DEA-C01 · Question #45
A healthcare company uses Amazon Kinesis Data Streams to stream real-time health data from wearable devices, hospital equipment, and patient records. A data engineer needs to find a solution to proces
The correct answer is B. Use the streaming ingestion feature of Amazon Redshift.. https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-streaming-ingestion.html Use the Streaming Ingestion Feature of Amazon Redshift: Amazon Redshift recently introduced streaming data ingestion, allowing Redshift to consume data directly from Kinesis Data Streams in
Question
A healthcare company uses Amazon Kinesis Data Streams to stream real-time health data from wearable devices, hospital equipment, and patient records. A data engineer needs to find a solution to process the streaming data. The data engineer needs to store the data in an Amazon Redshift Serverless warehouse. The solution must support near real-time analytics of the streaming data and the previous day's data. Which solution will meet these requirements with the LEAST operational overhead?
Options
- ALoad data into Amazon Kinesis Data Firehose. Load the data into Amazon Redshift.
- BUse the streaming ingestion feature of Amazon Redshift.
- CLoad the data into Amazon S3. Use the COPY command to load the data into Amazon Redshift.
- DUse the Amazon Aurora zero-ETL integration with Amazon Redshift.
How the community answered
(18 responses)- A17% (3)
- B56% (10)
- C6% (1)
- D22% (4)
Explanation
https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-streaming-ingestion.html Use the Streaming Ingestion Feature of Amazon Redshift: Amazon Redshift recently introduced streaming data ingestion, allowing Redshift to consume data directly from Kinesis Data Streams in near real-time. This feature simplifies the architecture by eliminating the need for intermediate steps or services, and it is specifically designed to support near real-time analytics. The operational overhead is minimal since the feature is integrated within Redshift.
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