Microsoft DP-201 Exam Practice Questions (P. 4)
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Question #18
HOTSPOT -
You are designing an application that will store petabytes of medical imaging data
When the data is first created, the data will be accessed frequently during the first week. After one month, the data must be accessible within 30 seconds, but files will be accessed infrequently. After one year, the data will be accessed infrequently but must be accessible within five minutes.
You need to select a storage strategy for the data. The solution must minimize costs.
Which storage tier should you use for each time frame? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
You are designing an application that will store petabytes of medical imaging data
When the data is first created, the data will be accessed frequently during the first week. After one month, the data must be accessible within 30 seconds, but files will be accessed infrequently. After one year, the data will be accessed infrequently but must be accessible within five minutes.
You need to select a storage strategy for the data. The solution must minimize costs.
Which storage tier should you use for each time frame? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
Correct Answer:
First week: Hot -
Hot - Optimized for storing data that is accessed frequently.
After one month: Cool -
Cool - Optimized for storing data that is infrequently accessed and stored for at least 30 days.
After one year: Cool -
Incorrect Answers:
Archive: Optimized for storing data that is rarely accessed and stored for at least 180 days with flexible latency requirements (on the order of hours).
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-storage-tiers
First week: Hot -
Hot - Optimized for storing data that is accessed frequently.
After one month: Cool -
Cool - Optimized for storing data that is infrequently accessed and stored for at least 30 days.
After one year: Cool -
Incorrect Answers:
Archive: Optimized for storing data that is rarely accessed and stored for at least 180 days with flexible latency requirements (on the order of hours).
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-storage-tiers
Question #20
HOTSPOT -
You are designing a new application that uses Azure Cosmos DB. The application will support a variety of data patterns including log records and social media relationships.
You need to recommend which Cosmos DB API to use for each data pattern. The solution must minimize resource utilization.
Which API should you recommend for each data pattern? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
You are designing a new application that uses Azure Cosmos DB. The application will support a variety of data patterns including log records and social media relationships.
You need to recommend which Cosmos DB API to use for each data pattern. The solution must minimize resource utilization.
Which API should you recommend for each data pattern? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
Correct Answer:
Log records: SQL -
Social media mentions: Gremlin -
You can store the actual graph of followers using Azure Cosmos DB Gremlin API to create vertexes for each user and edges that maintain the "A-follows-B" relationships. With the Gremlin API, you can get the followers of a certain user and create more complex queries to suggest people in common. If you add to the graph the Content Categories that people like or enjoy, you can start weaving experiences that include smart content discovery, suggesting content that those people you follow like, or finding people that you might have much in common with.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/social-media-apps
Log records: SQL -
Social media mentions: Gremlin -
You can store the actual graph of followers using Azure Cosmos DB Gremlin API to create vertexes for each user and edges that maintain the "A-follows-B" relationships. With the Gremlin API, you can get the followers of a certain user and create more complex queries to suggest people in common. If you add to the graph the Content Categories that people like or enjoy, you can start weaving experiences that include smart content discovery, suggesting content that those people you follow like, or finding people that you might have much in common with.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/social-media-apps
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