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Part I: Getting Started
Chapter 1: The Data Lakehouse Paradigm
Part II: Data Platforms
Chapter 2: Snowflake
Chapter 3: Databricks
Chapter 4: Synapse Analytics
Part III: Apache Spark ELT
Chapter 5: Pipelines and Jobs
Chapter 6: Notebook Code
Part IV: Delta Lake.-Chapter 7: Schema Evolution
Chapter 8: Change Feed
Chapter 9: Clones
Chapter 10: Live Tables
Chapter 11: Sharing
Part V: Optimizing Performance
Chapter 12: Dynamic Partition Pruning for Querying Star Schemas
Chapter 13: Z-Ordering & Data Skipping
Chapter 14: Adaptive Query Execution
Chapter 15: Bloom Filter Index
Chapter 16: Hyperspace
Part VI: Advanced Capabilities
Chapter 17: Auto Loader
Chapter 18: Python Wheels
Chapter 19: Security & Controls.

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