Data Engineering on Microsoft Azure

In this course, the student will learn about the data engineering as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. 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.

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Audience Profile

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.

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

Course outline

• Module 1: Azure for the Data Engineer
• Module 2: Store data in Azure
• Module 3: Data integration at scale with Azure Data Factory or Azure Synapse Pipeline
• Module 4: Realize Integrated Analytical Solutions with Azure Synapse Analytics
• Module 5: Work with Data Warehouses using Azure Synapse Analytics
• Module 6: Perform data engineering with Azure Synapse Apache Spark Pools
• Module 7: Work with Hybrid Transactional and Analytical Processing Solutions using Azure Synapse Analytics
• Module 8: Data engineering with Azure Databricks
• Module 9: Large-Scale Data Processing with Azure Data Lake Storage Gen2
• Module 10: Implement a Data Streaming Solution with Azure Stream Analytics