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Microsoft DP-420 Exam Syllabus Topics:

Section	Weight	Objectives
Optimize an Azure Cosmos DB solution	15-20%	- Optimize query performance 1. Retrieve request unit cost 2. Calculate query cost 3. Adjust indexing policies 4. Implement integrated cache - Define and implement indexing strategy 1. Choose appropriate index types 2. Optimize index performance 3. Configure custom indexing policies 4. Implement composite indexes 5. Choose read-heavy or write-heavy indexing - Design and implement change feeds 1. Implement aggregation persistence 2. Develop Azure Functions triggers 3. Manage change feed instances 4. Consume change feeds using SDK
Maintain an Azure Cosmos DB solution	25-30%	- Monitor and troubleshoot Azure Cosmos DB solutions 1. Troubleshoot throughput issues 2. Implement backup and recovery strategies 3. Monitor metrics and logs 4. Monitor performance and availability
Integrate an Azure Cosmos DB solution	5-10%	- Implement solutions across services 1. Aggregate and archive data 2. Integrate Azure Functions and Event Hubs 3. Use Change Feed for denormalization 4. Enforce referential integrity 5. Implement Azure AI Search integration - Enable analytical workloads 1. Query analytical store from Synapse 2. Enable analytical store 3. Write data back from Spark 4. Configure Azure Cosmos DB Mirroring
Design and implement data distribution	5-10%	- Design and implement replication strategy 1. Choose a consistency model 2. Perform manual failovers 3. Evaluate consistency model impacts 4. Choose when to distribute data 5. Define automatic failover policies - Design and implement multi-region writes 1. Implement conflict resolution policies 2. Choose when to use multi-region writes 3. Implement multi-region writes
Design and implement data models	35-40%	- Design a data partitioning strategy 1. Evaluate cross-partition query cost 2. Plan for transactions with partition keys 3. Evaluate throughput and data distribution 4. Implement synthetic partition keys 5. Choose a partitioning strategy 6. Choose a partition key - Plan and implement sizing and scaling 1. Choose between serverless, provisioned, and free tier 2. Design resource governance and scaling 3. Configure throughput 4. Evaluate throughput and storage requirements 5. Evaluate global distribution costs - Implement client connectivity options 1. Implement singleton client 2. Create database connections 3. Use Azure Cosmos DB emulator 4. Configure client-side threading and logging 5. Choose gateway or direct connectivity mode 6. Handle connection errors - Design and implement a non-relational data model for Azure Cosmos DB for NoSQL 1. Identify partition key, id, and unique keys 2. Denormalize data across documents 3. Reference between documents 4. Identify data and associated access patterns 5. Store multiple entity types in the same container 6. Store multiple related entities in the same document - Implement data access 1. Manage transactional batch operations 2. Implement patch operations 3. Implement SQL queries with arrays and aggregation 4. Use SDKs for CRUD operations 5. Implement optimistic concurrency control 6. Use consistency and query request options - Implement server-side programming 1. Implement user-defined functions 2. Write and deploy stored procedures 3. Implement triggers

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q37-Q42):

NEW QUESTION # 37
You maintain a relational database for a book publisher. The database contains the following tables.

The most common query lists the books for a given authorId.
You need to develop a non-relational data model for Azure Cosmos DB Core (SQL) API that will replace the relational database. The solution must minimize latency and read operation costs.
What should you include in the solution?

A. Create a container for Author and a container for Book. In each Author document, embed booked for each book by the author. In each Book document embed author of each author.
B. Create a container for Author and a container for Book. In each Author document and Book document embed the data from Bookauthorlnk.
C. Create a container that contains a document for each Author and a document for each Book. In each Book document, embed authorId.
D. Create Author, Book, and Bookauthorlnk documents in the same container.

Answer: A

Explanation:
Store multiple entity types in the same container.

NEW QUESTION # 38
You have a container named container1 in an Azure Cosmos DB Core (SQL) API account. The container1 container has 120 GB of data.
The following is a sample of a document in container1.

The orderId property is used as the partition key.
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:

NEW QUESTION # 39
You have the indexing policy shown in the following exhibit.

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Box 1: ORDER BY c.name DESC, c.age DESC
Queries that have an ORDER BY clause with two or more properties require a composite index.
The following considerations are used when using composite indexes for queries with an ORDER BY clause with two or more properties:
If the composite index paths do not match the sequence of the properties in the ORDER BY clause, then the composite index can't support the query.
The order of composite index paths (ascending or descending) should also match the order in the ORDER BY clause.
The composite index also supports an ORDER BY clause with the opposite order on all paths.
Box 2: At the same time as the item creation
Azure Cosmos DB supports two indexing modes:
Consistent: The index is updated synchronously as you create, update or delete items. This means that the consistency of your read queries will be the consistency configured for the account.
None: Indexing is disabled on the container.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/index-policy

NEW QUESTION # 40
You have a container named container1 in an Azure Cosmos DB Core (SQL) API account.
You need to provide a user named User1 with the ability to insert items into container1 by using role-based access control (RBAC). The solution must use the principle of least privilege.
Which roles should you assign to User1?

A. Cosmos DB Built-in Data Contributor only
B. CosmosDB Operator only
C. DocumentDB Account Contributor and Cosmos DB Built-in Data Contributor
D. DocumentDB Account Contributor only

Answer: B

Explanation:
Cosmos DB Operator: Can provision Azure Cosmos accounts, databases, and containers. Cannot access any data or use Data Explorer.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/role-based-access-control

NEW QUESTION # 41
You are designing an Azure Cosmos DB for NoSQL solution to store data from IoT devices.
Writes from the devices will occur every second. Data will be retained indefinitely.
The following is a sample of the data.

You need to select a partition key that meets the following requirements for writes:
- Minimizes the partition skew
- Avoids capacity limits
- Avoids hot partitions
What should you do?

A. Use deviceId as the partition key.
B. Create a new synthetic key that contains deviceId and a random number.
C. Use deviceManufacturer as the partition key.
D. Create a new Synthetic key that contains deviceId and deviceManufacturer.

Answer: B

Explanation:
Creating a synthetic key that combines deviceId with a random number helps distribute writes more evenly across partitions, effectively minimizing partition skew and avoiding hot partitions.
This approach also helps to maintain a balance of write operations, ensuring that no single partition is overwhelmed, which can occur if using deviceId alone, especially if devices write data in bursts.

NEW QUESTION # 42
......

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