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DEA-C01 Exam - Question 102

A marketing company collects clickstream data. The company sends the clickstream data to Amazon Kinesis Data Firehose and stores the clickstream data in Amazon S3. The company wants to build a series of dashboards that hundreds of users from multiple departments will use.

The company will use Amazon QuickSight to develop the dashboards. The company wants a solution that can scale and provide daily updates about clickstream activity.

Which combination of steps will meet these requirements MOST cost-effectively? (Choose two.)

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Correct Answer: BE

To meet the requirements most cost-effectively, the company should use Amazon Athena to query the clickstream data and access the query data through QuickSight SPICE with a daily refresh. Amazon Athena enables you to perform SQL queries directly on data stored in Amazon S3 without the need for complex ETL processes, making it a cost-effective solution for querying large datasets. QuickSight SPICE allows for fast, in-memory data analysis and can provide scalability to support many users and large datasets, and configuring a daily refresh ensures that the dashboards are updated with the latest data while keeping query performance high and costs low.

Discussion

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GHill1982Options: BE
Jun 16, 2024

Agree with B & E. Athena would be cheaper than Redshift. S3 analytics is irrelevant. The functionality in SPICE should be more cost effective than direct SQL by reducing the frequency and volume of queries.

Ja13Options: BE
Jul 3, 2024

B. Use Amazon Athena to query the clickstream data. E. Access the query data through QuickSight SPICE (Super-fast, Parallel, In-memory Calculation Engine). Configure a daily refresh for the dataset. Here's why: B. Use Amazon Athena to query the clickstream data: Amazon Athena allows you to run SQL queries directly on data stored in Amazon S3 without the need for complex ETL processes. It is a cost-effective solution for querying large datasets on S3. E. Access the query data through QuickSight SPICE: QuickSight SPICE is designed for fast, in-memory data analysis and can scale to support many users and large datasets. By configuring a daily refresh, you ensure that the dashboards are updated with the latest data while keeping query performance high and costs low.

tgvOptions: BE
Jun 15, 2024

Athena charges based on the amount of data scanned per query, which can be cost-effective for ad-hoc querying and periodic updates. SPICE can be more cost-effective for frequent access and analysis by multiple users as it reduces the load on the underlying data source.