Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
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Practical Statistics for Data Scientists, 2e: 50+ Essential Concepts Using R and Python
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The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition
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R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
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Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
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Python All-in-One For Dummies (For Dummies: Learning Made Easy)
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Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh
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SQL for Data Analysis: Advanced Techniques for Transforming Data into Insights
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Data Modeling with Microsoft Power Bi: Self-Service and Enterprise Dwh with Power Bi
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SQL Pocket Guide: A Guide to SQL Usage
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