<p> Chapter 1: Stage 1: Source</p> <p>Chapter 2: Starting with Source Data</p> <p>Chapter 3: The Need to Replicate Source Data</p> <p>Chapter 4: Source Data Best Practices</p> <p>Chapter 5: Stage 2: Data Lake</p> <p>Chapter 6: Why Build a Data Lake</p> <p>Chapter 7: Choosing an Engine for the Data Lake</p> <p>Chapter 8: Extract and Load (EL) a Lake</p> <p>Chapter 9: Data Lake Security</p> <p>Chapter 10: Data Lake Maintenance</p> <p>Chapter 11: Stage 3: Data Warehouse</p> <p>Chapter 12: The Power of Layers and Views</p> <p>Chapter 13: Staging Schemas</p> <p>Chapter 14: Model data with dbt</p> <p>Chapter 15: Deploy Modeling Code</p> <p>Chapter 16: Implementing the Data Warehouse</p> <p>Chapter 17: Managing Data Access </p> <p>Chapter 18: Maintaining the Source of Truth</p> <p>Chapter 19: Stage 4: Data Marts</p> <p>Chapter 20: Data Mart Implementation</p> <p>Chapter 21: Data Mart Maintenance</p> <p>Chapter 22: What's Changed</p> <p>Chapter 23: Row vs Column Oriented Database</p> <p>Chapter 24: Style Guide Example</p> <p>Chapter 25: Building an SST Example</p> <p>Acknowledgments</p> <p>Index</p> <p> </p>
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