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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:
- 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.
- 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.
Who should take the DP-200 exam
The Implementing an Azure Data Solution (beta) DP-200 Exam certification is an internationally-recognized validation that identifies persons who earn it as possessing skilled as a Microsoft Certified Azure Data Engineer Associate. If candidates want significant improvement in career growth needs enhanced knowledge, skills, and talents. Implementing an Azure Data Solution (beta) DP-200 Exam certification provides proof of this advanced knowledge and skill. If a candidate has knowledge of associated technologies and skills that are required to pass Implementing an Azure Data Solution (beta) DP-200 Exam then he should take this exam.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-200.aspx
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Microsoft DP-200 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Implement Data Storage Solutions (40-45%) | |
| Implement non-relational data stores | - implement a solution that uses Cosmos DB, Data Lake Storage Gen2, or Blob storage -implement data distribution and partitions -implement a consistency model in Cosmos DB -provision a non-relational data store -provide access to data to meet security requirements -implement for high availability, disaster recovery, and global distribution |
| Implement relational data stores | -provide access to data to meet security requirements -implement for high availability and disaster recovery -implement data distribution and partitions for Azure Synapse Analytics -implement PolyBase |
| Manage data security | -implement data masking -encrypt data at rest and in motion |
Manage and Develop Data Processing (25-30%) | |
| Develop batch processing solutions | -develop batch processing solutions by using Data Factory and Azure Databricks -ingest data by using PolyBase -implement the integration runtime for Data Factory -create linked services and datasets -create pipelines and activities -create and schedule triggers -implement Azure Databricks clusters, notebooks, jobs, and autoscaling -ingest data into Azure Databricks |
| Develop streaming solutions | -configure input and output -select the appropriate built-in functions -implement event processing by using Stream Analytics |
Monitor and Optimize Data Solutions (30-35%) | |
| Monitor data storage | -monitor relational and non-relational data stores -implement Blob storage monitoring -implement Data Lake Storage Gen2 monitoring -implement Azure Synapse Analytics monitoring -implement Cosmos DB monitoring -configure Azure Monitor alerts -implement auditing by using Azure Log Analytics |
| Monitor data processing | -monitor Data Factory pipelines - monitor Azure Databricks -monitor Stream Analytics -configure Azure Monitor alerts -implement auditing by using Azure Log Analytics |
| Optimize of Azure data solutions | -troubleshoot data partitioning bottlenecks - optimize Data Lake Storage Gen2 -optimize Stream Analytics -optimize Azure Synapse Analytics -manage the data lifecycle |
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