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Design-Driven Data Engineering is a practical, end-to-end guide that teaches you how to build modern data systems by starting where it matters most: business design.

Instead of jumping straight into tools, frameworks, and cloud services, this book shows you how to think like a data architect—translating business needs into elegant data models, scalable architectures, clean pipelines, and analytics systems that deliver real value. You will learn a structured, design-first methodology that applies to every platform, whether you work with SQL databases, modern lakehouses, or fully cloud-native solutions.

Through clear explanations, examples, and actionable patterns, you will discover how to:

Use design thinking to analyze business processes, events, and data requirements
Turn business workflows into conceptual and logical data models
Design robust schemas, warehouse/lakehouse layers, and medallion architectures
Build ingestion, transformation, and orchestration pipelines that scale
Implement governance, metadata, lineage, and quality frameworks
Create semantic models for BI and analytics
Bring together databases, pipelines, cloud services, and automation into a coherent, maintainable system

Whether you are a data engineer, analytics developer, architect, or technical leader, this book provides a blueprint for designing systems that remain flexible, scalable, and resilient as your business evolves.

Design-Driven Data Engineering gives you the clarity, structure, and patterns you need to build data platforms that don’t just work—but work elegantly.

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