DP-200 Exam Study Guide (Implementing Azure Data Solution)
You can access DP-200 Exam Microsoft official page here
Preparing for the DP-200 Implementing an Azure Data Solution exam? Don’t know where to start? This post is the DP-200 Certificate Study Guide, which helps you to achieve the Azure Data Engineer Associate Certification.
I have curated a list of articles from Microsoft documentation for each objective of the DP-200 exam. Please share the post within your circles so it helps them to prepare for the exam.
DP-203 will replace both DP-201 and DP-200 in the coming months.
Skills Measured
- Implement Data Storage Solutions (40-45%)
- Manage and Develop Data Processing (25-30%)
- Monitor and Optimize Data Solutions (30-35%)
DP-200 Exam Free Study Guide
For each test objective, I’ve compiled a thorough collection of articles from Microsoft documentation. Please feel free to forward this page to your friends and coworkers in order to assist them in preparing for the test .
Implement Data Storage Solutions (40-45%)
Implement Non-relational Data Stores
- Implement a solution that uses Cosmos DB
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Create an Azure Cosmos account
Implement a solution that uses Blob storage
Host a static website on Blob storage
Implement a solution that uses Data Lake Storage Gen2
Load data into Azure Data Lake Storage Gen2 with ADF
Implement data distribution
Distribute your data globally with Azure Cosmos DB
Implement data partitions
Partitioning & horizontal scaling in Azure Cosmos DB
Implement a consistency model in CosmosDB
Choose the right consistency level for your Azure Cosmos DB
Provision of a non-relational datastore
Create Azure Cosmos account, database, container & items from Azure portal
Provide access to data to meet security requirements
Secure access to data in Azure Cosmos DB
Implement for high availability
- Azure Cosmos DB global distribution using the SQL API
- Implement for disaster recovery
- Online backup & on-demand data restore in Azure Cosmos DB
- Implement for global distribution
- Set up Azure Cosmos DB global distribution
Implement Relational Data Stores
- Provide access to data to meet security requirements
- Secure a database in Azure SQL Database
- Implement for high availability and disaster recovery
- Configuring Resilient Azure Databases High Availability
- Data Strategies for Disaster Recovery
- Implement data distribution and partitions for Azure Synapse Analytics
- Implement a geo-distributed database: Azure SQL Database
- Partitioning tables in Synapse SQL pool
- Guidance: Designing distributed tables in Synapse SQL pool
- Implement PolyBase
- Load data to Azure Synapse Analytics SQL pool
Manage Data Security
- Implement data masking
- Dynamic data masking for Azure Synapse Analytics
- Encrypt data at rest
- Transparent Data Encryption (TDE) in Azure Synapse Analytics
- Encrypt data in motion
- Transport Layer Security (Encryption-in-transit)
- Create a site-to-site connection in the Azure portal
Manage and Develop Data Processing (25-30%)
Develop Batch Processing Solutions
- Develop batch processing solutions by using Data Factory and Azure Databricks
- Batch processing with data factory and data bricks
- Ingest data by using PolyBase
- Develop batch processing with polybase
- Implement the integration runtime for Data Factory
- How to create & configure Azure Integration Runtime
- Check this video for Azure SSIS Integration Runtime – demo
- Implement Copy Activity within Azure Data Factory
- Copy activity in Azure Data Factory
- Create linked services and datasets
- Create a linked service
- Create datasets
- Create pipelines and activities
- Creating pipelines with activities
- Create a pipeline
- Implement Mapping Data Flows in Azure Data Factory
- Mapping data flows in Azure Data Factory
- Create and schedule triggers
- Create Schedule Triggers in Azure Data Factory
- Implement Azure Databricks clusters, notebooks, jobs, and autoscaling
- Azure Databricks Cluster, Notebooks, Jobs
- Cluster size and autoscaling
- Ingest data into Azure Databricks
- Extract, transform & load data by using Azure Databricks
Develop Streaming Solutions
- Configure input and output
- Stream data as input into Stream Analytics
- Azure Stream Analytics output to Azure Cosmos DB
- Select the appropriate built-in functions
- Introduction to Stream Analytics windowing functions
- Implement event processing using Stream Analytics
- Understanding Complex Event Processing & Azure Stream Analytics
Monitor and Optimize Data Solutions (30-35%)
Monitor Data Storage
- Monitor relational and non-relational data stores
-
Microsoft Azure Database monitoring playbook
Implement BLOB storage monitoring
Monitor a storage account in the Azure portal
Implement Data Lake Storage Gen2 monitoring
Monitoring considerations for Data Lake Storage Gen2
Monitoring Azure Data Lake Store
Implement Azure Synapse Analytics monitoring
Accessing diagnostic logs for Azure Data Lake Storage Gen1
Implement Cosmos DB monitoring
Configure Azure Monitor alerts
Create, view & manage metric alerts using Azure Monitor
Implement auditing by using Azure Log Analytics
Monitor Data Processing
- Monitor Data Factory pipelines
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Monitor & Alert Data Factory by using Azure Monitor
Monitor Azure Databricks
Monitor Databricks with Azure Monitor
Monitor stream analytics
Monitor & manage Stream Analytics jobs with Azure PowerShell cmdlets
Configure Azure Monitor Alerts
- Create alerts for Azure SQL Database & Azure Synapse Analytics
- Implement Auditing by using Azure Log Analytics
- Auditing for Azure SQL Database & Azure Synapse Analytics
Optimize Azure Data Solutions
- Troubleshoot data partitioning bottlenecks
- Data partitioning strategies
- Optimize Data Lake Storage Gen2
- Optimize Azure Data Lake Storage Gen2 for performance
- Optimize Stream Analytics
- Leverage query parallelization in Azure Stream Analytics
- Optimize Azure Synapse Analytics
- Best practices for Synapse SQL pool in Azure Synapse Analytics
- Manage the data life cycle
- Manage the Azure Blob storage lifecycle
That’s it! This completes the DP-200 Implementing an Azure Data Solution Certification Study Guide.
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