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DAS-C01 Exam Practice Made Easy: Latest Mock Exams, AWS Certified Data Analytics | SPOTO

Achieving the AWS Certified Data Analytics - Specialty certification is a milestone for data professionals, validating their expertise in leveraging AWS services for data-driven solutions. However, the DAS-C01 exam can be challenging, and adequate preparation is crucial. SPOTO's latest mock exams offer a comprehensive and convenient way to ace the DAS-C01 certification. These mock exams are meticulously designed to mirror the actual exam format, providing you with a realistic testing experience. With a vast collection of exam questions and answers, you'll gain exposure to a wide range of topics covered in the certification, including data collection, processing, modeling, visualization, and security. SPOTO's mock exams are more than just exam dumps; they are carefully crafted exam materials that simulate real-world scenarios, helping you apply your knowledge in practical contexts. Regular practice with these online exam questions and sample questions will not only reinforce your understanding but also boost your confidence and time management skills. The detailed explanations accompanying each question ensure that you not only learn the correct answers but also gain a deeper comprehension of the underlying concepts. Additionally, these mock exams serve as invaluable exam preparation tools, allowing you to identify your strengths and weaknesses, enabling you to focus your study efforts effectively.
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Question #1
A company is planning to do a proof of concept for a machine learning (ML) project using Amazon SageMaker with a subset of existing on-premises data hosted in the company’s 3 TB data warehouse. For part of the project, AWS Direct Connect is established and tested. To prepare the data for ML, data analysts are performing data curation. The data analysts want to perform multiple step, including mapping, dropping null fields, resolving choice, and splitting fields. The company needs the fastest solution to cur
A. Ingest data into Amazon S3 using AWS DataSync and use Apache Spark scrips to curate the data in an Amazon EMR cluste
B. Store the curated data in Amazon S3 for ML processing
C. Create custom ETL jobs on-premises to curate the dat
D. Use AWS DMS to ingest data into Amazon S3 for ML processing
E. Ingest data into Amazon S3 using AWS DM
F. Use AWS Glue to perform data curation and store the data in Amazon S3 for ML processing
View answer
Correct Answer: B
Question #2
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 the day, and cluster utilization is high during certain periods. The COPY command usually completes within a couple of seconds. However, when load spi
A. Increase the number of retrie
B. Decrease the timeout valu
C. Increase the job concurrency
D. Keep the number of retries at 0
E. Increase the job concurrency
F. Keep the number of retries at 0
View answer
Correct Answer: B
Question #3
A data analytics specialist is setting up workload management in manual mode for an Amazon Redshift environment. The data analytics specialist is defining query monitoring rules to manage system performance and user experience of an Amazon Redshift cluster. Which elements must each query monitoring rule include?
A. A unique rule name, a query runtime condition, and an AWS Lambda function to resubmit any failed queries in off hours
B. A queue name, a unique rule name, and a predicate-based stop condition
C. A unique rule name, one to three predicates, and an action
D. A workload name, a unique rule name, and a query runtime-based condition
View answer
Correct Answer: A
Question #4
A company has a marketing department and a finance department. The departments are storing data in Amazon S3 in their own AWS accounts in AWS Organizations. Both departments use AWS Lake Formation to catalog and secure their data. The departments have some databases and tables that share common names. The marketing department needs to securely access some tables from the finance department. Which two steps are required for this process? (Choose two.)
A. The finance department grants Lake Formation permissions for the tables to the external account for the marketing department
B. The finance department creates cross-account IAM permissions to the table for the marketing department role
C. The marketing department creates an IAM role that has permissions to the Lake Formation tables
View answer
Correct Answer: C
Question #5
A company has an application that uses the Amazon Kinesis Client Library (KCL) to read records from a Kinesis data stream. After a successful marketing campaign, the application experienced a significant increase in usage. As a result, a data analyst had to split some shards in the data stream. When the shards were split, the application started throwing an ExpiredIteratorExceptions error sporadically. What should the data analyst do to resolve this?
A. Increase the number of threads that process the stream records
B. Increase the provisioned read capacity units assigned to the stream’s Amazon DynamoDB table
C. Increase the provisioned write capacity units assigned to the stream’s Amazon DynamoDB table
D. Decrease the provisioned write capacity units assigned to the stream’s Amazon DynamoDB table
View answer
Correct Answer: A
Question #6
A technology company is creating a dashboard that will visualize and analyze time-sensitive data. The data will come in through Amazon Kinesis Data Firehose with the butter interval set to 60 seconds. The dashboard must support near-real-time data. Which visualization solution will meet these requirements?
A. Select Amazon Elasticsearch Service (Amazon ES) as the endpoint for Kinesis Data Firehos
B. Set up a Kibana dashboard using the data in Amazon ES with the desired analyses and visualizations
C. Select Amazon S3 as the endpoint for Kinesis Data Firehos
D. Read data into an Amazon SageMaker Jupyter notebook and carry out the desired analyses and visualizations
E. Select Amazon Redshift as the endpoint for Kinesis Data Firehos
F. Connect Amazon QuickSight with SPICE to Amazon Redshift to create the desired analyses and visualizations
View answer
Correct Answer: A

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