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Chapter 1: Understanding the Databricks Data Engineer Professional Role

Chapter 2: Databricks Lakehouse Platform Overview

Chapter 3: Delta Lake Deep Dive: Transaction Log, Concurrency, and Clone

Chapter 4: Delta Lake Indexing: Partitioning, Z-Ordering, Bloom Filters, and File Sizes

Chapter 5: Optimizing Tables for Databricks SQL Service

Chapter 6: Partitioning Strategies and Best Practices

Chapter 7: Batch vs. Incremental Data Processing in Spark

Chapter 8: Partition Hints: Coalesce, Repartition, Repartition by Range, and Rebalance

Chapter 9: Controlling File Size When Writing PySpark DataFrames

Chapter 10: Type 1 Updates and Patterns for Updating Spark Tables

Chapter 11: Structured Streaming in Databricks: Design Patterns and State Tuning

Chapter 12: Stream-Static Joins and Delta Lake: Practical Implementations

Chapter 13: Deduplication in Streaming Workloads

Chapter 14: Leveraging Change Data Feed (CDF) for CDC Pipelines

Chapter 15: Deleting and Archiving Data in Delta Lake

Chapter 16: Performance Pitfalls: Tiny Files, Over-Partitioning, and Scanning Overhead

Chapter 17: Data Modeling for Lakehouse: Bronze, Silver, and Gold Layers

Chapter 18: Multiplex Bronze Tables: Streaming Design and Productionalization

Chapter 19: Shallow vs. Deep Clones in Delta Lake

Chapter 20: Enforcing Data Quality: Constraints, Foreign Keys, and Bad Data Prevention

Chapter 21: Implementing Slowly Changing Dimensions (SCD) Types 0, 1, and 2

Chapter 22: Security & Governance: Creating Dynamic Views and Data Masking

Chapter 23: Row-Level and Column-Level Access Controls

Chapter 24: Monitoring & Logging: Spark UI, Ganglia UI, and Cluster UI

Chapter 25: Analyzing Event Timelines and Metrics for Cluster Performance

Chapter 26: Maintaining Cost and Latency SLAs in Production Streaming Jobs

Chapter 27: Deploying and Monitoring Batch and Streaming Jobs

Chapter 28: Testing & Deployment: Repairing and Rerunning Failed Jobs

Chapter 29: Managing Dependencies: Python Files, Wheels, and Databricks Notebooks

Chapter 30: Multi-Task Jobs: Dependencies, Scheduling, and CRON

Chapter 31: Configuring the Databricks CLI for Workspace and Cluster Operations

Chapter 32: Executing REST API Commands for Job Cloning, Triggers, and Outputs

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