snowflake-data-engineering

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snowflake-data-engineering

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Snowflake Data Engineering in Action

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# Snowflake Data Engineering

## Part 1: Introducing Data Engineering with Snowflake
### Chapter 1: Data Engineering with Snowflake
### Chapter 2: Creating Your First Data Pipeline
## Part 2: Ingesting, Transforming, and Storing Data
### Chapter 3: Best Practices for Data Staging 
### Chapter 4: Transforming Data
### Chapter 5: Continuous Data Ingestion
### Chapter 6: Executing Code Natively with Snowpark
### Chapter 7: Augmenting Data with Outputs from Large Language Models
### Chapter 8: Optimizing Query Performance
### Chapter 9: Controlling Cost
### Chapter 10: Data Governance and Access Control
## Part 3: Building Data Pipelines
### Chapter 11: Designing Data Pipelines
### Chapter 12: Ingesting Data Incrementally
### Chapter 13: Orchestrating Data Pipelines
### Chapter 14: Testing for Data Integrity and Completeness
### Chapter 15: Data Pipeline Continuous Integration
## Appendices
### Appendix A: Configuring Your Snowflake Environment
### Appendix B: Snowflake Objects used in the Examples

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