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Exam AWS Certified Data Analytics - Specialty All Questions

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Exam AWS Certified Data Analytics - Specialty topic 1 question 151 discussion

A company provides an incentive to users who are physically active. The company wants to determine how active the users are by using an application on their mobile devices to track the number of steps they take each day. The company needs to ingest and perform near-real-time analytics on live data. The processed data must be stored and must remain available for 1 year for analytics purposes.
Which solution will meet these requirements with the LEAST operational overhead?

  • A. Use Amazon Cognito to write the data from the application to Amazon DynamoDB. Use an AWS Step Functions workflow to create a transient Amazon EMR cluster every hour and process the new data from DynamoDB. Output the processed data to Amazon Redshift for analytics. Archive the data from Amazon Redshift after 1 year.
  • B. Ingest the data into Amazon DynamoDB by using an Amazon API Gateway API as a DynamoDB proxy. Use an AWS Step Functions workflow to create a transient Amazon EMR cluster every hour and process the new data from DynamoDB. Output the processed data to Amazon Redshift to run analytics calculations. Archive the data from Amazon Redshift after 1 year.
  • C. Ingest the data into Amazon Kinesis Data Streams by using an Amazon API Gateway API as a Kinesis proxy. Run Amazon Kinesis Data Analytics on the stream data. Output the processed data into Amazon S3 by using Amazon Kinesis Data Firehose. Use Amazon Athena to run analytics calculations. Use S3 Lifecycle rules to transition objects to S3 Glacier after 1 year.
  • D. Write the data from the application into Amazon S3 by using Amazon Kinesis Data Firehose. Use Amazon Athena to run the analytics on the data in Amazon S3. Use S3 Lifecycle rules to transition objects to S3 Glacier after 1 year.
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Suggested Answer: C 🗳️

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silvaa360
Highly Voted 2 years, 5 months ago
Selected Answer: C
Near/Real-time analytics on live data is always done via KDA. Once the data is stored it cannot be seen as live data anymore. Arguments regarding operational overhead are relevant and will also mix things up for me, but I think here we need KDA.
upvoted 11 times
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MWL
Highly Voted 3 years ago
Selected Answer: C
I am not clear about C or D. For C: it use API gateway as a proxy. ALthough it can, as mentioned beow by "Teraxs". But Is it a good idea to use API gateway for streaming data? For it's pricing, it will cost about for every million message. If the company has millions of customers, uploading activity stream every second. The cost will be huge. For D: The question says they need analyze live data. So it needs kinesis analystics. But D doesn't mention about that. And answer D use kinesis firehose, it is also not near real-time. But, anyway, C will meet the requirement, but D cannot. So I choose C.
upvoted 7 times
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Garavirod
Most Recent 1 year, 3 months ago
FSDFASDF
upvoted 1 times
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LocalHero
1 year, 6 months ago
D is not correct. D cant solve realtime anallitics.
upvoted 1 times
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penguins2
1 year, 9 months ago
I vote for D. D has the least operational overhead and fulfill the purpose. C need to manage KDS shard, API gateway, etc.
upvoted 2 times
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ccpmad
1 year, 10 months ago
Selected Answer: C
"the processed data must be stored", so it is C. D stores the raw data directly to S3
upvoted 3 times
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wally_1995
1 year, 10 months ago
Stored PROCESSED data, not raw data, hence C instead of D!
upvoted 2 times
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pk349
2 years ago
D: I passed the test
upvoted 2 times
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rsn
2 years, 1 month ago
Selected Answer: C
I will go with C. Though D has least operational overhead, Athena can't be considered as the solution for Analytics
upvoted 2 times
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hughnguyen
2 years, 3 months ago
D sounds right
upvoted 2 times
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Ody__
2 years, 4 months ago
Selected Answer: D
D has the least operational overhead
upvoted 3 times
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b33f
2 years, 6 months ago
Selected Answer: C
I vote for C. Because the company needs to perform analytics on LIVE data, I don't think D can be the answer. D analyzes the data after it is stored in S3 and does not perform analytics on live data.
upvoted 1 times
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MultiCloudIronMan
2 years, 6 months ago
C because it clearly says the company wants to ingest and perform analytics near-real time then the processed that is stored. So its KDA for near-real time analtics, although KDS is real-time, but it can also deliver near-real time.
upvoted 1 times
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jazzok
2 years, 7 months ago
The key to selecting C instead of D is: "the processed data must be stored…". In C, the data has been processed through KDA, then saved in S3. But in D, data is from the application to S3 directly, not being processed yet, Athena comes later. So I go with C.
upvoted 2 times
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he11ow0rId
2 years, 8 months ago
Selected Answer: D
for the purpose of the exam, near-real time is generally KDF. Have to agree that arguments can be made for C
upvoted 1 times
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rocky48
2 years, 9 months ago
Selected Answer: D
Option D
upvoted 3 times
rocky48
2 years, 9 months ago
Assuming "LEAST amount of operational overhead", D seems to be the best option.
upvoted 1 times
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arboles
2 years, 10 months ago
Selected Answer: D
For near real-time and with least operational overhead D is better answer
upvoted 2 times
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