Exam AWS Certified Data Analytics - Specialty topic 1 question 80 discussion

Answer is B. First of all the question mentions about analyzing the stream over a 5-minute timeframe. Only option B satisfies the above condition. Also KDA uses RCF. Q: How can I perform real-time anomaly detection in Kinesis Data Analytics? Kinesis Data Analytics includes pre-built SQL functions for several advanced analytics including one for anomaly detection. You can simply make a call to this function from your SQL code for detecting anomalies in real-time. Kinesis Data Analytics uses the Random Cut Forest algorithm to implement anomaly detection. For more information on Random Cut Forests, see the Streaming Data Anomaly Detection whitepaper.

Looks like 'B' it is.

Answer is . B Ingest the data stream with Amazon Kinesis Data Streams. Have a Kinesis Data Analytics application evaluate the stream over a 5-minute window using the RCF function and summarize the count of status codes. Persist the source and results to Amazon S3 through output delivery to Kinesis Data Firehouse

B: I passed the test

Why further questions are not available?

Correct answer is B as Kinesis Data Streams can be used to capture the data with Kinesis Data Analytics to perform RCF over a 5 minutes window pushing the source and results data into Kinesis Data Firehose for S3 persistence. https://aws.amazon.com/blogs/big-data/perform-near-real-time-analytics-on-streaming-data-with-amazon-kinesis-and-amazon-elasticsearch-service/ Option A is wrong as it would require more effort and the cost would be higher if storing the data in DynamoDB. Option C is wrong as Kinesis Data Firehose with a delivery frequency of 1 minute or 1 MB would not be able to meet the requirement accurately. Also, the cost would be higher if storing the data in DynamoDB. Option D is wrong as having the Kinesis Data Analytics application evaluate the stream over a 1-minute window would not meet the 5 minutes requirement.

answer is B

Answer is B

Answer is B

ANSWER:OPTION B EXPLAINATION: Since it's a real time streaming data ,so filter out option C,D as KFH is near real time .Now out of option A and B ,S3 has a low data persistence cost .