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Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS
Data Engineering with AWS is the missing expert-led manual for the AWS ecosystem ― go from foundations to building data engineering pipelines effortlessly
Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS
Item #: 48265124

Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS

Item #: 48265124

€ 81

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Data Engineering with AWS is the missing expert-led manual for the AWS ecosystem ― go from foundations to building data engineering pipelines effortlessly
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What Stands Out

Cloud Expertise
Gain hands-on experience with AWS, a leading cloud platform, enhancing your cloud engineering skills to meet industry demands and advance your career in data engineering.
Pipeline Design
Learn to design efficient data transformation pipelines that streamline data processes, helping organizations to leverage their data effectively for informed decision-making.
Real-World Applications
Hands-on projects simulate real-world scenarios, allowing you to apply theoretical knowledge practically, preparing you for the challenges faced in modern data engineering roles.

Product Details

Discover how to design and build cloud-based data transformation pipelines using AWS. Find comprehensive resources for data engineering at Ubuy Monaco.
  • Comprehensive guide for designing and building cloud-based data transformation pipelines with AWS
  • Written by a Senior Data Architect with over twenty-five years of experience in the business
  • Covers common data architectures, modern approaches to generating value from big data, and AWS tools for ingesting, transforming, and consuming data
  • Explains how to architect and implement data lakes and data lakehouses for big data analytics
  • Teaches how to use AWS tools for analyzing data and how to draw new insights from data using machine learning and artificial intelligence
  • Suitable for data engineers, data analysts, and data architects new to AWS, with or without a basic understanding of big data-related topics and Python coding
Publisher Packt Publishing
Publication date December 29, 2021
Language English
Print length 482 pages
ISBN-10 1800560419
ISBN-13 978-1800560413
Item Weight 1.81 pounds (820 grams)
Dimensions 7.5 x 1.09 x 9.25 inches (19.1 x 2.8 x 23.5 cm)

Who Should Buy?

Suitable For
  • Aspiring Data Engineers

    Individuals looking to start a career in data engineering can greatly benefit from structured learning on AWS tools.

  • Cloud Practitioners

    Professionals familiar with cloud concepts who want to delve deeper into data engineering practices would find this course essential.

  • Technical Managers

    Managers overseeing data teams seeking to enhance their team's capabilities in cloud-based data transformation will find this informative.

Not Suitable For
  • Beginner Programmers

    Those without foundational programming skills may struggle to grasp the content and practical applications of data engineering.

Product Description

Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS

Have any Query? Chat with us

Customer Questions & Answers

  • Question: Who is the target audience for this book?

    Answer: This book primarily targets data engineers, data scientists, and developers looking to enhance their skills in cloud data architecture. It's also suitable for IT professionals or business analysts involved in data management and analytics wishing to gain hands-on experience with AWS. The content is structured to serve both beginners and those with prior knowledge of AWS seeking to specialize in data engineering.
  • Question: What prior knowledge do I need before reading this book?

    Answer: While specific prerequisites are not mandatory, familiarity with AWS, SQL, and basic programming concepts in Python or Java can greatly enhance your understanding of the material. A general knowledge of data engineering concepts will help you grasp the advanced topics more efficiently. The book is designed to start with foundational concepts, making it approachable even for more novice users.
  • Question: Can I apply the techniques learned in this book to my job?

    Answer: Absolutely! The techniques and frameworks presented in 'Data Engineering with AWS' are applicable in various industries that utilize data-driven decision-making. As organizations increasingly migrate to cloud-based solutions, the skills acquired can help in transforming data processes, optimizing data workflows, and improving data analytics capabilities in your work environment.
  • Question: Are there any hands-on projects included in the book?

    Answer: Yes, the book features a variety of hands-on projects that allow you to apply what you've learned. These projects range from simple data pipeline implementations to more complex scenarios involving multiple AWS services. Engaging in these projects helps solidify your understanding and provides practical experience that is essential for real-world application.
  • Question: Is it suitable for learning AWS data services comprehensively?

    Answer: Yes, this book serves as a comprehensive guide to AWS data services. It delves into the functionalities and applications of key AWS tools and provides insight into their integration for building efficient data pipelines. This thorough approach gives readers the skills needed to confidently navigate the AWS ecosystem for data engineering tasks.
  • Question: How is the book structured?

    Answer: The book is structured in a progressive format, starting with foundational concepts of data engineering and gradually advancing to more complex implementations. Each chapter builds on the last, featuring clear explanations, architectural diagrams, and coding examples for better clarity. This structuring caters to varied learning paces and allows for modular studying.
  • Question: What are the key takeaways from reading this book?

    Answer: Key takeaways from 'Data Engineering with AWS' include a solid understanding of AWS data architecture, the ability to design and implement data transformation pipelines, and practical hands-on experience with real-world projects. You'll also gain insights into best practices for data modeling, data governance, and optimizing for cost and performance on AWS.
  • Question: How often is this book updated or revised?

    Answer: The book is periodically updated to reflect the latest developments in AWS services and data engineering practices. Knowledge in cloud technology evolves rapidly, and the author aims to keep the content relevant and aligned with current trends. Readers are encouraged to check online resources or the author's page for any supplemental materials or updates.
  • Question: Can this book help me prepare for AWS certifications?

    Answer: Yes, this book provides a solid foundation for AWS certification related to data engineering and analytics, particularly the AWS Certified Data Analytics and AWS Certified Solutions Architect. The insights and practical experiences outlined will enhance your knowledge, making you better prepared for certification exams and practical applications within the AWS environment.
  • Question: Where can I buy 'Data Engineering with AWS' in Monaco?

    Answer: You can purchase 'Data Engineering with AWS' at Ubuy, a popular online marketplace. Ubuy provides a convenient shopping experience, allowing you to easily browse through the available options and make your purchase securely. With user-friendly navigation, you can quickly find the book and have it delivered directly to your location.

Data Modeling & Design Editorial Review

Data Engineering with AWS: Learn how to design and build cloud-based data transformation pipelines using AWS is an excellent resource for both beginners and intermediate users in the field of data engineering. The book effectively breaks down complex topics related to data ingestion, transformation, and consumption into digestible sections presented in an organized manner. Readers appreciate the clear explanations of key analytics services, making it easier for them to grasp the necessary concepts without feeling overwhelmed. The hands-on examples provided throughout the book enhance the learning experience, allowing readers to apply what they've learned in real-world scenarios. Overall, it is a practical guide for anyone looking to enhance their skills in AWS data engineering, particularly valuable for those new to the field or transitioning into cloud-based data solutions.

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Pros

  • Comprehensive coverage of AWS data engineering concepts
  • Hands-on examples simplify complex topics
  • Well-structured for easy understanding
  • Solid introduction to data pipeline architecture
  • Useful for both beginners and intermediate learners

Cons

  • May not offer enough depth for AWS certification preparation

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