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DAS-C01 Exam Dumps V16.02 [2022] For Passing AWS Certified Data Analytics – Specialty
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QUESTION 1
A data analyst is designing a solution to interactively query datasets with SQL using a JDBC connection. Users will join data stored in Amazon S3 in Apache ORC format with data stored in Amazon OpenSearch Service (Amazon Elasticsearch Service) and Amazon Aurora MySQL.
Which solution will provide the MOST up-to-date results?
A. Use AWS Glue jobs to ETL data from Amazon ES and Aurora MySQL to Amazon S3. Query the data with Amazon Athena.
B. Use Amazon DMS to stream data from Amazon ES and Aurora MySQL to Amazon Redshift. Query the data with Amazon Redshift.
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QUESTION 1
A company has a business unit uploading .csv files to an Amazon S3 bucket. The company\\’s data platform team has
set up an AWS Glue crawler to do discovery, and create tables and schemas. An AWS Glue job writes processed data
from the created tables to an Amazon Redshift database. The AWS Glue job handles column mapping and creating the
Amazon Redshift table appropriately. When the AWS Glue job is rerun for any reason in a day, duplicate records are
introduced into the Amazon Redshift table.
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QUESTION 1
A company wants to provide its data analysts with uninterrupted access to the data in its Amazon Redshift cluster. All
data is streamed to an Amazon S3 bucket with Amazon Kinesis Data Firehose. An AWS Glue job that is scheduled to
run every 5 minutes issues a COPY command to move the data into Amazon Redshift.
The amount of data delivered is uneven throughout then day, and cluster utilization is high during certain periods. The
COPY command usually completes within a couple of seconds. However, when load spike occurs, locks can exist and
data can be missed. Currently, the AWS Glue job is configured to run without retries, with timeout at 5 minutes and
concurrency at 1.
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QUESTION 1
An airline has been collecting metrics on flight activities for analytics. A recently completed proof of concept
demonstrates how the company provides insights to data analysts to improve on-time departures. The proof of concept
used objects in Amazon S3, which contained the metrics in .csv format, and used Amazon Athena for querying the data.
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QUESTION 1
An airline has .csv-formatted data stored in Amazon S3 with an AWS Glue Data Catalog. Data analysts want to join this
data with call center data stored in Amazon Redshift as part of a dally batch process. The Amazon Redshift cluster is
already under a heavy load. The solution must be managed, serverless, well-functioning, and minimize the load on the
existing Amazon Redshift cluster. The solution should also require minimal effort and development activity.
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All exercise answers will be announced at the end of the article
QUESTION 1
An airline has been collecting metrics on flight activities for analytics. A recently completed proof of concept
demonstrates how the company provides insights to data analysts to improve on-time departures. The proof of concept used objects in Amazon S3, which contained the metrics in .csv format, and used Amazon Athena for querying the data.