Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 50 discussion

https://docs.aws.amazon.com/redshift/latest/mgmt/query-editor-v2-schedule-query.html

the company can automate the refresh schedules for materialized views with minimal effort. This approach leverages the built-in capabilities of Amazon Redshift, reducing the need for additional services, configurations, or custom code. It aligns with the principle of using the simplest and most straightforward solution that meets the requirements, minimizing operational overhead and complexity

We can schedule the refresh using query scheduler from Query Editor V2.

Amazon Redshift can automatically refresh materialized views with up-to-date data from its base tables when materialized views are created with or altered to have the autorefresh option. For more details, refer to the documentation here, https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-refresh.html.

https://docs.aws.amazon.com/redshift/latest/mgmt/query-editor-v2-schedule-query.html

You can set autorefresh for materialized views using CREATE MATERIALIZED VIEW. You can also use the AUTO REFRESH clause to refresh materialized views automatically.

https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-refresh.html

You can set AUTO REFRESH option on creation. So I will vote with C.

Lambda requires code and configuring permissions. A and D are additional overheads as well. Vote C

B. https://docs.aws.amazon.com/redshift/latest/dg/materialized-view-UDFs.html

AWS Lambda allows running code in response to triggers without needing to provision or manage servers. However, creating a UDF within Amazon Redshift to call a Lambda function for this purpose involves writing custom code and managing permissions between Lambda and Redshift.