Verified DP-201 Dumps Q&As - DP-201 Test Engine with Correct Answers
Pass Your DP-201 Dumps as PDF Updated on 2022 With 207 Questions
NEW QUESTION 45
You are designing an Azure SQL Data Warehouse for a financial services company. Azure Active Directory will be used to authenticate the users.
You need to ensure that the following security requirements are met:
* Department managers must be able to create new database.
* The IT department must assign users to databases.
* Permissions granted must be minimized.
Which role memberships should you recommend? To answer, drag the appropriate roles to the correct groups.
Each role may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: dbmanager
Members of the dbmanager role can create new databases.
Box 2: db_accessadmin
Members of the db_accessadmin fixed database role can add or remove access to the database for Windows logins, Windows groups, and SQL Server logins.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-manage-logins
NEW QUESTION 46
Note: This question is part of a series of questions that present the same scenario. Each question
in the series contains a unique solution that might meet the stated goals. Some question sets
might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these
questions will not appear in the review screen.
You are designing an Azure SQL Database that will use elastic pools. You plan to store data about
customers in a table. Each record uses a value for CustomerID.
You need to recommend a strategy to partition data based on values in CustomerID.
Proposed Solution: Separate data into customer regions by using horizontal partitioning.
Does the solution meet the goal?
- A. Yes
- B. No
Answer: B
Explanation:
Explanation/Reference:
Explanation:
We should use Horizontal Partitioning through Sharding, not divide through regions.
Note: Horizontal Partitioning - Sharding: Data is partitioned horizontally to distribute rows across a scaled
out data tier. With this approach, the schema is identical on all participating databases. This approach is
also called "sharding". Sharding can be performed and managed using (1) the elastic database tools
libraries or (2) self-sharding. An elastic query is used to query or compile reports across many shards.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-elastic-query-overview
NEW QUESTION 47
You have a data model that you plan to implement in an Azure SQL data warehouse as shown in the following exhibit.
All the dimension tables will be less than 5 GB after compression, and the fact table will be approximately 6 TB.
Which type of table should you use for each table? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Replicated
Replicated tables are ideal for small star-schema dimension tables, because the fact table is often distributed on a column that is not compatible with the connected dimension tables. If this case applies to your schema, consider changing small dimension tables currently implemented as round-robin to replicated.
Box 2: Replicated
Box 3: Replicated
Box 4: Hash-distributed
For Fact tables use hash-distribution with clustered columnstore index. Performance improves when two hash tables are joined on the same distribution column.
References:
https://azure.microsoft.com/en-us/updates/reduce-data-movement-and-make-your-queries-more-efficient-with-th
https://azure.microsoft.com/en-us/blog/replicated-tables-now-generally-available-in-azure-sql-data-warehouse/
NEW QUESTION 48
You need to design the storage for the telemetry capture system. What storage solution should you use in the design?
- A. Azure Databricks
- B. Azure SQL Data Warehouse
- C. Azure Cosmos DB
Answer: C
NEW QUESTION 49
A company plans to use Apache Spark Analytics to analyze intrusion detection data You need to recommend a solution to monitor network and system activities for malicious activities and policy violations. Reports must be produced in an electronic format and sent to management. The solution must minimize administrative efforts.
What should you recommend?
- A. Azure Data Factory
- B. Azure Databricks
- C. Azure HDInsight
- D. Azure Data Lake
Answer: C
Explanation:
With Azure HDInsight you can set up Azure Monitor alerts that will trigger when the value of a metric or the results of a query meet certain conditions. You can condition on a query returning a record with a value that is greater than or less than a certain threshold, or even on the number of results returned by a query. For example, you could create an alert to send an email if a Spark job fails or if a Kafka disk usage becomes over
90 percent full.
Reference:
https://azure.microsoft.com/en-us/blog/monitoring-on-azure-hdinsight-part-4-workload-metrics-and-logs/
NEW QUESTION 50
You are developing an application that uses Azure Data Lake Storage Gen 2.
You need to recommend a solution to grant permissions to a specific application for a limited time period.
What should you include in the recommendation?
- A. account keys
- B. shared access signatures (SAS)
- C. role assignments
- D. Azure Active Directory (Azure AD) identities
Answer: B
Explanation:
A shared access signature (SAS) is a URI that grants restricted access rights to Azure Storage resources. You can provide a shared access signature to clients who should not be trusted with your storage account key but to whom you wish to delegate access to certain storage account resources. By distributing a shared access signature URI to these clients, you can grant them access to a resource for a specified period of time, with a specified set of permissions.
Reference:
https://docs.microsoft.com/en-us/rest/api/storageservices/delegate-access-with-shared-access-signature
NEW QUESTION 51
A company has an application that uses Azure SQL Database as the data store.
The application experiences a large increase in activity during the last month of each year.
You need to manually scale the Azure SQL Database instance to account for the increase in data write operations.
Which scaling method should you recommend?
- A. Scale out by sharding the data across databases.
- B. Scale up by increasing the database throughput units.
- C. Scale up by using elastic pools to distribute resources.
Answer: B
Explanation:
Explanation
As of now, the cost of running an Azure SQL database instance is based on the number of Database Throughput Units (DTUs) allocated for the database. When determining the number of units to allocate for the solution, a major contributing factor is to identify what processing power is needed to handle the volume of expected requests.
Running the statement to upgrade/downgrade your database takes a matter of seconds.
NEW QUESTION 52
You plan to ingest streaming social media data by using Azure Stream Analytics. The data will be stored in files in Azure Data Lake Storage, and then consumed by using Azure Databricks and PolyBase in Azure Synapse Analytics.
You need to recommend a Stream Analytics data output format to ensure that the queries from Databricks and PolyBase against the files encounter the fewest possible errors. The solution must ensure that the files can be queried quickly and that the data type information is retained.
What should you recommend?
- A. JSON
- B. CSV
- C. Avro
- D. Parquet
Answer: C
Explanation:
The Avro format is great for data and message preservation.
Avro schema with its support for evolution is essential for making the data robust for streaming architectures like Kafka, and with the metadata that schema provides, you can reason on the data. Having a schema provides robustness in providing meta-data about the data stored in Avro records which are self-documenting the data.
References:
http://cloudurable.com/blog/avro/index.html
NEW QUESTION 53
You plan to store 100 GB of data used by a line-of-business (LOB) app.
You need to recommend a data storage solution for the data. The solution must meet the following requirements:
* Minimize storage costs.
* Natively support relational queries.
* Provide a recovery time objective (RTO) of less than one minute.
What should you include in the recommendation?
- A. Azure Blob storage
- B. Azure SQL Database
- C. Azure Cosmos DB
- D. Azure Synapse Analytics
Answer: A
Explanation:
Explanation/Reference:
Incorrect Answers:
A: Azure Cosmos DB would require an SQL API.
NEW QUESTION 54
You are designing security for administrative access to Azure SQL Data Warehouse.
You need to recommend a solution to ensure that administrators use two-factor authentication when accessing the data warehouse from Microsoft SQL Server Management Studio (SSMS).
What should you include in the recommendation?
- A. Azure Active Directory (Azure AD) Privileged Identity Management (PIM)
- B. Azure conditional access policies
- C. Azure Active Directory (Azure AD) Identity Protection
- D. Azure Key Vault secrets
Answer: B
Explanation:
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-conditional-access
NEW QUESTION 55
You are designing an Azure Data Factory pipeline for processing data. The pipeline will process data that is stored in general-purpose standard Azure storage.
You need to ensure that the compute environment is created on-demand and removed when the process is completed.
Which type of activity should you recommend?
- A. Data Lake Analytics U-SQL activity
- B. Databricks Jar activity
- C. Databricks Python activity
- D. HDInsight Pig activity
Answer: D
Explanation:
The HDInsight Pig activity in a Data Factory pipeline executes Pig queries on your own or on-demand HDInsight cluster.
References:
https://docs.microsoft.com/en-us/azure/data-factory/transform-data-using-hadoop-pig
NEW QUESTION 56
You are designing a solution for the ad hoc analysis of data in Azure Databricks notebooks. The data will be stored in Azure Blob storage.
You need to ensure that Blob storage will support the recovery of the data if the data is overwritten accidentally.
What should you recommend?
- A. Use read-access geo-redundant storage (RA-GRS).
- B. Enable diagnostics logging.
- C. Add a resource lock.
- D. Enable soft delete.
Answer: D
Explanation:
Soft delete protects blob data from being accidentally or erroneously modified or deleted. When soft delete is enabled for a storage account, blobs, blob versions (preview), and snapshots in that storage account may be recovered after they are deleted, within a retention period that you specify.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/soft-delete-overview
NEW QUESTION 57
Which Azure Data Factory components should you recommend using together to import the daily inventory data from SQL to Data Lake Storage? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Self-hosted integration runtime
A self-hosted IR is capable of nunning copy activity between a cloud data stores and a data store in private network.
Scenario: Daily inventory data comes from a Microsoft SQL server located on a private network.
Box 2: Schedule trigger
Daily schedule
Box 3: Copy activity
Scenario:
Stage inventory data in Azure Data Lake Storage Gen2 before loading the data into the analytical data store. Litware wants to remove transient data from Data Lake Storage once the data is no longer in use. Files that have a modified date that is older than 14 days must be removed.
NEW QUESTION 58
You are designing a solution that will use Azure Table storage. The solution will log records in the following entity.
You are evaluating which partition key to use based on the following two scenarios:
* Scenario1: Minimize hotspots under heavy write workloads.
* Scenario2: Ensure that date lookups are as efficient as possible for read workloads.
Which partition key 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
References:
https://docs.microsoft.com/en-us/rest/api/storageservices/designing-a-scalable-partitioning-strategy-for-azure-tab
NEW QUESTION 59
You need to design the solution for analyzing customer data.
What should you recommend?
- A. Azure Cognitive Services
- B. Azure SQL Data Warehouse
- C. Azure Data Lake Storage
- D. Azure Batch
- E. Azure Databricks
Answer: E
Explanation:
Customer data must be analyzed using managed Spark clusters.
You create spark clusters through Azure Databricks.
Reference:
https://docs.microsoft.com/en-us/azure/azure-databricks/quickstart-create-databricks-workspace-portal
NEW QUESTION 60
A company purchases IoT devices to monitor manufacturing machinery. The company uses an IoT appliance to communicate with the IoT devices.
The company must be able to monitor the devices in real-time.
You need to design the solution.
What should you recommend?
- A. Azure Stream Analytics Edge application using Microsoft Visual Studio
- B. Azure Data Factory instance using the Azure portal
- C. Azure Analysis Services using Microsoft Visual Studio
- D. Azure Analysis Services using the Azure portal
Answer: A
Explanation:
Azure Stream Analytics (ASA) on IoT Edge empowers developers to deploy near-real-time analytical intelligence closer to IoT devices so that they can unlock the full value of device-generated data.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-edge
NEW QUESTION 61
You have a data model that you plan to implement in an Azure SQL data warehouse as shown in the following exhibit.
All the dimension tables will be less than 5 GB after compression, and the fact table will be approximately 6 TB.
Which type of table should you use for each table? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Replicated
Replicated tables are ideal for small star-schema dimension tables, because the fact table is often distributed on a column that is not compatible with the connected dimension tables. If this case applies to your schema, consider changing small dimension tables currently implemented as round-robin to replicated.
Box 2: Replicated
Box 3: Replicated
Box 4: Hash-distributed
For Fact tables use hash-distribution with clustered columnstore index. Performance improves when two hash tables are joined on the same distribution column.
References:
https://azure.microsoft.com/en-us/updates/reduce-data-movement-and-make-your-queries-more-efficient-with-th
https://azure.microsoft.com/en-us/blog/replicated-tables-now-generally-available-in-azure-sql-data-warehouse/
NEW QUESTION 62
What should you recommend as a batch processing solution for Health Interface?
- A. Azure Stream Analytics
- B. Azure Data Factory
- C. Azure Databricks
- D. Azure CycleCloud
Answer: A
Explanation:
Scenario: ADatum identifies the following requirements for the Health Interface application:
Support a more scalable batch processing solution in Azure.
Reduce the amount of time it takes to add data from new hospitals to Health Interface.
Data Factory integrates with the Azure Cosmos DB bulk executor library to provide the best performance when you write to Azure Cosmos DB.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-cosmos-db Design data processing solutions Testlet 5 Overview You are a data engineer for Trey Research. The company is close to completing a joint project with the government to build smart highways infrastructure across North America. This involves the placement of sensors and cameras to measure traffic flow, car speed, and vehicle details.
You have been asked to design a cloud solution that will meet the business and technical requirements of the smart highway.
Solution components
Telemetry Capture
The telemetry capture system records each time a vehicle passes in front of a sensor. The sensors run on a custom embedded operating system and record the following telemetry data:
* Time
* Location in latitude and longitude
* Speed in kilometers per hour (kmph)
* Length of vehicle in meters
Visual Monitoring
The visual monitoring system is a network of approximately 1,000 cameras placed near highways that capture images of vehicle traffic every 2 seconds. The cameras record high resolution images. Each image is approximately 3 MB in size.
Requirements. Business
The company identifies the following business requirements:
* External vendors must be able to perform custom analysis of data using machine learning technologies.
* You must display a dashboard on the operations status page that displays the following metrics: telemetry, volume, and processing latency.
* Traffic data must be made available to the Government Planning Department for the purpose of modeling changes to the highway system. The traffic data will be used in conjunction with other data such as information about events such as sporting events, weather conditions, and population statistics. External data used during the modeling is stored in on-premises SQL Server 2016 databases and CSV files stored in an Azure Data Lake Storage Gen2 storage account.
* Information about vehicles that have been detected as going over the speed limit during the last 30 minutes must be available to law enforcement officers. Several law enforcement organizations may respond to speeding vehicles.
* The solution must allow for searches of vehicle images by license plate to support law enforcement investigations. Searches must be able to be performed using a query language and must support fuzzy searches to compensate for license plate detection errors.
Requirements. Security
The solution must meet the following security requirements:
* External vendors must not have direct access to sensor data or images.
* Images produced by the vehicle monitoring solution must be deleted after one month. You must minimize costs associated with deleting images from the data store.
* Unauthorized usage of data must be detected in real time. Unauthorized usage is determined by looking for unusual usage patterns.
* All changes to Azure resources used by the solution must be recorded and stored. Data must be provided to the security team for incident response purposes.
Requirements. Sensor data
You must write all telemetry data to the closest Azure region. The sensors used for the telemetry capture system have a small amount of memory available and so must write data as quickly as possible to avoid losing telemetry data.
Design data processing solutions
Testlet 6
Case study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
Litware, Inc. owns and operates 300 convenience stores across the US. The company sells a variety of packaged foods and drinks, as well as a variety of prepared foods, such as sandwiches and pizzas.
Litware has a loyalty club whereby members can get daily discounts on specific items by providing their membership number at checkout.
Litware employs business analysts who prefer to analyze data by using Microsoft Power BI, and data scientists who prefer analyzing data in Azure Databricks notebooks.
Requirements. Business Goals
Litware wants to create a new analytics environment in Azure to meet the following requirements:
* See inventory levels across the stores. Data must be updated as close to real time as possible.
* Execute ad hoc analytical queries on historical data to identify whether the loyalty club discounts increase sales of the discounted products.
* Every four hours, notify store employees about how many prepared food items to produce based on historical demand from the sales data.
Requirements. Technical Requirements
Litware identifies the following technical requirements:
* Minimize the number of different Azure services needed to achieve the business goals
* Use platform as a service (PaaS) offerings whenever possible and avoid having to provision virtual machines that must be managed by Litware.
* Ensure that the analytical data store is accessible only to the company's on-premises network and Azure services.
* Use Azure Active Directory (Azure AD) authentication whenever possible.
* Use the principle of least privilege when designing security.
* Stage inventory data in Azure Data Lake Storage Gen2 before loading the data into the analytical data store. Litware wants to remove transient data from Data Lake Storage once the data is no longer in use.
Files that have a modified date that is older than 14 days must be removed.
* Limit the business analysts' access to customer contact information, such as phone numbers, because this type of data is not analytically relevant.
* Ensure that you can quickly restore a copy of the analytical data store within one hour in the event of corruption or accidental deletion.
Requirements. Planned Environment
Litware plans to implement the following environment:
* The application development team will create an Azure event hub to receive real-time sales data, including store number, date, time, product ID, customer loyalty number, price, and discount amount, from the point of sale (POS) system and output the data to data storage in Azure.
* Customer data, including name, contact information, and loyalty number, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Product data, including product ID, name, and category, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Daily inventory data comes from a Microsoft SQL server located on a private network.
* Litware currently has 5 TB of historical sales data and 100 GB of customer data. The company expects approximately 100 GB of new data per month for the next year.
* Litware will build a custom application named FoodPrep to provide store employees with the calculation results of how many prepared food items to produce every four hours.
* Litware does not plan to implement Azure ExpressRoute or a VPN between the on-premises network and Azure.
NEW QUESTION 63
You are designing a solution that will use Azure Databricks and Azure Data Lake Storage Gen2.
From Databricks, you need to access Data Lake Storage directly by using a service principal.
What should you include in the solution?
- A. shared access signatures (SAS) in Data Lake Storage
- B. access keys in Data Lake Storage
- C. an organizational relationship in Azure Active Directory (Azure AD)
- D. an application registration in Azure Active Directory (Azure AD)
Answer: D
Explanation:
Create and grant permissions to service principal
If your selected the access method requires a service principal with adequate permissions, and you do not have one, follow these steps:
1. Create an Azure AD application and service principal that can access resources. Note the following properties:
* client-id: An ID that uniquely identifies the application.
* directory-id: An ID that uniquely identifies the Azure AD instance.
* service-credential: A string that the application uses to prove its identity.
2. Register the service principal, granting the correct role assignment, such as Storage Blob Data
3. Contributor, on the Azure Data Lake Storage Gen2 account.
Reference:
https://docs.databricks.com/data/data-sources/azure/azure-datalake-gen2.html
NEW QUESTION 64
You need to design a solution to meet the SQL Server storage requirements for CONT_SQL3.
Which type of disk should you recommend?
- A. Premium SSD Managed Disk
- B. Ultra SSD Managed Disk
- C. Standard SSD Managed Disk
Answer: B
Explanation:
CONT_SQL3 requires an initial scale of 35000 IOPS.
Ultra SSD Managed Disk Offerings
The following table provides a comparison of ultra solid-state-drives (SSD) (preview), premium SSD, standard SSD, and standard hard disk drives (HDD) for managed disks to help you decide what to use.
Reference:
https://docs.microsoft.com/en-us/azure/virtual-machines/windows/disks-types
NEW QUESTION 65
You plan to implement an Azure Data Lake Gen2 storage account.
You need to ensure that the data lake will remain available if a data center fails in the primary Azure region.
The solution must minimize costs.
Which type of replication should you use for the storage account?
- A. geo-redundant storage (GRS)
- B. zone-redundant storage (ZRS)
- C. locally-redundant storage (LRS)
- D. geo-zone-redundant storage (GZRS)
Answer: A
Explanation:
Geo-redundant storage (GRS) copies your data synchronously three times within a single physical location in the primary region using LRS. It then copies your data asynchronously to a single physical location in the secondary region.
Incorrect Answers:
B: Zone-redundant storage (ZRS) copies your data synchronously across three Azure availability zones in the primary region. For applications requiring high availability, Microsoft recommends using ZRS in the primary region, and also replicating to a secondary region.
C: Locally redundant storage (LRS) copies your data synchronously three times within a single physical location in the primary region. LRS is the least expensive replication option, but is not recommended for applications requiring high availability.
D: GZRS is more expensive compared to GRS.
Reference:
https://docs.microsoft.com/en-us/azure/storage/common/storage-redundancy
NEW QUESTION 66
Which Azure service and feature should you recommend using to manage the transient data for Data Lake Storage? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Scenario: Stage inventory data in Azure Data Lake Storage Gen2 before loading the data into the analytical data store. Litware wants to remove transient data from Data Lake Storage once the data is no longer in use.
Files that have a modified date that is older than 14 days must be removed.
Service: Azure Data Factory
Clean up files by built-in delete activity in Azure Data Factory (ADF).
ADF built-in delete activity, which can be part of your ETL workflow to deletes undesired files without writing code. You can use ADF to delete folder or files from Azure Blob Storage, Azure Data Lake Storage Gen1, Azure Data Lake Storage Gen2, File System, FTP Server, sFTP Server, and Amazon S3.
You can delete expired files only rather than deleting all the files in one folder. For example, you may want to only delete the files which were last modified more than 13 days ago.
Feature: Delete Activity
Reference:
https://azure.microsoft.com/sv-se/blog/clean-up-files-by-built-in-delete-activity-in-azure-data-factory/
NEW QUESTION 67
A company has locations in North America and Europe. The company uses Azure SQL Database to support business apps.
Employees must be able to access the app data in case of a region-wide outage. A multi-region availability solution is needed with the following requirements:
* Read-access to data in a secondary region must be available only in case of an outage of the primary region.
* The Azure SQL Database compute and storage layers must be integrated and replicated together.
You need to design the multi-region high availability solution.
What should you recommend? To answer, select the appropriate values in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Standard
The following table describes the types of storage accounts and their capabilities:
Box 2: Geo-redundant storage
If your storage account has GRS enabled, then your data is durable even in the case of a complete regional outage or a disaster in which the primary region isn't recoverable.
Note: If you opt for GRS, you have two related options to choose from:
GRS replicates your data to another data center in a secondary region, but that data is available to be read only if Microsoft initiates a failover from the primary to secondary region.
Read-access geo-redundant storage (RA-GRS) is based on GRS. RA-GRS replicates your data to another data center in a secondary region, and also provides you with the option to read from the secondary region. With RA-GRS, you can read from the secondary region regardless of whether Microsoft initiates a failover from the primary to secondary region.
References:
https://docs.microsoft.com/en-us/azure/storage/common/storage-introduction
https://docs.microsoft.com/en-us/azure/storage/common/storage-redundancy-grs
NEW QUESTION 68
You have a MongoDB database that you plan to migrate to an Azure Cosmos DB account that uses the MongoDB API.
During testing, you discover that the migration takes longer than expected.
You need to recommend a solution that will reduce the amount of time it takes to migrate the data.
What are two possible recommendations to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. Increase the Request Units (RUs).
- B. Add a write region.
- C. Create unique indexes.
- D. Turn off indexing.
- E. Create compound indexes.
Answer: A,D
Explanation:
A: Increase the throughput during the migration by increasing the Request Units (RUs).
For customers that are migrating many collections within a database, it is strongly recommend to configure database-level throughput. You must make this choice when you create the database. The minimum database- level throughput capacity is 400 RU/sec. Each collection sharing database-level throughput requires at least
100 RU/sec.
B: By default, Azure Cosmos DB indexes all your data fields upon ingestion. You can modify the indexing policy in Azure Cosmos DB at any time. In fact, it is often recommended to turn off indexing when migrating data, and then turn it back on when the data is already in Cosmos DB.
Reference:
https://docs.microsoft.com/bs-latn-ba/Azure/cosmos-db/mongodb-pre-migration
NEW QUESTION 69
......
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