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Microsoft DP-420 Exam Syllabus Topics:

SectionWeightObjectives
Design and implement data distribution5-10%- Design and implement replication strategy
  • 1. Evaluate consistency model impacts
  • 2. Choose when to distribute data
  • 3. Define automatic failover policies
  • 4. Choose a consistency model
  • 5. Perform manual failovers
- Design and implement multi-region writes
  • 1. Choose when to use multi-region writes
  • 2. Implement conflict resolution policies
  • 3. Implement multi-region writes
Integrate an Azure Cosmos DB solution5-10%- Implement solutions across services
  • 1. Integrate Azure Functions and Event Hubs
  • 2. Use Change Feed for denormalization
  • 3. Aggregate and archive data
  • 4. Enforce referential integrity
  • 5. Implement Azure AI Search integration
- Enable analytical workloads
  • 1. Write data back from Spark
  • 2. Query analytical store from Synapse
  • 3. Configure Azure Cosmos DB Mirroring
  • 4. Enable analytical store
Design and implement data models35-40%- Design and implement a non-relational data model for Azure Cosmos DB for NoSQL
  • 1. Identify partition key, id, and unique keys
  • 2. Store multiple related entities in the same document
  • 3. Identify data and associated access patterns
  • 4. Denormalize data across documents
  • 5. Reference between documents
  • 6. Store multiple entity types in the same container
- Implement client connectivity options
  • 1. Configure client-side threading and logging
  • 2. Create database connections
  • 3. Implement singleton client
  • 4. Handle connection errors
  • 5. Use Azure Cosmos DB emulator
  • 6. Choose gateway or direct connectivity mode
- Implement server-side programming
  • 1. Implement user-defined functions
  • 2. Write and deploy stored procedures
  • 3. Implement triggers
- Implement data access
  • 1. Implement patch operations
  • 2. Implement optimistic concurrency control
  • 3. Implement SQL queries with arrays and aggregation
  • 4. Manage transactional batch operations
  • 5. Use SDKs for CRUD operations
  • 6. Use consistency and query request options
- Plan and implement sizing and scaling
  • 1. Design resource governance and scaling
  • 2. Evaluate global distribution costs
  • 3. Choose between serverless, provisioned, and free tier
  • 4. Configure throughput
  • 5. Evaluate throughput and storage requirements
- Design a data partitioning strategy
  • 1. Choose a partition key
  • 2. Implement synthetic partition keys
  • 3. Choose a partitioning strategy
  • 4. Evaluate throughput and data distribution
  • 5. Evaluate cross-partition query cost
  • 6. Plan for transactions with partition keys
Optimize an Azure Cosmos DB solution15-20%- Design and implement change feeds
  • 1. Manage change feed instances
  • 2. Consume change feeds using SDK
  • 3. Implement aggregation persistence
  • 4. Develop Azure Functions triggers
- Optimize query performance
  • 1. Retrieve request unit cost
  • 2. Adjust indexing policies
  • 3. Implement integrated cache
  • 4. Calculate query cost
- Define and implement indexing strategy
  • 1. Choose read-heavy or write-heavy indexing
  • 2. Choose appropriate index types
  • 3. Implement composite indexes
  • 4. Optimize index performance
  • 5. Configure custom indexing policies
Maintain an Azure Cosmos DB solution25-30%- Monitor and troubleshoot Azure Cosmos DB solutions
  • 1. Implement backup and recovery strategies
  • 2. Monitor performance and availability
  • 3. Troubleshoot throughput issues
  • 4. Monitor metrics and logs

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q160-Q165):

NEW QUESTION # 160
You have an Apache Spark pool in Azure Synapse Analytics that runs the following Python code in a notebook.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
New and updated orders will be added to contoso-erp.orders: Yes
The code performs bulk data ingestion from contoso-app: No
Both contoso-app and contoso-erp have Analytics store enabled: Yes
The code uses the spark.readStream method to read data from a container named orders in a database named contoso-app. The data is then filtered by a condition and written to another container named orders in a database named contoso-erp using the spark.writeStream method. The write mode is set to "append", which means that new and updated orders will be added to the destination container1.
The code does not perform bulk data ingestion from contoso-app, but rather stream processing. Bulk data ingestion is a process of loading large amounts of data into a data store in batches. Stream processing is a process of continuously processing data as it arrives in real-time2.
Both contoso-app and contoso-erp have Analytics store enabled, because they are both accessed by Spark pools using the spark.cosmos.oltp method. This method requires that the containers have Analytics store enabled, which is a feature that allows Spark pools to query data stored in Azure Cosmos DB containers using SQL APIs3.


NEW QUESTION # 161
You plan to create an Azure Cosmos DB container named account that will contain items in the following format.

You need to define a query that will return the ids of all accounts that have ever recorded a negative value for balance.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 162
Hotspot Question
You have an Azure subscription that contains an Azure Cosmos DB for NoSQL account named Account1 and an Azure key vault named Vault1.
You plan to enable customer-managed keys and use an encryption key stored in Vault1 to encrypt data at rest.
You need to configure Account1 to use the key from Vault1. The solution must ensure that Account1 continues to operate if the key is rotated in Vault1.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 163
You have an Azure Resource Manager (ARM) template that provisions Azure Cosmos DB accounts and databases. The accounts are deployed to a single Azure region. The databases have provisioned throughput configured. The name of the region, the type of database throughput, and the throughput value are defined as template parameters.
You need to modify some of the Azure Cosmos DB accounts and databases based on the following scenarios:
* Scenario 1: Add a read region and increase the database throughput.
* Scenario 2: Change the provisioned database throughput to autoscale.
The solution must minimize administrative effort and the duration of the modifications.
What should you use for each scenario? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 164
You have an Azure subscription that contains a resource group named RG1. RG1 contains an Azure Cosmos DB for NoSQL account named account1.
You plan to audit changes to the control plane of account1.
You need to ensure that audit events include the details of the security principal that performs each control plane change.
How should you complete the az command? To answer select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 165
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