Data Engineering Design Patterns: Recipes for Solving the Most Common Data Engineering Problems-finelybook

Data Engineering Design Patterns: Recipes for Solving the Most Common Data Engineering Problems

Author: Bartosz Konieczny

Publisher finelybook 出版社:‏ ‎ O’Reilly Media

Edition 版本:‏ 1st edition

Publication Date 出版日期:‏ 2025-05-20

Language 语言: English

Print Length 页数: 372 pages

ISBN-10: 1098165810

ISBN-13: 9781098165819

Book Description

Data projects are an intrinsic part of an organization’s technical ecosystem, but data engineers in many companies continue to work on problems that others have already solved. This hands-on guide shows you how to provide valuable data by focusing on various aspects of data engineering, including data ingestion, data quality, idempotency, and more.

Author Bartosz Konieczny guides you through the process of building reliable end-to-end data engineering projects, from data ingestion to data observability, focusing on data engineering design patterns that solve common business problems in a secure and storage-optimized manner. Each pattern includes a user-facing description of the problem, solutions, and consequences that place the pattern into the context of real-life scenarios.

Throughout this journey, you’ll use open source data tools and public cloud services to apply each pattern. You’ll learn:

Challenges data engineers face and their impact on data systems
How these challenges relate to data system components
Useful applications of data engineering patterns
How to identify and fix issues with your current data components
TTechnology-agnostic solutions to new and existing data projects, with open source implementation examples
Bartosz Konieczny is a freelance data engineer who’s been coding since 2010. He’s held various senior hands-on positions that allowed him to work on many data engineering problems in batch and stream processing.

About the Author

Bartosz is a freelance data engineer enthusiast who has been coding since 2010. He has held various senior hands-on positions that helped him work on many data engineering problems, such as sessionization, data ingestion, data cleansing, ordered data processing, or data migration. He enjoys solving data challenges with public cloud services and Open Source technologies, especially Apache Spark, Apache Kafka, Apache Airflow, and Delta Lake. You can contact him at contact@waitingforcode.com.

Besides that, you can read his blog posts at waitingforcode.com, or improve your data engineering skills with one of his courses or training. Bartosz is also an occasional speaker at conferences and meetups, including Data+AI Summit, Big Data Technology Warsaw Summit, or NDC Porto.

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PDF, (conv), EPUB | 14 MB | 2025-04-19

Data Engineering Design Patterns: Recipes for Solving the Most Common Data Engineering Problems