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Practical Data Engineering with Apache Projects: Solving Everyday Data Challenges with Spark, Iceberg, Kafka, Flink, and More
English | 2026 | ISBN: B0FQM9X1VSc | 251 pages | PDF | 6.4 MB
This book is a comprehensive guide designed to equip you with the practical skills and knowledge necessary to tackle real-world data challenges using Open Source solutions. Focusing on 10 real-world data engineering projects, it caters specifically to data engineers at the early stages of their careers, providing a strong foundation in essential open source tools and techniques such as Apache Spark, Flink, Airflow, Kafka, and many more.
Each chapter is dedicated to a single project, starting with a clear presentation of the problem it addresses. You will then be guided through a step-by-step process to solve the problem, leveraging widely-used open-source data tools. This hands-on approach ensures that you not only understand the theoretical aspects of data engineering but also gain valuable experience in applying these concepts to real-world scenarios.
At the end of each chapter, the book delves into common challenges that may arise during the implementation of the solution, offering practical advice on troubleshooting these issues effectively. Additionally, the book highlights best practices that data engineers should follow to ensure the robustness and efficiency of their solutions. A major focus of the book is using open-source projects and tools to solve problems encountered in data engineering.
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