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Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud
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Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud
Become a successful data engineer by building and deploying your own data pipelines on Google Cloud.
Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud
Item #: 106582812

Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud

90% of respondents would recommend this to a friend

Item #: 106582812

TND 118

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What Stands Out

Comprehensive Guide
This guide provides an in-depth look at building scalable data platforms using Google Cloud, making it ideal for aspiring and professional data engineers seeking to enhance their skills.
Hands-on Projects
Incorporating practical projects, this book allows readers to apply concepts in real-world scenarios, effectively bridging theory with practice for better understanding and retention.
Updated Content
The second edition features the latest advancements in Google Cloud technologies, ensuring readers are informed about current trends and best practices in data engineering.

Product Details

Shop Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud online at a best price in Tunisia. 1835080111
Publisher Packt Publishing
Publication date April 30, 2024
Edition 2nd ed.
Language English
Print length 476 pages
ISBN-10 1835080111
ISBN-13 978-1835080115
Item Weight 1.79 pounds (810 grams)
Dimensions 7.5 x 1.08 x 9.25 inches (19.1 x 2.7 x 23.5 cm)

Who Should Buy?

Suitable For
  • Aspiring Data Engineers

    Individuals looking to start a career in data engineering and seeking hands-on experience with Google Cloud technologies.

  • Cloud Professionals

    IT professionals wanting to enhance their skills in cloud-based data solutions, particularly within Google Cloud Platform.

  • Data Scientists

    Data scientists interested in expanding their knowledge about data engineering to better manage and preprocess data.

Not Suitable For
  • Beginners in Tech

    Those with no prior technical background may find the content too advanced and challenging to grasp effectively.

Product Description

Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud

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Customer Questions & Answers

  • Question: What is 'Data Engineering with Google Cloud Platform' about?

    Answer: This comprehensive guide explores the nuances of data engineering specifically utilizing Google Cloud Platform (GCP). It focuses on methodologies for building scalable data platforms, employing tools such as BigQuery, Dataflow, and Dataproc. The second edition incorporates updated practices and case studies to reflect the latest advancements in cloud technologies. Data engineering professionals can implement these concepts to manage and analyze large datasets efficiently, transcending traditional infrastructure limitations.
  • Question: Who is the target audience for this book?

    Answer: The book is primarily aimed at data engineers, data analysts, and cloud developers who are looking to enhance their capabilities in cloud-based data infrastructures. It’s also valuable for IT professionals and students interested in pursuing a career in data engineering. By leveraging GCP, the reader gains hands-on experience in building and optimizing data pipelines, thus broadening their skill set for modern data challenges.
  • Question: What are the key features of this book?

    Answer: Key features of 'Data Engineering with Google Cloud Platform' include hands-on tutorials, real-world case studies, and best practices in cloud-based data management. The second edition highlights improved coverage of Google Cloud tools, integration techniques, and scalability challenges. These elements make the book an essential resource for anyone looking to fill gaps in their knowledge and optimize their data workflows within GCP.
  • Question: How does this book help in building scalable data platforms?

    Answer: The book provides step-by-step guidance on leveraging GCP services to construct scalable data platforms tailored to specific business needs. Readers will learn how to design systems that can efficiently handle increased data volumes while maintaining performance. It discusses load balancing, elasticity, and data storage optimizations. This approach is vital for organizations that need to adapt to fluctuating data demands without compromising on speed or efficiency.
  • Question: What technologies are covered in the book?

    Answer: The guide extensively covers various GCP technologies such as Google BigQuery for data warehousing, Dataflow for stream and batch processing, and Pub/Sub for event-driven architectures. It details how these tools integrate with each other, allowing users to create powerful data-pipelines. Through this knowledge, readers can equip themselves with the skills to implement robust data solutions using cutting-edge cloud technologies.
  • Question: Are there practical examples included in the book?

    Answer: Yes, the book is rich with practical examples and case studies that demonstrate the real-world application of data engineering concepts. These examples illustrate how organizations have leveraged GCP to solve complex data problems, enabling readers to visualize how theoretical knowledge translates into effective strategies. By dissecting these scenarios, readers can gain insights that are applicable to their unique data challenges.
  • Question: How can this book contribute to my career advancement?

    Answer: Reading this book equips professionals with the necessary skills to excel in the rapidly evolving field of data engineering. By mastering GCP and its tools, you become more competitive in job markets where cloud proficiency is increasingly demanded. Additionally, the knowledge gained can lead to new opportunities for projects, collaborations, and innovations in your organization, enhancing your professional profile.
  • Question: What learning resources are included with the book?

    Answer: The book offers learning resources such as access to online materials, supplementary code examples, and links to dedicated tutorials. These resources provide readers with additional support during their learning process, enabling them to experiment with the concepts discussed in the book. Engaging with these materials solidifies understanding and enhances practical application, creating a robust learning environment.
  • Question: What prerequisites are recommended before reading this book?

    Answer: While the book is accessible to newcomers, having a basic understanding of data engineering principles and some familiarity with cloud computing will be beneficial. Prior experience with SQL and familiarity with programming, ideally in Python or Java, will help in grasping the technical aspects explained in the book. This foundational knowledge allows readers to navigate the content effectively and maximize their learning experience.
  • Question: Where can I buy 'Data Engineering with Google Cloud Platform' in Tunisia?

    Answer: You can purchase 'Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud 2nd ed.' from Ubuy in Tunisia. Ubuy is a reliable platform that offers a diverse selection of books and online resources, making it easy for you to find and acquire the latest edition of this essential guide.

Data Modeling & Design Editorial Review

**** "Data Engineering with Google Cloud Platform" by Adi Wijaya stands out as an essential guide for data engineers who aim to elevate their skills in Google Cloud. This 2nd edition offers a comprehensive look into the nuances of data engineering, from foundational concepts to complex, scalable data pipelines. The book expertly caters to both novices and seasoned professionals, striking a balance between big-picture insights and detailed technical execution. One of the book's most commendable features is its structured approach. Wijaya begins by familiarizing readers with key tools such as BigQuery, Cloud Storage, and Cloud Dataflow, gradually weaving in advanced topics like real-time data processing and machine learning integration. This step-by-step progression ensures that learners of all levels can engage with the material effectively. The hands-on tutorials are particularly beneficial, fostering a practical learning environment through direct implementation of concepts. This methodology is enhanced by the inclusion of command-line utilities like gcloud and gsutil, giving readers tangible experience in cloud resource management. Real-world examples further illustrate how these concepts apply to various industries, making the material resonate with professional contexts. However, some users noted that absolute beginners might find certain sections to be fast-paced without prior knowledge of cloud computing fundamentals. Additionally, while the book focuses specifically on GCP, readers seeking comparative insights with other platforms, such as AWS or Azure, may find this aspect lacking. Overall, "Data Engineering with Google Cloud Platform" is a highly recommended resource for anyone invested in mastering the intricacies of data engineering within the GCP ecosystem. With its mix of theory, practical activities, and industry-specific examples, it equips aspiring and practicing data engineers with the essential knowledge needed to thrive. **

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Pros

  • Structured approach that builds knowledge progressively
  • Comprehensive coverage of data engineering principles
  • Hands-on tutorials with practical exercises
  • Real-world use cases enhancing context and application
  • Clear explanations of GCP data engineering tools and concepts

Cons

  • May be fast-paced for complete beginners in cloud computing

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TND 118

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Features & Benefits

  • Learn to build and deploy data pipelines on Google Cloud.
  • Gain insights into data governance within Google Cloud.
  • Explore essential tools like Dataform, DLP, and Dataproc Serverless.
  • Receive Google Cloud data engineering certification guidance.
  • Adapt foundational principles to cutting-edge practices.
  • Ideal for beginners and seasoned professionals in data engineering.

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