Data projects are an intrinsic part of an organization’s technical ecosystem, but data engineers in many companies are still trying to solve 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.

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

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