Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines.
The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit.
The student will then show how to create a real-time analytical system to create real-time analytical solutions.

• 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

• Continue learning and face new challenges with after-course one-on-one instructor coaching