Amazon Exam DAS-C01 Topic 2 Question 83 Discussion

Actual exam question for Amazon's DAS-C01 exam

Question #: 83
Topic #: 2

A large energy company is using Amazon QuickSight to build dashboards and report the historical usage data of its customers This data is hosted in Amazon Redshift The reports need access to all the fact tables' billions ot records to create aggregation in real time grouping by multiple dimensions

A data analyst created the dataset in QuickSight by using a SQL query and not SPICE Business users have noted that the response time is not fast enough to meet their needs

Which action would speed up the response time for the reports with the LEAST implementation effort?

AUse QuickSight to modify the current dataset to use SPICE

BUse AWS Glue to create an Apache Spark job that joins the fact table with the dimensions. Load the data into a new table

CUse Amazon Redshift to create a materialized view that joins the fact table with the dimensions

DUse Amazon Redshift to create a stored procedure that joins the fact table with the dimensions Load the data into a new table

Show Suggested Answer

Suggested Answer: A

by Lai at Dec 14, 2023, 06:23 AM

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Pearlene

24 days ago

Haha, I hear you. Spark can be a bit intimidating, but it's worth it in the long run. Although, I have to say, option D also seems like a decent choice. Stored procedures in Redshift can be pretty efficient, and we wouldn't have to worry about the complexity of Spark. Decisions, decisions...

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27 days ago

Hmm, this is a tricky one. We need to find a way to speed up the response time without too much implementation effort. I'm leaning towards option C - creating a materialized view in Amazon Redshift. That way, the data is already pre-joined and ready for QuickSight to use, which should improve the performance.

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