Download Designing and Implementing an Azure AI Solution.AI-100.PrepAway.2021-05-20.156q.tqb
| Vendor: | Microsoft |
| Exam Code: | AI-100 |
| Exam Name: | Designing and Implementing an Azure AI Solution |
| Date: | May 20, 2021 |
| File Size: | 6 MB |
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Demo Questions
Question 1
You are designing an Al solution that will analyze millions of pictures by using Azure HDlnsight Hadoop cluster.
You need to recommend a solution for storing the pictures. The solution must minimize costs.
Which storage solution should you recommend?
- an Azure Data Lake Storage Gent
- Azure File Storage
- Azure Blob storage
- Azure Table storage WPQW?
Correct answer: C
Explanation:
Data Lake will be a bit more expensive although they are in close range of each other. Blob storage has more options for pricing depending upon things like how frequently you need to access your data (cold vs hot storage). Reference: http://bloq.praqmaticworks.com/azure-data-lake-vs-azure-blob-storaqe-in-data-warehousinq Data Lake will be a bit more expensive although they are in close range of each other. Blob storage has more options for pricing depending upon things like how frequently you need to access your data (cold vs hot storage).
Reference:
http://bloq.praqmaticworks.com/azure-data-lake-vs-azure-blob-storaqe-in-data-warehousinq
Question 2
You are configuring data persistence for a Microsoft Bot Framework application. The application requires a NoSQL cloud data store.
You need to identify a storage solution for the application. The solution must minimize costs.
What should you identity?
- Azure Blob storage
- Azure Cosmos DB
- Azure HDlnsight
- Azure Table storage
Correct answer: D
Explanation:
Table Storage is a NoSQL key-value store for rapid development using massive semi-structured datasets You can develop applications on Cosmos DB using popular NoSQL APls. Both services have a different scenario and pricing model. While Azure Storage Tables is aimed at high capacity on a single region (optional secondary read only region but no failover), indexing by PK/RK and storage-optimized pricing; Azure Cosmos DB Tables aims for high throughput (single-digit millisecond latency), global distribution (multiple failover), SLA-backed predictive performance with automatic indexing of each attribute/property and a pricing model focused on throughput. References: https://db-enqines.com/en/svstem/Microsoft+Azure+Cosmos+DB%3BMicrosoft+Azure+Table+Storaqe Table Storage is a NoSQL key-value store for rapid development using massive semi-structured datasets You can develop applications on Cosmos DB using popular NoSQL APls.
Both services have a different scenario and pricing model.
While Azure Storage Tables is aimed at high capacity on a single region (optional secondary read only region but no failover), indexing by PK/RK and storage-optimized pricing; Azure Cosmos DB Tables aims for high throughput (single-digit millisecond latency), global distribution (multiple failover), SLA-backed predictive performance with automatic indexing of each attribute/property and a pricing model focused on throughput.
References:
https://db-enqines.com/en/svstem/Microsoft+Azure+Cosmos+DB%3BMicrosoft+Azure+Table+Storaqe
Question 3
Your company recently deployed several hardware devices that contain sensors.
The sensors generate new data on an hourly basis. The data generated is stored on-premises and retained for several years.
During the past two months, the sensors generated 300 GB of data.
You plan to move the data to Azure and then perform advanced analytics on the data.
You need to recommend an Azure storage solution for the data.
Which storage solution should you recommend?
- Azure Queue storage
- Azure Cosmos DB
- Azure Blob storage
- Azure SQL Database
Correct answer: C
Explanation:
References: https://docs.microsoft.com/en-us/azure/architecture/data-quide/technologv—choices/data—storaqe References:
https://docs.microsoft.com/en-us/azure/architecture/data-quide/technologv—choices/data—storaqe
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