Fundamentals of Data Engineering: Plan and Build Robust Data Systems
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Fundamentals of Data Engineering: Plan and Build Robust Data Systems
Learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.
Fundamentals of Data Engineering: Plan and Build Robust Data Systems
Preces #: 115753719

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

Preces #: 115753719

€ 54

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Learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.
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What Stands Out

Comprehensive Guide
Covers essential concepts of data engineering, from planning to building systems, providing a solid foundation for novice and experienced practitioners alike.
Practical Insights
Includes real-world examples and case studies that demonstrate effective strategies, allowing readers to apply learned principles directly to their projects.
Up-to-Date Techniques
Incorporates modern tools and methodologies, ensuring readers are equipped with the latest skills necessary for today's data-centric environment.

Produkta informācija

Get the 1st Edition of Fundamentals of Data Engineering, a comprehensive guide to plan and build robust data systems. Buy now at Ubuy Latvia!
  • Comprehensive view of data engineering lifecycle and best practices
  • Learn to plan and build systems using cloud technologies
  • Understand data generation, ingestion, orchestration, transformation, storage, and governance
  • Cut through marketing hype when choosing data technologies and architecture
  • Incorporate data governance and security across the data engineering lifecycle
  • Target audience includes software engineers, data scientists, data analysts, and technical practitioners
Item Weight1.1 lbs (500 grams)

Who Should Buy?

Suitable For
  • Aspiring Data Engineers

    Perfect for beginners looking to understand data system design and implementation basics for their future careers.

  • Technical Managers

    Useful for managers overseeing data projects, helping them understand fundamental concepts for better team leadership.

  • Data Enthusiasts

    Ideal for individuals passionate about data who want to deepen their understanding of engineering methodologies and best practices.

Not Suitable For
  • Experienced Professionals

    May not be suitable for seasoned engineers seeking advanced topics beyond foundational data engineering concepts.

  • Non-Technical Users

    Not recommended for users without technical backgrounds or interest, as it covers complex engineering principles.

  • Casual Readers

    Unsuitable for those seeking light reading or casual insights, as it focuses on applied technical knowledge.

PRODUKTA APRAKSTS

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

Vai jums ir kādi jautājumi? Terzet ar mums

Klientu jautājumi un atbildes

  • jautājums: Who is this book for?

    atbildi: This book is for software engineers, data scientists, and analysts looking for a comprehensive view of data engineering.
  • jautājums: What does the book cover?

    atbildi: The book covers the data engineering lifecycle, including data generation, ingestion, orchestration, transformation, storage, and governance.
  • jautājums: What will readers learn from this book?

    atbildi: Readers will learn how to plan and build robust data systems by evaluating the best technologies and following best practices throughout the data engineering lifecycle.

Data Modeling & Design Editorial Review

**** "Fundamentals of Data Engineering: Plan and Build Robust Data Systems" by Joe Reis and Matt Houser has garnered Considerable acclaim since its release, especially for those who are new to the field of data engineering. This book is praised for its clear and practical approach, offering readers a well-structured overview of essential concepts, tools, and workflows necessary for Constructing real-world data pipelines. It strikes a balance between being accessible for beginners and providing enough depth to benefit those with some prior experience in data analysis or engineering. A standout feature of the book is its technology-agnostic stance, which distinguishes it from many other resources that focus on specific tools such as PySpark or Hadoop. Instead, it fosters a broader understanding of data engineering principles, emphasizing sound architectural strategies and the importance of ROI. Readers have noted that it provides valuable insights ranging from hardware fundamentals to stakeholder management, making it a comprehensive resource for various professionals within the data ecosystem. However, while the book serves as a solid introduction to data engineering, it is not without its shortcomings. Some readers express concern over its lack of cohesive narrative, as certain concepts are introduced without thorough explanations, leading to a somewhat disjointed reading experience. Additionally, there are sections that feel excessively repetitive, with some information highlighted multiple times across different chapters. The variance in the level of technical detail can also be off-putting; certain topics are elaborated upon while others receive minimal coverage, potentially alienating readers from different backgrounds or experience levels. Moreover, some critics mention that the book appears to be heavily influenced by a "big tech" perspective, particularly concerning the emphasis on streaming data as the future of data engineering. Readers not involved in such high-frequency data environments may find this assertion less relevant to their needs. Despite its imperfections, "Fundamentals of Data Engineering" is regarded as a vital addition to any data professional's library. It is particularly recommended for newcomers aiming to establish a solid foundation in data engineering principles, while more experienced practitioners might derive less value from it. Overall, this book is a commendable effort in an evolving field, though some readers may find it worthwhile to wait for subsequent editions to address its current limitations. **

Customer Reviews & Ratings

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  • 4 zvaigzne
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Pros

  • Clear, practical, and well-structured for beginners.
  • Technology-agnostic, providing universal data engineering frameworks.
  • Valuable insights for both new and experienced professionals.
  • Comprehensive coverage of data architecture and stakeholder management.

Mīnusi

  • Lack of cohesive narrative; concepts occasionally introduced before fully explained.

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€ 54

Pasūtiet tūlīt un saņemiet to Piektdiena, Jūlijs 10

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Funkcijas un priekšrocības

  • Understand the data engineering lifecycle
  • Assess data engineering problems using best practices
  • Choose the right data technologies, architecture, and processes
  • Design and build a robust architecture
  • Incorporate data governance and security