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Microsoft DP-420 Exam Syllabus Topics:

Section Weight Objectives Topic 1: Maintain an Azure Cosmos DB solution 25-30% - Monitor and troubleshoot Azure Cosmos DB solutions

1. Monitor performance and availability
2. Implement backup and recovery strategies
3. Troubleshoot throughput issues
4. Monitor metrics and logs

Topic 2: Design and implement data distribution 5-10% - Design and implement replication strategy

1. Choose a consistency model
2. Define automatic failover policies
3. Evaluate consistency model impacts
4. Perform manual failovers
5. Choose when to distribute data

- Design and implement multi-region writes

1. Choose when to use multi-region writes
2. Implement multi-region writes
3. Implement conflict resolution policies

Topic 3: Integrate an Azure Cosmos DB solution 5-10% - Enable analytical workloads

1. Query analytical store from Synapse
2. Write data back from Spark
3. Configure Azure Cosmos DB Mirroring
4. Enable analytical store

- Implement solutions across services

1. Implement Azure AI Search integration
2. Enforce referential integrity
3. Integrate Azure Functions and Event Hubs
4. Aggregate and archive data
5. Use Change Feed for denormalization

Topic 4: Design and implement data models 35-40% - Implement server-side programming

1. Write and deploy stored procedures
2. Implement triggers
3. Implement user-defined functions

- Design a data partitioning strategy

1. Choose a partitioning strategy
2. Plan for transactions with partition keys
3. Evaluate throughput and data distribution
4. Implement synthetic partition keys
5. Evaluate cross-partition query cost
6. Choose a partition key

- Implement data access

1. Use consistency and query request options
2. Use SDKs for CRUD operations
3. Manage transactional batch operations
4. Implement patch operations
5. Implement SQL queries with arrays and aggregation
6. Implement optimistic concurrency control

- Implement client connectivity options

1. Implement singleton client
2. Use Azure Cosmos DB emulator
3. Create database connections
4. Configure client-side threading and logging
5. Handle connection errors
6. Choose gateway or direct connectivity mode

- Design and implement a non-relational data model for Azure Cosmos DB for NoSQL

1. Identify data and associated access patterns
2. Denormalize data across documents
3. Store multiple entity types in the same container
4. Store multiple related entities in the same document
5. Reference between documents
6. Identify partition key, id, and unique keys

- Plan and implement sizing and scaling

1. Design resource governance and scaling
2. Configure throughput
3. Evaluate throughput and storage requirements
4. Evaluate global distribution costs
5. Choose between serverless, provisioned, and free tier

Topic 5: Optimize an Azure Cosmos DB solution 15-20% - Design and implement change feeds

1. Develop Azure Functions triggers
2. Consume change feeds using SDK
3. Implement aggregation persistence
4. Manage change feed instances

- Optimize query performance

1. Adjust indexing policies
2. Implement integrated cache
3. Calculate query cost
4. Retrieve request unit cost

- Define and implement indexing strategy

1. Implement composite indexes
2. Optimize index performance
3. Choose appropriate index types
4. Configure custom indexing policies
5. Choose read-heavy or write-heavy indexing

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q105-Q110):

NEW QUESTION # 105

You have the Azure Cosmos DB for NoSQL containers shown in the following table.

You have the items shown in the following table.

When will each item expire? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

NEW QUESTION # 106

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

Answer: A

Explanation:

Store multiple entity types in the same container.

NEW QUESTION # 107

You need to create a data store for a directory of small and medium-sized businesses (SMBs). The data store must meet the following requirements:

* Store companies and the users employed by them. Each company will have less than 1,000 users.

* Some users have data that is greater than 2 KB.

* Associate each user to only one company.

* Provide the ability to browse by company.

* Provide the ability to browse the users by company.

* Whenever a company or user profile is selected, show a details page for the company and all the related users.

* Be optimized for reading data.

Which design should you implement to optimize the data store for reading data?

A. Create a user container that uses the user ID as the partition key and a company container that container that uses the company ID as the partition key. Add the company ID to each user documents.
B. In a user container, create a document for each user. Embed the company into each user document. Use the user ID as the partition key.
C. In a company container, create a document for each company. Embed the users into company documents. Use the company ID as the partition key.
D. In a directory container, create a document for each company and a document for each user. Use company ID as the partition key.

Answer: C

Explanation:

Explanation

Azure Cosmos DB is a multi-model database that supports various data models, such as documents, key-value, graph, and column-family3. The core content-model of Cosmos DB's database engine is based on atom-record-sequence (ARS), which allows it to store and query different types of data in a flexible and efficient way3.

To optimize the data store for reading data, you should consider the following factors:

The size and shape of your data

The frequency and complexity of your queries

The latency and throughput requirements of your application

The trade-offs between storage efficiency and query performance

Based on these factors, one possible design that you could implement is B. In a company container, create a document for each company. Embed the users into company documents. Use the company ID as the partition key.

This design has the following advantages:

It stores companies and users as self-contained documents that can be easily retrieved by company ID1.

It avoids storing redundant data or creating additional containers for users1.

It allows you to browse by company and browse the users by company with simple queries1.

It shows a details page for the company and all the related users by fetching a single document1.

It leverages the benefits of embedding data, such as reducing the number of requests, improving query performance, and simplifying data consistency2.

This design also has some limitations, such as:

It may not be suitable for some users who have data that is greater than 2 KB, as it could exceed the maximum document size limit of 2 MB2.

It may not be optimal for scenarios where users need to be associated with more than one company or queried independently from companies2.

It may not be scalable for companies that have more than 1,000 users, as it could result in hot partitions or throttling2.

Depending on your specific use case and requirements, you may need to adjust this design or choose a different one. For example, you could use a hybrid data model that combines embedding and referencing data2

, or you could use a graph data model that expresses entities and relationships as vertices and edges.

NEW QUESTION # 108

You have an Azure subscription that contains an Azure Cosmos DB for NoSQL database named DB1. The shared throughput provisioned for DB1 is 10,000 DTU/s. DB1 contains the containers shown in the following table.

You need to modify the throughput for the containers. The solution must meet the following requirements:

* The maximum throughput for Container1 must be 4,000 DTU/s.

* The throughput for Contained must be shared across the containers.

* Administrative effort must be minimized.

What should you do? To answer, select the appropriate options in the answer are a. NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 109

You have an Azure Cosmos DB for NoSQL database named db1.

You run the following code:

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 QUESTION # 110

......

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Maximizing Your Microsoft DP-420 Exam Preparation with Practice Tests

Microsoft DP-420 Exam Syllabus Topics:

Valid DP-420 New Dumps Ebook & Passing DP-420 Exam is No More a Challenging Task

Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q105-Q110):

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