DP-200 Implementing an Azure Data Solution (beta)

Languages: English
Audiences: IT Professionals
Technology: Microsoft Azure

Skills measured
This exam measures your ability to accomplish the technical tasks listed below. The percentages indicate the relative weight of each major topic area on the exam. The higher the percentage, the more questions you are likely to see on that content area on the exam. View video tutorials about the variety of question types on Microsoft exams.

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Implement Data Storage Solutions (25-30%)
Implement Azure cloud data warehouses
May include but is not limited to: Design Data Lake architecture, design the data schema, provision the data warehouse
Implement No-SQL Databases
May include but is not limited to: Manage Data distribution and Partitions, select the database platform, model data storage based on use cases, select storage types, provision storage accounts, provision Data Lake storage, integrate WebHDFS applications with Data Lake Storage, provision in CosmosDB
Implement Azure SQL Database
May include but is not limited to: Provision Azure SQL Database, configure elastic pools, configure data backup strategies, configure elastic jobs, provision Azure SQL database managed instance, configure connections, manage data synchronization
Implement hybrid data scenarios
May include but is not limited to: Design hybrid solution, design data replication and synchronization
Manage Azure DevOps Pipelines
May include but is not limited to: Use a build service, deploy using Azure Resource Manager templates

Manage and Develop Data Processing (30-35%)
Implement big data environments
May include but is not limited to: Implement Hadoop clusters, implement Databricks environment
Develop batch processing solutions
May include but is not limited to: Develop batch processing solutions using Spark, develop batch processing solutions using Azure Databricks
Develop streaming solutions
May include but is not limited to: Implement event processing using Azure stream analytics, query data using Azure Stream Analytics, configure Azure Stream Analytics to read from Event Hub, configure Azure Stream Analytics to read from BLOB storage
Develop integration solutions
May include but is not limited to: Create data pipeline systems in Azure, develop data integration pipelines with Azure Data Factory, develop data integration pipelines with Azure Databricks
Implement data migration
May include but is not limited to: Transform data, bulk load data with PolyBase
Automate Data Factory Pipelines
May include but is not limited to: Deploy data factory pipelines, configure Data Factory

Manage Data Security (15-20%)
Manage source data access security
May include but is not limited to: Connect to sources, create connection objects, install Gateways
Configure authentication and authorization
May include but is not limited to: Set up firewall rules, integrate Azure AD, design Cosmos DB security, design Data Lake security, design Azure SQL DB security, manage Access Control, manage permissions on resources
Manage and enforce data policies and standards
May include but is not limited to: Mask data, encrypt data at rest, encrypt data in motion, encrypt data elements, configure audit
Set up notifications
May include but is not limited to: Set up alerts on security threats, set up alerts on unexpected resource usage

Monitoring Data Solutions (10-15%)
Monitor data storage
May include but is not limited to: Implement BLOB storage monitoring, implement Data Lake Store monitoring, implement HDInsight monitoring
Monitor databases for a specified scenario
May include but is not limited to: Implement SQL Database monitoring, implement SQL Data Warehouse monitoring, implement Cosmos DB monitoring
Monitor data processing
May include but is not limited to: Design and implement Data Factory monitoring, monitor Azure Databricks, monitor HDInsight processing, monitor stream analytics

Manage and Troubleshoot Azure Data Solutions (10-15%)
Manage Optimization
May include but is not limited to: Troubleshoot data partitioning bottlenecks, optimize HIVE processing, optimize Data Lake, optimize SPARK processing, optimize Azure Stream Analytics, optimize Data Warehouse, optimize SQL DB, manage data life cycle
Manage business continuity
May include but is not limited to: Implement a disaster recovery strategy, design for High Availability, Import and export data, design a data retention policy

Preparation options
Find classroom and online training
Explore more training on Microsoft Learn

Who should take this exam?
Candidates for this exam are Azure data engineers who are responsible for data related tasks that include ingesting, egressing, and transforming data from multiple sources using various services and tools. The Azure data engineer collaborates with business stakeholders to identify and meet data requirements while designing and implementing the management, monitoring, security, and privacy of data using the full stack of Azure services to satisfy business needs.
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