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DAS-C01 – AWS Certified Data Analytics - Specialty

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Showing 7–9 of 10 questions

Question 7

A manufacturing company wants to create an operational analytics dashboard to visualize metrics from equipment in near-real time. The company uses Amazon Kinesis Data Streams to stream the data to other applications. The dashboard must automatically refresh every 5 seconds. A data analytics specialist must design a solution that requires the least possible implementation effort.

Which solution meets these requirements?

Select an option, then click Submit answer.

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    Use Amazon Kinesis Data Firehose to store the data in Amazon S3. Use Amazon QuickSight to build the dashboard.
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    Use Apache Spark Streaming on Amazon EMR to read the data in near-real time. Develop a custom application for the dashboard by using D3.js.
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    Use Amazon Kinesis Data Firehose to push the data into an Amazon OpenSearch Service (Amazon Elasticsearch Service) cluster. Visualize the data by using an OpenSearch Dashboards (Kibana).
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    Use AWS Glue streaming ETL to store the data in Amazon S3. Use Amazon QuickSight to build the dashboard.
Question 8

A retail company’s data analytics team recently created multiple product sales analysis dashboards for the average selling price per product using Amazon QuickSight. The dashboards were created from .csv files uploaded to Amazon S3. The team is now planning to share the dashboards with the respective external product owners by creating individual users in Amazon QuickSight. For compliance and governance reasons, restricting access is a key requirement. The product owners should view only their respective product analysis in the dashboard reports.

Which approach should the data analytics team take to allow product owners to view only their products in the dashboard?

Select an option, then click Submit answer.

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    Separate the data by product and use S3 bucket policies for authorization.
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    Separate the data by product and use IAM policies for authorization.
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    Create a manifest file with row-level security.
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    Create dataset rules with row-level security.
Question 9

A company has developed several AWS Glue jobs to validate and transform its data from Amazon S3 and load it into Amazon RDS for MySQL in batches once every day. The ETL jobs read the S3 data using a DynamicFrame. Currently, the ETL developers are experiencing challenges in processing only the incremental data on every run, as the AWS Glue job processes all the S3 input data on each run.

Which approach would allow the developers to solve the issue with minimal coding effort?

Select an option, then click Submit answer.

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    Have the ETL jobs read the data from Amazon S3 using a DataFrame.
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    Enable job bookmarks on the AWS Glue jobs.
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    Create custom logic on the ETL jobs to track the processed S3 objects.
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    Have the ETL jobs delete the processed objects or data from Amazon S3 after each run.