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Answer: Use Amazon Redshift streaming ingestion from Kinesis Data Streams and to present data as a materialized view.
Option D is CORRECT because Amazon Redshift streaming ingestion allows for direct ingestion of streaming data from Amazon Kinesis Data Streams into Amazon Redshift. This solution enables the company to create materialized views that can query the streaming data in near real-time without the need for intermediate storage, such as Amazon S3. This approach minimizes operational overhead by removing the need for managing complex ETL processes or batch loading jobs, making it an efficient solution for real-time data analysis in Redshift.
Author: Ritesh Yadav
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Question 4/58
A technology company currently uses Amazon Kinesis Data Streams to collect log data in real time. The company wants to use Amazon Redshift for downstream real-time queries and to enrich the log data.
Which solution will ingest data into Amazon Redshift with the LEAST operational overhead?
A
Set up an Amazon Kinesis Data Firehose delivery stream to send data to a Redshift provisioned cluster table.
B
Set up an Amazon Kinesis Data Firehose delivery stream to send data to Amazon S3. Configure a Redshift provisioned cluster to load data every minute.
C
Configure Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to send data directly to a Redshift provisioned cluster table.
D
Use Amazon Redshift streaming ingestion from Kinesis Data Streams and to present data as a materialized view.
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