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Exam AWS Certified Machine Learning - Specialty topic 1 question 288 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty

Question #: 288
Topic #: 1

[All AWS Certified Machine Learning - Specialty Questions]

A company processes millions of orders every day. The company uses Amazon DynamoDB tables to store order information. When customers submit new orders, the new orders are immediately added to the DynamoDB tables. New orders arrive in the DynamoDB tables continuously.

A data scientist must build a peak-time prediction solution. The data scientist must also create an Amazon QuickSight dashboard to display near real-time order insights. The data scientist needs to build a solution that will give QuickSight access to the data as soon as new order information arrives.

Which solution will meet these requirements with the LEAST delay between when a new order is processed and when QuickSight can access the new order information?

A. Use AWS Glue to export the data from Amazon DynamoDB to Amazon S3. Configure QuickSight to access the data in Amazon S3.
B. Use Amazon Kinesis Data Streams to export the data from Amazon DynamoDB to Amazon S3. Configure QuickSight to access the data in Amazon S3.
C. Use an API call from QuickSight to access the data that is in Amazon DynamoDB directly.
D. Use Amazon Kinesis Data Firehose to export the data from Amazon DynamoDB to Amazon S3. Configure QuickSight to access the data in Amazon S3.

Show Suggested Answer

Suggested Answer: D 🗳️

by kyuhuck at Feb. 7, 2024, 9:37 a.m.

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Comments

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Ganshank

3 months, 1 week ago

Selected Answer: B

All options are bad. What you really need is CDC using DynamoDB Streams to send the data to S3 and then leverage Quicksight to access that information from S3. And for some reason they skipped that option entirely. So the next closest thing to DynamoDB Streams is Kinesis Data Stream (they are basically the same technology under the hood). Kinesis Data Firehose does not directly integrate with DynamoDB as a source - so you can ignore D. DynamoDB is an high-volume, high-velocity, operational NoSQL datastore. It is meant to be used in insert-only mode for writes, and atomic item-level lookups/queries. Running any kind of batched queries on DynamoDB directly will probably kill your provisioned capacity and performance - so no A or B.

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Ganshank

3 months, 1 week ago

Sorry meant to say no A or C.

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CloudGyan

7 months ago

Selected Answer: C

Direct Access

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LeoD

8 months ago

Selected Answer: C

Kinesis Data Stream do not support to save data to S3 directly. -- B is out Kinesis Data Firehose do not access data from S3 directly. -- D is out

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MultiCloudIronMan

10 months ago

Selected Answer: C

Direct Access: Using an API call allows QuickSight to access the data in DynamoDB directly, ensuring near real-time insights without the need for intermediate steps like exporting data to S3. Minimal Latency: This approach minimizes latency since it eliminates the delay associated with data transfer and storage in S3.

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MJSY

10 months, 2 weeks ago

Selected Answer: D

Kinesis Data Stream didnt support any feature to save data to s3 directly, so the answer is D. if it mention that a lambda after Data Stream to consume data to s3, the B is the LEAST delay option.

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INeedtopassthisexam

1 year ago

ChatGPT

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ggrodskiy

1 year, 3 months ago

B Amazon QuickSight dashboard to display near real-time! order insights B provides the most efficient solution for near real-time access to new order information in QuickSight

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Denise123

1 year, 3 months ago

Selected Answer: D

Option C involves using an API call from QuickSight to access the data directly in Amazon DynamoDB. While this option can provide real-time access to the data, it requires direct integration between QuickSight and DynamoDB, which may involve additional development effort. Additionally, QuickSight's native integration with DynamoDB for real-time data access might be limited compared to its integration with data stored in Amazon S3. Therefore, while option C might offer real-time access, option D with Kinesis Data Firehose to S3 could be a more robust and scalable solution, especially considering the potential limitations of direct DynamoDB integration with QuickSight.

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vkbajoria

1 year, 4 months ago

Selected Answer: D

D is the best solution given options. if not directly, QuickSight can connect to DynamoDB via Athena using a connector https://aws.amazon.com/blogs/big-data/visualize-amazon-dynamodb-insights-in-amazon-quicksight-using-the-amazon-athena-dynamodb-connector-and-aws-glue/

upvoted 3 times

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AIWave

1 year, 5 months ago

Selected Answer: D

Quicksight doesn't integrate with DynamoDB directly. It could use S3, Redshift, Aurora/RDS, Athena, IOT analytics and EC2 hosted databases as data sources. Glouw would work as well but Firehose (D) is the least delay option.

upvoted 4 times

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Stokvisss

1 year, 5 months ago

Selected Answer: C

QuickSight provides the ability to connect to various data sources, including DynamoDB, to create visualizations and dashboards. QuickSight supports a direct connection to DynamoDB tables, allowing you to query and visualize data stored in DynamoDB in real-time. No need to consume a DynamoDB stream with firehose. C is right.

upvoted 2 times

AIWave

1 year, 5 months ago

Quicksight doesn't integrate with DynamoDB directly

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kyuhuck

1 year, 6 months ago

Selected Answer: D

he best solution, considering the requirement for the least delay and the ability to handle continuous data flow efficiently, would be: D. Use Amazon Kinesis Data Firehose to export the data from Amazon DynamoDB to Amazon S3, and configure QuickSight to access the data in Amazon S3. This solution leverages the automatic, scalable streaming capture of Kinesis Data Firehose to move data into S3, where it can be readily accessed by QuickSight for analytics and visualization purposes. This approach balances the need for near real-time insights with the capabilities of AWS services to handle streaming data effectively.

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