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Chapter 1: Design and implement data storage-Implement a partition strategy-Implement a partition strategy for files
Chapter 2: Design and implement data storage-Implement a partition strategy-Implement a partition strategy for analytical workloads
Chapter 3: Design and implement data storage-Implement a partition strategy-Implement a partition strategy for streaming workloads
Chapter 5: Design and implement data storage-Implement a partition strategy-Identify when partitioning is needed in Azure Data Lake Storage Gen2
Chapter 6: Design and implement data storage-Design and implement the data exploration layer-Create and execute queries by using a compute solution that leverages SQL serverless and Spark clusters
Chapter 7: Design and implement data storage-Design and implement the data exploration layer-Recommend and implement Azure Synapse Analytics database templates
Chapter 8: Design and implement data storage-Design and implement the data exploration layer-Push new or updated data lineage to Microsoft Purview
Chapter 9: Design and implement data storage-Design and implement the data exploration layer-Browse and search metadata in Microsoft Purview Data Catalog
Chapter 10: Develop data processing -Ingest and transform data-Design and implement incremental data loads
Chapter 12: Develop data processing -Ingest and transform data-Transform data by using Transact-SQL (T-SQL) in Azure Synapse Analytics
Chapter 13: Develop data processing -Ingest and transform data-Ingest and transform data by using Azure Synapse Pipelines or Azure Data Factory
Chapter 14: Develop data processing -Ingest and transform data-Transform data by using Azure Stream Analytics
Chapter 15: Develop data processing -Ingest and transform data-Cleanse data
Chapter 16: Develop data processing -Ingest and transform data-Handle duplicate data
Chapter 17: Develop data processing -Ingest and transform data-Avoiding duplicate data by using Azure Stream Analytics Exactly Once Delivery
Chapter 18: Develop data processing -Ingest and transform data-Handle missing data
Chapter 19: Develop data processing -Ingest and transform data-Handle late-arriving data
Chapter 21: Develop data processing -Ingest and transform data-Shred JSON
Chapter 22: Develop data processing -Ingest and transform data-Encode and decode data
Chapter 23: Develop data processing -Ingest and transform data-Configure error handling for a transformation
Chapter 24: Develop data processing -Ingest and transform data-Normalize and denormalize data
Chapter 25: Develop data processing -Ingest and transform data-Perform data exploratory analysis
Chapter 26: Develop data processing-Develop a batch processing solution-Develop batch processing solutions by using Azure Data Lake Storage Gen2, Azure Databricks, Azure Synapse Analytics, and Azure Data Factory
Chapter 27: Develop data processing-Develop a batch processing solution-Use PolyBase to load data to a SQL pool
Chapter 28: Develop data processing-Develop a batch processing solution-Implement Azure Synapse Link and query the replicated data
Chapter 30: Develop data processing-Develop a batch processing solution-Scale resources
Chapter 31: Develop data processing-Develop a batch processing solution-Configure the batch size
Chapter 32: Develop data processing-Develop a batch processing solution-Create tests for data pipelines
Chapter 33: Develop data processing-Develop a batch processing solution-Integrate Jupyter or Python notebooks into a data pipeline
Chapter 35: Develop data processing-Develop a batch processing solution-Revert data to a previous state
Chapter 36: Develop data processing-Develop a batch processing solution-Configure exception handling
Chapter 37: Develop data processing-Develop a batch processing solution-Configure batch retention
Chapter 39: Develop data processing-Develop a stream processing solution-Create a stream processing solution by using Stream Analytics and Azure Event Hubs
Chapter 42: Develop data processing-Develop a stream processing solution-Handle schema drift
Chapter 43: Develop data processing-Develop a stream processing solution-Process time series data
Chapter 44: Develop data processing-Develop a stream processing solution-Process data across partitions
Chapter 45: Develop data processing-Develop a stream processing solution-Process within one partition
Chapter 46: Develop data processing-Develop a stream processing solution-Configure checkpoints and watermarking during processing
Chapter 47: Develop data processing-Develop a stream processing solution-Scale resources
Chapter 49: Develop data processing-Develop a stream processing solution-Optimize pipelines for analytical or transactional purposes
Chapter 50: Develop data processing-Develop a stream processing solution-Handle interruptions
Chapter 53: Develop data processing-Develop a stream processing solution-Replay archived stream data
Chapter 56: Develop data processing-Manage batches and pipelines-Handle failed batch loads
Chapter 57: Develop data processing-Manage batches and pipelines-Validate batch loads
Chapter 58: Develop data processing-Manage batches and pipelines-Manage data pipelines in Azure Data Factory or Azure Synapse Pipelines
Chapter 60: Develop data processing-Manage batches and pipelines-Implement version control for pipeline artifacts
Chapter 61: Develop data processing-Manage batches and pipelines-Manage Spark jobs in a pipeline
Chapter 62: Secure, monitor, and optimize data storage and data processing-Implement data security-Implement data masking
Chapter 63: Secure, monitor, and optimize data storage and data processing-Implement data security-Encrypt data at rest and in motion
Chapter 64: Secure, monitor, and optimize data storage and data processing-Implement data security-Implement row-level and column-level security
Chapter 66: Secure, monitor, and optimize data storage and data processing-Implement data security-Implement POSIX-like access control lists (ACLs) for Data Lake Storage Gen2
Chapter 67: Secure, monitor, and optimize data storage and data processing-Implement data security-Implement a data retention policy
Chapter 70: Secure, monitor, and optimize data storage and data processing-Implement data security-Load a DataFrame with sensitive information
Chapter 71: Secure, monitor, and optimize data storage and data processing-Implement data security-Write encrypted data to tables or Parquet files
Chapter 72: Secure, monitor, and optimize data storage and data processing-Implement data security-Manage sensitive information
Chapter 73: Secure, monitor, and optimize data storage and data processing-Monitor data storage and data processing-Implement logging used by Azure Monitor
Chapter 74: Secure, monitor, and optimize data storage and data processing-Monitor data storage and data processing-Configure monitoring services
Chapter 75: Secure, monitor, and optimize data storage and data processing-Monitor data storage and data processing-Monitor stream processing
Chapter 76: Secure, monitor, and optimize data storage and data processing-Monitor data storage and data processing-Measure performance of data movement
Chapter 77: Secure, monitor, and optimize data storage and data processing-Monitor data storage and data processing-Monitor and update statistics about data across a system
Chapter 78: Secure, monitor, and optimize data storage and data processing-Monitor data storage and data processing-Monitor data pipeline performance
Chapter 79: Secure, monitor, and optimize data storage and data processing-Monitor data storage and data processing-Measure query performance
Chapter 80: Secure, monitor, and optimize data storage and data processing-Monitor data storage and data processing-Schedule and monitor pipeline tests
Chapter 81: Secure, monitor, and optimize data storage and data processing-Monitor data storage and data processing-Interpret Azure Monitor metrics and logs
Chapter 82: Secure, monitor, and optimize data storage and data processing-Monitor data storage and data processing-Implement a pipeline alert strategy
Chapter 83: Secure, monitor, and optimize data storage and data processing-Optimize and troubleshoot data storage and data processing-Compact small files
Chapter 84: Secure, monitor, and optimize data storage and data processing-Optimize and troubleshoot data storage and data processing-Handle skew in data
Chapter 85: Secure, monitor, and optimize data storage and data processing-Optimize and troubleshoot data storage and data processing-Handle data spill
Chapter 87: Secure, monitor, and optimize data storage and data processing-Optimize and troubleshoot data storage and data processing-Tune queries by using indexers
Chapter 88: Secure, monitor, and optimize data storage and data processing-Optimize and troubleshoot data storage and data processing-Tune queries by using cache
Chapter 89: Secure, monitor, and optimize data storage and data processing-Optimize and troubleshoot data storage and data processing-Troubleshoot a failed Spark job
Chapter 90: Secure, monitor, and optimize data storage and data processing-Optimize and troubleshoot data storage and data processing-Troubleshoot a failed pipeline run, including activities executed in external services

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