The Definitive Guide to Azure Data Engineering: Modern Elt, Devops, and Analytics on the Azure Cloud Platform

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Part I. Getting Started1. The Tools and Pre-Requisites2. Data Factory vs SSIS vs Databricks3. Design a Data Lake Storage Gen2 Account
Part II. Azure Data Factory for ELT4. Dynamically Load SQL Database to Data Lake Storage Gen 25. Use COPY INTO to Load Synapse Analytics Dedicated SQL Pool6. Load Data Lake Storage Gen2 Files into Synapse Analytics Dedicated SQL Pool7. Create and Load Synapse Analytics Dedicated SQL Pool Tables Dynamically8. Build Custom Logs in SQL Database for Pipeline Activity Metrics9. Capture Pipeline Error Logs in SQL Database10. Dynamically Load Snowflake Data Warehouse11. Mapping Data Flows for Data Warehouse ETL 12. Aggregate and Transform Big Data Using Mapping Data Flows13. Incrementally Upsert Data14. Loading Excel Sheets into Azure SQL Database Tables15. Delta Lake
Part III. Real-Time Analytics in Azure16. Stream Analytics Anomaly Detection17. Real-time IoT Analytics Using Apache Spark 18. Azure Synapse Link for Cosmos DB
Part IV. DevOps for Continuous Integration and Deployment 19. Deploy Data Factory Changes 20. Deploy SQL Database
Part V. Advanced Analytics21. Graph Analytics Using Apache Spark's GraphFrame API22. Synapse Analytics Workspaces23. Machine Learning in Databricks
Part VI. Data Governance24. Purview for Data Governance