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38944285
The Definitive Guide to Azure Data Engineering: Modern ELT, DevOps, and Analytics on the Azure Cloud Platform 1st ed. Edition
77% of respondents would recommend this to a friend
物品 #:
38944285
HKD 372
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What Stands Out
Comprehensive Coverage
This guide offers in-depth insights into modern ELT strategies, DevOps practices, and analytics tailored for Azure, making it essential for data engineers and cloud professionals seeking to enhance their skills.
Practical Applications
Includes real-world case studies and practical tips, enabling readers to implement concepts instantly, streamlining their workflow and providing actionable solutions for data engineering challenges on Azure.
Expert Contributions
Authored by industry experts, this resource leverages firsthand knowledge and experience, ensuring readers receive trustworthy and updated information relevant to current practices in Azure data engineering.
產品詳情
| Publisher | Apress |
| Publication date | August 7, 2021 |
| Edition | 1st ed. |
| Language | English |
| Print length | 636 pages |
| ISBN-10 | 1484271815 |
| ISBN-13 | 978-1484271810 |
| Item Weight | 2.4 pounds (1.09 kg) |
| Dimensions | 7.01 x 1.44 x 10 inches (17.8 x 3.7 x 25.4 cm) |
Who Should Buy?
-
Data Engineers
This guide is perfect for data engineers looking to enhance their skills in Azure-based data engineering practices.
-
DevOps Professionals
DevOps professionals aiming to integrate data engineering practices into their workflows will find valuable insights in this book.
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Business Analysts
Business analysts wanting to leverage Azure for data analytics will benefit from comprehensive practical examples and methodologies.
-
Beginner Users
Complete beginners to data engineering may struggle with the advanced concepts and terminology used throughout the guide.
產品敘述
The Definitive Guide to Azure Data Engineering: Modern ELT, DevOps, and Analytics on the Azure Cloud Platform 1st ed. Edition
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C & C++ Windows Programming Editorial Review
**** "The Definitive Guide to Azure Data Engineering: Modern ELT, DevOps, and Analytics on the Azure Cloud Platform" is a comprehensive resource tailored for professionals already familiar with data processing and looking to enhance their expertise in Azure Data Engineering. Reviewers indicate that this book is ideally suited for advanced data engineers who have a solid foundation in roles such as ETL development. Readers appreciate the author's intention to provide best practices and essential knowledge for implementing data solutions effectively on the Azure platform. The book is noted for its structured approach and relevance, delving into contemporary topics and code that align with the fast-evolving Azure ecosystem. The author, Mr. L'Esteve, has made commendable efforts to keep the content updated and relevant by providing links to supplemental resources, code repositories, and sample databases. This aspect has been particularly helpful for readers who are looking for practical guidance and hands-on exercises to implement solutions for real-world projects. While the book excels in offering advanced techniques and practical know-how, some novice readers may find it challenging due to its assumption of prior knowledge. Reviewers warn that those unfamiliar with Azure Data Engineering might become lost and frustrated, as the material does not cater to beginners seeking a comprehensive introduction to the subject. Additionally, there are comments about the book being somewhat dated, which could impact its relevance for those seeking the most current practices in a rapidly changing field. Overall, "The Definitive Guide to Azure Data Engineering" has been well-received by experienced practitioners looking for a thorough exploration of advanced data engineering techniques and tools on the Azure platform. **
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優點
- Comprehensive resource for advanced Azure Data Engineering practitioners.
- Structured chapters outlining relevant topics and advanced code examples.
- Frequent updates from the author, including links to supplemental resources.
- Hands-on exercises that facilitate practical implementation.
- Clear explanations of complex concepts with step-by-step instructions.
缺點
- Not suitable for beginners or those without a background in data engineering.
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