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Potential Candidates and Prerequisites
The Microsoft DP-201 exam is intended mainly for the Azure data engineers. These are the professionals who work closely with the business stakeholders in order to determine and satisfy the data requirements and design data solutions that utilize Azure data services. These specialists are also responsible for designing Azure data storage solutions that utilize relational & non-relational data stores, real-time and batch data processing solutions, as well as data security & compliance solutions.
To successfully complete the DP-201 test, the applicants should have competence in designing data solutions that utilize Azure services, including Azure SQL Database, Azure Cosmos DB, Azure Data Lake Storage, Azure Synapse Analytics, Azure Stream Analytics, Azure Data Factory, Azure Blob storage, and Azure Databricks.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-201.aspx
Microsoft DP-201 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Design Azure Data Storage Solutions (40-45%) | |
| Recommend an Azure data storage solution based on requirements | - choose the correct data storage solution to meet the technical and business requirements - choose the partition distribution type |
| Design non-relational cloud data stores | - design data distribution and partitions - design for scale (including multi-region, latency, and throughput) - design a solution that uses Cosmos DB, Data Lake Storage Gen2, or Blob storage - select the appropriate Cosmos DB API - design a disaster recovery strategy - design for high availability |
| Design relational cloud data stores | - design data distribution and partitions - design for scale (including latency and throughput) - design a solution that uses Azure Synapse Analytics - design a disaster recovery strategy - design for high availability |
Design Data Processing Solutions (25-30%) | |
| Design batch processing solutions | - design batch processing solutions that use Data Factory and Azure Databricks - identify the optimal data ingestion method for a batch processing solution - identify where processing should take place, such as at the source, at the destination, or in transit |
| Design real-time processing solutions | - design for real-time processing by using Stream Analytics and Azure Databricks - design and provision compute resources |
Design for Data Security and Compliance (25-30%) | |
| Design security for source data access | - plan for secure endpoints (private/public) - choose the appropriate authentication mechanism, such as access keys, shared access signatures (SAS), and Azure Active Directory (Azure AD) |
| Design security for data policies and standards | - design data encryption for data at rest and in transit - design for data auditing and data masking - design for data privacy and data classification - design a data retention policy - plan an archiving strategy - plan to purge data based on business requirements |
