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New DP-420 Study Plan, Latest DP-420 Exam Answers

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The DP-420 certification exam is designed to test candidates on a range of topics, including Azure Cosmos DB data modeling, partitioning, indexing, and querying. It also covers concepts related to Azure Functions, Azure Event Hubs, Azure Stream Analytics, and Azure Cosmos DB Change Feed. DP-420 exam is intended for professionals who have experience working with Azure Cosmos DB and are knowledgeable about cloud computing concepts and principles.

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Achieving the Microsoft DP-420 certification can open up new career opportunities for you as a cloud-native application developer or architect. It can help you demonstrate your expertise in designing and implementing scalable and highly available cloud-native applications using Cosmos DB, which is a critical component of the Microsoft Azure ecosystem. By passing DP-420 exam, you can show potential employers that you have the skills and knowledge needed to develop and deploy cloud-native applications that meet the demands of modern businesses.

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q51-Q56):

NEW QUESTION # 51
You need to select the partition key for con-iot1. The solution must meet the IoT telemetry requirements.
What should you select?

A. the device ID
B. the temperature
C. the timestamp
D. the humidity

Answer: A

Explanation:
The partition key is what will determine how data is routed in the various partitions by Cosmos DB and needs to make sense in the context of your specific scenario. The IoT Device ID is generally the "natural" partition key for IoT applications.
Scenario: The iotdb database will contain two containers named con-iot1 and con-iot2.
Ensure that Azure Cosmos DB costs for IoT-related processing are predictable.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/solution-ideas/articles/iot-using-cosmos-db

NEW QUESTION # 52
You plan to store order data in Azure Cosmos DB for NoSQL account. The data contains information about orders and their associated items.
You need to develop a model that supports order read operations. The solution must minimize the number or requests.

A. Create a single database that contains one container. Create a separate document for each order and embed the order items into the order documents.
B. Create a single database that contains a container for order and a container for order items.
C. Create a database for orders and a database for order items.
D. Create a single database that contains one container. Store orders and order items in separate documents in the container.

Answer: A

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 develop a model that supports order read operations and minimizes the number of requests, 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 model that you could implement is B. Create a single database that contains one container. Create a separate document for each order and embed the order items into the order documents.
This model has the following advantages:
* It stores orders and order items as self-contained documents that can be easily retrieved by order ID1.
* It avoids storing redundant data or creating additional containers for order items1.
* It allows you to view the order history of a customer with simple queries1.
* It leverages the benefits of embedding data, such as reducing the number of requests, improving query performance, and simplifying data consistency2.
This model also has some limitations, such as:
* It may not be suitable for some order items that 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 order items need to be queried independently from orders or aggregated by other criteria
* It may not support transactions across multiple orders or customers, as transactions are scoped to a single logical partition2.
Depending on your specific use case and requirements, you may need to adjust this model 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 # 53
You plan to deploy two Azure Cosmos DB Core (SQL) API accounts that will each contain a single database.
The accounts will be configured as shown in the following table.

How should you provision the containers within each account to minimize costs? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: Serverless capacity mode
Azure Cosmos DB serverless best fits scenarios where you expect intermittent and unpredictable traffic with long idle times. Because provisioning capacity in such situations isn't required and may be cost-prohibitive, Azure Cosmos DB serverless should be considered in the following use-cases:
Getting started with Azure Cosmos DB
Running applications with bursty, intermittent traffic that is hard to forecast, or low (<10%) average-to-peak traffic ratio Developing, testing, prototyping and running in production new applications where the traffic pattern is unknown Integrating with serverless compute services like Azure Functions Box 2: Provisioned throughput capacity mode and autoscale throughput The use cases of autoscale include:
Variable or unpredictable workloads: When your workloads have variable or unpredictable spikes in usage, autoscale helps by automatically scaling up and down based on usage. Examples include retail websites that have different traffic patterns depending on seasonality; IOT workloads that have spikes at various times during the day; line of business applications that see peak usage a few times a month or year, and more. With autoscale, you no longer need to manually provision for peak or average capacity.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/serverless
https://docs.microsoft.com/en-us/azure/cosmos-db/provision-throughput-autoscale#use-cases-of-autoscale

NEW QUESTION # 54
You have a container that stores data about families. The following is a sample document.

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
Children who do no have parents defined will appear on the list = NO
Children who do not have parents defined will not appear on the list. This is because the document schema defines the children property as an array of objects that contain the firstName and gender properties of each child, as well as a parents property that references the id values of the parents. If a child does not have parents defined, it means that the parents property is either missing or empty for that child. Therefore, such a child will not be included in the list of children who have parents defined.
Children who have more than one pet will appear on the list multiple times. = Yes Children who have more than one pet will appear on the list multiple times. This is because the document schema defines the pets property as an array of objects that contain the givenName and type properties of each pet, as well as a children property that references the id values of the children who own the pet. If a child has more than one pet, it means that the child's id value will appear in the children property of multiple pet objects. Therefore, such a child will be included in the list of children who have pets multiple times.
Children who do no have pets defined will appear on the list = No
Children who do not have pets defined will not appear on the list. This is because the document schema defines the pets property as an array of objects that contain the givenName and type properties of each pet, as well as a children property that references the id values of the children who own the pet. If a child does not have pets defined, it means that the child's id value does not appear in the children property of any pet object.
Therefore, such a child will not be included in the list of children who have pets defined.

NEW QUESTION # 55
You have a database named db1 in an Azure Cosmos DB for NoSQL
You are designing an application that will use dbl.
In db1, you are creating a new container named coll1 that will store in coll1.
The following is a sample of a document that will be stored in coll1.

The application will have the following characteristics:
* New orders will be created frequently by different customers.
* Customers will often view their past order history.
You need to select the partition key value for coll1 to support the application. The solution must minimize costs.
To what should you set the partition key?

A. orderDate
B. orderId
C. id
D. customerId

Answer: A

Explanation:
Based on the characteristics of the application and the provided document structure, the most suitable partition key value for coll1 in the given scenario would be the customerId, Option B.
The application frequently creates new orders by different customers and customers often view their past order history. Using customerId as the partition key would ensure that all orders associated with a particular customer are stored in the same partition. This enables efficient querying of past order history for a specific customer and reduces cross-partition queries, resulting in lower costs and improved performance.
a partition key is a JSON property (or path) within your documents that is used by Azure Cosmos DB to distribute data among multiple partitions3. A partition key should have a high cardinality, which means it should have many distinct values, such as hundreds or thousands1. A partition key should also align with the most common query patterns of your application, so that you can efficiently retrieve data by using the partition key value1.
Based on these criteria, one possible partition key that you could use for coll1 is B. customerId.
This partition key has the following advantages:
It has a high cardinality, as each customer will have a unique ID3.
It aligns with the query patterns of the application, as customers will often view their past order history3.
It minimizes costs, as it reduces the number of cross-partition queries and optimizes the storage and throughput utilization1.
This partition key also has some limitations, such as:
It may not be optimal for scenarios where orders need to be queried independently from customers or aggregated by date or other criteria3.
It may result in hot partitions or throttling if some customers create orders more frequently than others or have more data than others1.
It may not support transactions across multiple customers, as transactions are scoped to a single logical partition2.
Depending on your specific use case and requirements, you may need to adjust this partition key or choose a different one. For example, you could use a synthetic partition key that concatenates multiple properties of an item2, or you could use a partition key with a random or pre-calculated suffix to distribute the workload more evenly2.

NEW QUESTION # 56
......

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