Microsoft DP-200 Exam Syllabus Topics:

Reference: https://www.microsoft.com/en-us/learning/exam-dp-200.aspx

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Nowadays, being an Azure Data Engineer is very popular among the IT specialists, so Microsoft DP-200 is one of the exams that are taken more than others. This test is part of the Microsoft Certified: Azure Data Engineer Associate certification, which also requires passing Microsoft DP-201.

Exam Topics and Subtopics

To be able to pass the exam, you should cover its content with great deliberation. Therefore, you need to be ready to learn a lot. Thus, Microsoft DP-200 contains the following domains that you should explore:

• Implementation of data storage solutions (40-45%)

  In this topic, a potential candidate has to know how to implement non-relational and relational data stores. It includes your ability to implement a consistency model in Cosmos DB, solutions that use Blob storage, Data Lake Storage Gen2, or Cosmos DB, as well as data distribution and partitions for Azure Synapse Analytics. Besides that, the students should have the skills in managing data security, which includes your full understanding of data encryption and data masking implementation.

• Monitoring and optimization of data solutions (30-35%)

  As for this domain, you have to know how to monitor data processing and data storage as well as optimize Azure data solutions. These include your understanding of Azure Synapse Analytics, and Stream Analytics. Your skills in implementing Cosmos DB monitoring, Azure Synapse Analytics monitoring, Blob storage monitoring, and auditing by using Azure Log Analytics will be evaluated as well. The topic also contains your knowledge of the configuration of Azure Monitor alerts, monitoring of Stream Analytics, Azure Databricks, Data Factory pipelines, as well as relational and non-relational data stores.

• Management and development of data processing (25-30%)

  This section includes two subtopics that cover the development of batch processing and streaming solutions. In these areas, you will be evaluated in creating activities and pipelines, linked services and datasets, ingesting data into Azure Databricks, selecting the appropriate built-in functions, configuring input and output, etc. The skills in implementing for high availability and disaster recovery, PolyBase, as well as data distribution and partitions for Azure Synapse Analytics are also important. Moreover, you should not avoid learning the details of the implementation for the global distribution and be able to provide access to data to meet the security requirements.