AWS Certified Data Analytics – Specialty — Question 64
A large retailer has successfully migrated to an Amazon S3 data lake architecture. The company's marketing team is using Amazon Redshift and Amazon
QuickSight to analyze data, and derive and visualize insights. To ensure the marketing team has the most up-to-date actionable information, a data analyst implements nightly refreshes of Amazon Redshift using terabytes of updates from the previous day.
After the first nightly refresh, users report that half of the most popular dashboards that had been running correctly before the refresh are now running much slower. Amazon CloudWatch does not show any alerts.
What is the MOST likely cause for the performance degradation?
Answer options
- A. The dashboards are suffering from inefficient SQL queries.
- B. The cluster is undersized for the queries being run by the dashboards.
- C. The nightly data refreshes are causing a lingering transaction that cannot be automatically closed by Amazon Redshift due to ongoing user workloads.
- D. The nightly data refreshes left the dashboard tables in need of a vacuum operation that could not be automatically performed by Amazon Redshift due to ongoing user workloads.
Correct answer: D
Explanation
The correct answer is D because after a large data refresh, Amazon Redshift requires a vacuum operation to reclaim space and optimize performance. If user workloads are ongoing, this operation may not occur automatically, leading to slower dashboard performance. Options A and B are less likely as they do not directly relate to the impact of the nightly data refresh, and C does not address the specific need for a vacuum operation after such updates.