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