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Microsoft DP-200 Exam Reference
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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:
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.
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.
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.
Microsoft offers useful preparation options for the individuals who are planning to start their journey with this provider. Thus, for the Microsoft DP-200 exam, you can go for the following resources:
Using the study guides is what you need to do by all means. They help you cover the details of the exam content, its topics, and the information related to the format of the test. You can search for the options offered by Microsoft or look for the ones that are available on Amazon. For example, you can buy Azure Storage, Streaming, and Batch Analytics: A guide for data engineers by Richard L. Nuckolls or Hands-On Data Warehousing with Azure Data Factory by Christian Coté.
There are 8 learning paths in total that you can follow to learn the details of the exam content. Each path has several modules to cover. Thus, you can go for Store Data in Azure, Azure for the Data Engineer, Work with NoSQL Data in Azure Cosmos DB, Work with Relational Data in Azure, Implement a Data Streaming Solution with Azure Streaming Analytics, Large-Scale Data Processing, Implement a Data Warehouse with Azure Synapse Analytics, and Data Engineering with Azure Databricks.
As for the courses with an instructor, you can go for the Implementing an Azure Data Solution training. There are the options that include the classroom training and virtual courses. The time for each session is based on the location of the course.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-200.aspx
| Section | Weight | Objectives |
|---|---|---|
| Implement data storage solutions | 40-45% | - Implement Azure Synapse Analytics - Implement security requirements for data storage - Implement data retention policies - Implement Azure Cosmos DB - Implement storage accounts |
| Manage and develop data processing | 25-30% | - Transform data with Azure Databricks - Ingest data with Azure Data Factory - Ingest streaming data with Azure Stream Analytics - Orchestrate data processing activities - Implement data processing security |
| Monitor and optimize data solutions | 30-35% | - Troubleshoot data storage issues - Monitor data storage and data processing - Optimize performance of data solutions - Manage disaster recovery - Troubleshoot data processing issues |
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