In this course, the students will implement various data platform technologies into solutions that are in line with business and technical requirements including on-premises, cloud, and hybrid data scenarios incorporating both relational and No-SQL data. They will also learn how to process data using a range of technologies and languages for both streaming and batch data.
The students will also explore how to implement data security including authentication, authorization, data policies and standards. They will also define and implement data solution monitoring for both the data storage and data processing activities. Finally, they will manage and troubleshoot Azure data solutions which includes the optimization and disaster recovery of big data, batch processing and streaming data solutions.
The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about the data platform technologies that exist on Microsoft Azure.
The secondary audience for this course is individuals who develop applications that deliver content from the data platform technologies that exist on Microsoft Azure.
This course contains these themes and modules:
Module 1: Azure for the Data Engineer
Module 2: Working with Data Storage
Module 3: Enabling Team Based Data Science with Azure Databricks
Module 4: Building Globally Distributed Databases with Cosmos DB
Module 5: Working with Relational Data Stores in the Cloud
Module 6: Performing Real-Time Analytics with Stream Analytics
Module 7: Orchestrating Data Movement with Azure Data Factory
Module 8: Securing Azure Data Platforms
Module 9: Monitoring and Troubleshooting Data Storage and Processing
Module 10: Integrating and Optimizing Data Platforms
This course will help you prepare for exam DP-200: Implementing an Azure Data Solution
Exam DP-200 (together with exam DP-201) leads to the new certification: Microsoft Certified: Azure Data Engineer Associate
The exam fee is not included in the course price.