Are you tired of reading academic textbooks that make data engineering seem like a field only for the coding elites? Do you feel like you’re constantly struggling with complex datasets, unable to make sense of them? Do you want to unlock the true potential of data and become a sought-after professional in a rapidly evolving industry? If you’ve answered yes to these questions, then you’re in the right place. Why? Because mastering data engineering doesn’t have to be an uphill battle. Even if you’ve tried learning Python, SQL, or Hadoop, and it felt like you were reading a foreign language, it’s not the end of your data journey. In fact, becoming a proficient data engineer and unlocking lucrative opportunities in data is achievable and it’s much easier than you think. Here is just a small fraction of what you'll discover inside this book The foundational overview: What is data engineering and why it’s critical to businesses in the digital age? Step-by-step guide to mastering Python, the most used language in data engineering Breaking down complex database systems into understandable chunks: Practical exposure to SQL, NoSQL and NewSQL Navigating the maze of ETL (Extract, Transform, Load) processes like a seasoned data engineer Demystifying Hadoop and its components: Get up and running with Hadoop ecosystems in no time. Unlocking the potential of Apache Kafka for real-time data processing The definitive guide to data warehousing and data lakes - which one is right for you? Mastering data pipelines: How to execute effective, efficient and fault-tolerant pipelines Exploring Cloud solutions: An in-depth guide to Amazon Web Services (AWS), Google Cloud and Azure The future of data engineering: Get a jump start on distributed systems, edge computing, and more …and much, much more.

中文|2024年6月1日|ASIN:B0D5FLXXX5|175页|EPUB |1.36 Mb你是否厌倦了阅读那些让数据工程看起来像是一个只适合编码精英的领域的学术教科书？你是否觉得你一直在与复杂的数据集作斗争，无法理解它们？你想释放数据的真正潜力，成为一个快速发展的行业中备受追捧的专业人士吗？如果你对这些问题的回答是肯定的，那么你来对地方了。为什么？因为掌握数据工程不一定是一场艰苦的战斗。即使你尝试过学习Python、SQL或Hadoop，感觉就像在阅读一门外语，这也不是你数据之旅的终点。事实上，成为一名熟练的数据工程师并在数据中解锁有利可图的机会是可以实现的，而且比你想象的要容易得多。以下只是您在本书《基础概述》中发现的内容的一小部分：什么是数据工程，为什么它对数字时代的企业至关重要？掌握Python的分步指南，Python是数据工程中最常用的语言。将复杂的数据库系统分解为可理解的块：实际接触SQL、NoSQL和NewSQL。像经验丰富的数据工程师一样，在错综复杂的ETL（提取、转换、加载）过程中导航。揭开Hadoop及其组件的神秘面纱：立即启动并运行Hadoop生态系统。释放Apache Kafka在实时数据处理方面的潜力数据仓库和数据湖的权威指南——哪一个适合你？掌握数据管道：如何执行有效、高效和容错的管道探索云解决方案：亚马逊网络服务（AWS）、谷歌云和Azure的深入指南数据工程的未来：在分布式系统、边缘计算等方面快速起步……以及更多。

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