In this Azure Data Engineering training course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.
Azure Data Engineering Training Delivery Methods
- In-Person
- Online
Azure Data Engineering Training Information
In this course, you will learn how 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.
Training Prerequisites
Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. Specifically completing:
- Global Reach Academy course 8566, Microsoft Azure Fundamentals Training (AZ-900T00)
- Global Reach Academy course 8586, Microsoft Azure Data Fundamentals Training (DP-900)
Certification Information
This class does prepare an individual to take the Microsoft Certified Exam DP-203.
Azure Data Engineering Training Outline
Lessons:
