Amazon Web Services exactexam das-c01 Questions Bank by Emaan q141 vce pdf

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Exam Name:	AWS Certified Data Analytics - Specialty
Exam Code:	DAS-C01 Dumps
Vendor:	Amazon Web Services	Certification:	AWS Certified Data Analytics
Questions:	207 Q&A's	Shared By:	emaan

Question 48

A company is creating a data lake by using AWS Lake Formation. The data that will be stored in the data lake contains sensitive customer information and must be encrypted at rest using an AWS Key Management Service (AWS KMS) customer managed key to meet regulatory requirements.

How can the company store the data in the data lake to meet these requirements?

Options:

Store the data in an encrypted Amazon Elastic Block Store (Amazon EBS) volume. Register the Amazon EBS volume with Lake Formation.

Store the data in an Amazon S3 bucket by using server-side encryption with AWS KMS (SSE-KMS). Register the S3 location with Lake Formation.

Encrypt the data on the client side and store the encrypted data in an Amazon S3 bucket. Register the S3 location with Lake Formation.

Store the data in an Amazon S3 Glacier Flexible Retrieval vault bucket. Register the S3 Glacier Flexible Retrieval vault with Lake Formation.

Discussion

Question 49

A market data company aggregates external data sources to create a detailed view of product consumption in different countries. The company wants to sell this data to external parties through a subscription. To achieve this goal, the company needs to make its data securely available to external parties who are also AWS users.

What should the company do to meet these requirements with the LEAST operational overhead?

Options:

Store the data in Amazon S3. Share the data by using presigned URLs for security.

Store the data in Amazon S3. Share the data by using S3 bucket ACLs.

Upload the data to AWS Data Exchange for storage. Share the data by using presigned URLs for security.

Upload the data to AWS Data Exchange for storage. Share the data by using the AWS Data Exchange sharing wizard.

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Question 50

A global pharmaceutical company receives test results for new drugs from various testing facilities worldwide. The results are sent in millions of 1 KB-sized JSON objects to an Amazon S3 bucket owned by the company. Thedata engineering team needs to process those files, convert them into Apache Parquet format, and load them into Amazon Redshift for data analysts to perform dashboard reporting. The engineering team uses AWS Glue to process the objects, AWS Step Functions for process orchestration, and Amazon CloudWatch for job scheduling.

More testing facilities were recently added, and the time to process files is increasing.

What will MOST efficiently decrease the data processing time?

Options:

Use AWS Lambda to group the small files into larger files. Write the files back to Amazon S3. Process the files using AWS Glue and load them into Amazon Redshift tables.

Use the AWS Glue dynamic frame file grouping option while ingesting the raw input files. Process the files and load them into Amazon Redshift tables.

Use the Amazon Redshift COPY command to move the files from Amazon S3 into Amazon Redshift tables directly. Process the files in Amazon Redshift.

Use Amazon EMR instead of AWS Glue to group the small input files. Process the files in Amazon EMR and load them into Amazon Redshift tables.

Discussion

Question 51

A marketing company has data in Salesforce, MySQL, and Amazon S3. The company wants to use data from these three locations and create mobile dashboards for its users. The company is unsure how it should create the dashboards and needs a solution with the least possible customization and coding.

Which solution meets these requirements?

Options:

Use Amazon Athena federated queries to join the data sources. Use Amazon QuickSight to generate the mobile dashboards.

Use AWS Lake Formation to migrate the data sources into Amazon S3. Use Amazon QuickSight to generate the mobile dashboards.

Use Amazon Redshift federated queries to join the data sources. Use Amazon QuickSight to generate the mobile dashboards.

Use Amazon QuickSight to connect to the data sources and generate the mobile dashboards.