Data Engineering on Microsoft Azure Training

Duration

4 days.

Prerequisites

Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.
Specifically completing:

• AZ-900 - Azure Fundamentals
• DP-900 - Microsoft Azure Data Fundamentals

Skills Gained

After completing this course, students will be able to:

• Explore compute and storage options for data engineering workloads in Azure
• Run interactive queries using serverless SQL pools
• Perform data Exploration and Transformation in Azure Databricks
• Explore, transform, and load data into the Data Warehouse using Apache Spark
• Ingest and load Data into the Data Warehouse
• Transform Data with Azure Data Factory or Azure Synapse Pipelines
• Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines
• Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
• Perform end-to-end security with Azure Synapse Analytics
• Perform real-time Stream Processing with Stream Analytics
• Create a Stream Processing Solution with Event Hubs and Azure Databricks

Who Can Benefit?

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.