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Amazon DAS-C01 Exam

AWS Certified Data Analytics - Specialty

Total Questions: 207

Last Updated : 05-04-2024

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Amazon DAS-C01 Questions

Q1.

A data engineer is using AWS Glue ETL jobs to process data at frequent intervals The processed data is then copied into Amazon S3 The ETL jobs run every 15 minutes. The AWS Glue Data Catalog partitions need to be updated automatically after the completion of each job

Which solution will meet these requirements MOST cost-effectively?

AUse the AWS Glue Data Catalog to manage the data catalog Define an AWS Glue workflow for the ETL process Define a trigger within the workflow that can start the crawler when an ETL job run is complete

BUse the AWS Glue Data Catalog to manage the data catalog Use AWS Glue Studio to manage ETL jobs. Use the AWS Glue Studio feature that supports updates to the AWS Glue Data Catalog during job runs.

CUse an Apache Hive metastore to manage the data catalog Update the AWS Glue ETL code to include the enableUpdateCatalog and partitionKeys arguments.

DUse the AWS Glue Data Catalog to manage the data catalog Update the AWS Glue ETL code to include the enableUpdateCatalog and partitionKeys arguments.

Q2.

An ecommerce company ingests a large set of clickstream data in JSON format and stores the data in Amazon S3. Business analysts from multiple product divisions need to use Amazon Athena to analyze the dat

a. The company's analytics team must design a solution to monitor the daily data usage for Athena by each product division. The solution also must produce a warning when a divisions exceeds its quota

Which solution will meet these requirements with the LEAST operational overhead?

AUse a CREATE TABLE AS SELECT (CTAS) statement to create separate tables for each product division Use AWS Budgets to track Athena usage Configure a threshold for the budget Use Amazon Simple Notification Service (Amazon SNS) to send notifications when thresholds are breached.

BCreate an AWS account for each division Provide cross-account access to an AWS Glue Data Catalog to all the accounts. Set an Amazon CloudWatch alarm to monitor Athena usage. Use Amazon Simple Notification Service (Amazon SNS) to send notifications.

CCreate an Athena workgroup for each division Configure a data usage control for each workgroup and a time period of 1 day Configure an action to send notifications to an Amazon Simple Notification Service (Amazon SNS) topic

DCreate an AWS account for each division Configure an AWS Glue Data Catalog in each account Set an Amazon CloudWatch alarm to monitor Athena usage Use Amazon Simple Notification Service (Amazon SNS) to send notifications.

Q3.

A company is reading data from various customer databases that run on Amazon RDS. The databases contain many inconsistent fields For example, a customer record field that is place_id in one database is location_id in another database. The company wants to link customer records across different databases, even when many customer record fields do not match exactly

Which solution will meet these requirements with the LEAST operational overhead?

ACreate an Amazon EMR cluster to process and analyze data in the databases Connect to the Apache Zeppelin notebook, and use the FindMatches transform to find duplicate records in the data.

BCreate an AWS Glue crawler to crawl the databases. Use the FindMatches transform to find duplicate records in the data Evaluate and tune the transform by evaluating performance and results of finding matches

CCreate an AWS Glue crawler to crawl the data in the databases Use Amazon SageMaker to construct Apache Spark ML pipelines to find duplicate records in the data

DCreate an Amazon EMR cluster to process and analyze data in the databases. Connect to the Apache Zeppelin notebook, and use Apache Spark ML to find duplicate records in the data. Evaluate and tune the model by evaluating performance and results of finding duplicates

Q4.

A company using Amazon QuickSight Enterprise edition has thousands of dashboards analyses and datasets. The company struggles to manage and assign permissions for granting users access to various items within QuickSight. The company wants to make it easier to implement sharing and permissions management.

Which solution should the company implement to simplify permissions management?

AUse QuickSight folders to organize dashboards, analyses, and datasets Assign individual users permissions to these folders

BUse QuickSight folders to organize dashboards analyses, and datasets Assign group permissions by using these folders.

CUse AWS 1AM resource-based policies to assign group permissions to QuickSight items

DUse QuickSight user management APIs to provision group permissions based on dashboard naming conventions

Q5.

A company hosts an Apache Flink application on premises. The application processes data from several Apache Kafka clusters. The data originates from a variety of sources, such as web applications mobile apps and operational databases The company has migrated some of these sources to AWS and now wants to migrate the Flink application. The company must ensure that data that resides in databases within the VPC does not traverse the internet The application must be able to process all the data that comes from the company's AWS solution, on-premises resources and the public internet

Which solution will meet these requirements with the LEAST operational overhead?

AImplement Flink on Amazon EC2 within the company's VPC Create Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in the VPC to collect data that comes from applications and databases within the VPC Use Amazon Kinesis Data Streams to collect data that comes from the public internet Configure Flink to have sources from Kinesis Data Streams Amazon MSK and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect

BImplement Flink on Amazon EC2 within the company's VPC Use Amazon Kinesis Data Streams to collect data that comes from applications and databases within the VPC and the public internet Configure Flink to have sources from Kinesis Data Streams and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect

CCreate an Amazon Kinesis Data Analytics application by uploading the compiled Flink jar file Use Amazon Kinesis Data Streams to collect data that comes from applications and databases within the VPC and the public internet Configure the Kinesis Data Analytics application to have sources from Kinesis Data Streams and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect

DCreate an Amazon Kinesis Data Analytics application by uploading the compiled Flink jar file Create Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in the company's VPC to collect data that comes from applications and databases within the VPC Use Amazon Kinesis Data Streams to collect data that comes from the public internet Configure the Kinesis Data Analytics application to have sources from Kinesis Data Streams. Amazon MSK and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect

Solutions:

Question: 1 Answer: A

Question: 2 Answer: C

Question: 3 Answer: B

Question: 4 Answer: C

Question: 5 Answer: D

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