Madell At 201 D
Candidates for this exam are Microsoft Azure data engineers who collaborate with business stakeholders to identify and meet the data requirements to design data solutions that use Azure data services...
Azure data engineers are responsible for>Exam DP-201: Designing an Azure Data Solution
Purpose This study examined the head orientation of young children in naturalistic settings and the acoustics of their everyday environments for quantifying the potential effects of directionality. Method Twenty-seven children (11 with normal hearing, 16 with impaired hearing) between 11 and 78 months of age were video recorded in naturalistic settings for analyses of head orientation.
Languages: English
This exam measures your ability to accomplish the following technical tasks: design Azure data storage solutions; design data processing solutions; and design for data security and compliance.
Exam DP-201 Update Summary
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This exam has been refocused to differentiate the data engineer from a database administrator, emphasizing the data engineer’s proficiency in designing solutions for data storage in varying forms, structures, and purpose.
Updated content areas (effective June 21, 2019)
- Reorganized design of data storage solutions to two key categories: relational and non-relational cloud data stores
- Removed focus on HDInsight
- Reduced focus on Hybrid data scenarios
- Referenced authentication and authorization as applicable
- Referenced data policies and standards as applicable
- Referenced notifications as applicable
For more details, download the DP-201 change document (Adobe Acrobat PDF).
Madell At 201 D Instructions
Design Azure data storage solutions (40-45%)
Recommend an Azure Data solution based on requirements
- choose the correct data storage solution to meet the technical and business requirements
- choose the partition distribution type
Madell At201d
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
Ghost of the past song. Design relational cloud data stores
- design data distribution and partitions
- design for scale, including multi-region, latency, and throughput
- design a solution that uses SQL Database and SQL Data Warehouse
- design a disaster recovery strategy
- design for high availability
Design data processing solutions (25-30%)
Design batch processing solutions
- design batch processing solutions by using 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
- 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 for 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
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DownloadMicrosoft Certified: Azure Data Engineer Associate
Azure Data Engineers design and implement the management, monitoring, security, and privacy of data using the full stack of Azure data services to satisfy business needs.
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