Data Engineering on Microsoft Azure (DP-203)
Course Overview

In this course, you will learn about the data engineering patterns and practices as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Begin by understanding the core compute and storage technologies that are used to build an analytical solution. You will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files. You will learn how to interactively explore data stored in files in a data lake. You will also 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.

Additionally, comprehend the various ways you can transform the data using the same technologies that are used to ingest data. You will spend time on the course learning how to monitor and analyze the performance of analytical system so that you can optimize the performance of data loads, or queries that are issued against the systems. You will understand the importance of implementing security to ensure that the data is protected at rest or in transit. You will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics.








4 Day(s)




Microsoft Certified: Azure Data Engineer Associate

Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. Specifically completing:
Azure Fundamentals (AZ-900) AND Microsoft Azure Data Fundamentals (DP-900)

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