In Data Engineering on Azure Associate course, the student will learn about the data engineering patterns and practices as it pertains to working with batch and real-time analytical solutions.
1. The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about the data platform technologies that exist on Microsoft Azure.
2. The secondary audience for this course is individuals who develop applications that deliver content from the data platform technologies that exist on Microsoft Azure.
1. Explore compute and storage options for data engineering workloads
2. Design and implement the serving layer
3. Data engineering considerations for source files
4. Run interactive queries using Azure Synapse Analytics serverless SQL pools
1. Explore, transform, and load data into the Data Warehouse using Apache Spark
2. Data exploration and transformation in Azure Databricks
3. Ingest and load data into the data warehouse
4. Transform data with Azure Data Factory or Azure Synapse Pipelines
1. Orchestrate data movement and transformation in Azure Synapse Pipelines
2. Optimize query performance with dedicated SQL pools in Azure Synapse
3. Analyze and Optimize Data Warehouse Storage
4. Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
1. End-to-end security with Azure Synapse Analytics
2. Real-time Stream Processing with Stream Analytics
3. Create a Stream Processing Solution with Event Hubs and Azure Databricks
4. Build reports using Power BI integration with Azure Synpase Analytics
5. Perform Integrated Machine Learning Processes in Azure Synapse Analytics