Question

An online company wants to conduct real-time sentiment analysis about its products from its social media channels using SQL.

Which of the following solutions has the LOWEST cost and operational burden?
A. Set up a streaming data ingestion application on Amazon EC2 and connect it to a Hadoop cluster for data processing. Send the output to Amazon S3 and use Amazon Athena to analyze the data.
B. Configure the input stream using Amazon Kinesis Data Streams. Use Amazon Kinesis Data Analytics to write SQL queries against the stream.
C. Configure the input stream using Amazon Kinesis Data Streams. Use Amazon Kinesis Data Firehose to send data to an Amazon Redshift cluster, and then query directly against Amazon Redshift
D. Set up streaming data ingestion application on Amazon EC2 and send the output to Amazon S3 using Kinesis Data Firehose. Use Athena to analyze the data.

Answer 1

An online company wants to conduct real-time sentiment analysis about its products from its social media channels using SQL. The solution which has lowest cost and operational burden is as follow:

B. Configure the input stream using Amazon Kinesis Data Streams. Use Amazon Kinesis Data Analytics to write SQL queries against the stream.

Step-by-step explanation:

• The option A is not correct as this solution doesn't have lowest cost and operational burden as set up a streaming data ingestion application on Amazon EC2 and connect it to a Hadoop cluster for data processing will have more cost and operational burden.
• The lowest cost and operational burden solution is that we configure input stream using Amazon Kinesis Data Streams. We can use Amazon Kinesis Data Analytics to write SQL queries against the stream.
• The option c and d are also more pricey in terms of cost and operational burden as compared to Amazon Kinesis Data stream and analytics.