The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course data analysts and data scientists who work with analytical solutions built on Microsoft Azure.
1 - Explore compute and storage options for data engineering workloads
2 - Run interactive queries using Azure Synapse Analytics serverless SQL pools
3 - Data exploration and transformation in Azure Databricks
4 - Explore, transform, and load data into the Data Warehouse using Apache Spark
5 - Ingest and load data into the data warehouse
6 - Transform data with Azure Data Factory or Azure Synapse Pipelines
7 - Orchestrate data movement and transformation in Azure Synapse Pipelines
8 - End-to-end security with Azure Synapse Analytics
9 - Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
10 - Real-time Stream Processing with Stream Analytics
11 - Create a Stream Processing Solution with Event Hubs and Azure Databricks
Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.
Specifically completing: