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Data Engineering: A Practical Beginner’s Guide to Designing Reliable Data Pipelines, Warehouses, and Analytics Systems-logo

Data Engineering: A Practical Beginner’s Guide to Designing Reliable Data Pipelines, Warehouses, and Analytics Systems

Martin Schaefer

Transform chaotic spreadsheets into reliable data pipelines with this essential guide to modern data engineering. Perfect for your morning commute or focused study sessions, this empowering narrative demystifies how raw information becomes trustworthy...

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Opening Credits

1/11/2026
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Chapter 1: From Messy Spreadsheets to Data Systems

1/11/2026
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Chapter 2: Thinking in Data Flows and Systems

1/11/2026
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Chapter 3: Designing Useful Data Models

1/11/2026
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Chapter 4: Batch versus Streaming How Data Moves

1/11/2026
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Chapter 5: Databases, Warehouses, and Data Lakes

1/11/2026
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Chapter 6: Files, Formats, and Organizing the Lake

1/11/2026
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Chapter 7: Building Reliable Data Pipelines and Workflows

1/11/2026
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Chapter 8: Data Quality, Testing, and Observability

1/11/2026
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Chapter 9: Governance, Security, and Designing for Scale

1/11/2026
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Chapter 10: End to End Architectures and Your Path into Data Engineering

1/11/2026
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Closing Credits

1/11/2026