Practice Test 2 | AWS Certified Solutions Architect Associate | SAA-C03 | Dumps | Mock Test
As a Solutions Architect for a multinational organization having more than 150000 employees, management has decided to implement a real time analysis for their employees time spent in offices across the globe. You are tasked to design a architecture which will receive the inputs from 10000+ sensors with swipe machine sending in and out data from across the globe, each sending 20KB data every 5 Seconds in JSON format. The application will process and analyze the data and upload the results to dashboards in real time.
Other application requirements will have, ability to apply real time analytics on the captured data, processing of captured data will be parallel and durable, the application must be scalable as per the requirement as the load varies and new sensors are added or removed at various facilities. The analytic processing results are stored in a persistent data storage for data mining.
What combination of AWS services would be used for the above scenario?
A. Use EMR to copy the data coming from Swipe machines into DynamoDB and make it available for analytics
B. Use Amazon Kinesis Streams to ingest the Swipe data coming from sensors, Custom Kinesis Streams Applications will analyse the data, move analytics outcomes to RedShift using AWS EMR
C. Utilize SQS to receive the data coming from sensors, use Kinesis Firehose to analyse the data from SQS, then save the results to a Multi-AZ RDS instance
D. Use Amazon Kinesis Streams to ingest the sensors’ data, custom Kinesis Streams applications will analyse the data, move analytics outcomes to RDS using AWS EMR
Explanation:
Answer: Option B
- A. Use EMR to copy the data coming from Swipe machines into DynamoDB and make it available for analytics
This option is incorrect, EMR is not for receiving the real time data from thousands of sources, EMR is mainly used for Hadoop ecosystem based data used for Big data analysis.
- B. Use Amazon Kinesis Streams to ingest the Swipe data coming from sensors, Custom Kinesis Streams Applications will analyse the data, move analytics outcomes to RedShift using AWS EMR
This option is correct, as the Amazon Kinesis streams are used to read the data from thousands of sources like social media, survey based data …etc. and the kinesis streams can be used to analyse the data and can feed it using AWS EMR, to analytics based database like RedShift which works on OLAP.
- C. Utilize SQS to receive the data coming from sensors, use Kinesis Firehose to analyse the data from SQS, then save the results to a Multi-AZ RDS instance
This option is incorrect, SQS cannot be used to read the real time data from thousands of sources. Besides the Kinesis Firehose is used to ship the data to other AWS service not for the analysis. And finally RDS is again an OLTP based database.
- D. Use Amazon Kinesis Streams to ingest the sensors’ data, custom Kinesis Streams applications will analyse the data, move analytics outcomes to RDS using AWS EMR
This option is incorrect, as the AWS EMR can read large amounts of data, however RDS is a transactional database works based on the OLTP, thus it cannot store the analytical data.
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