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Online Data-Engineer-Associate Questions Video

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Total 289 questions
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AWS Certified Data Engineer - Associate (DEA-C01) Questions and Answers

Question 77

A company that operates globally must follow regulations that require data from an AWS Region to be accessible only within that Region.

A data engineer is creating a data pipeline that will create resources in the Region where the data engineer works. The data pipeline should have access to data only from the Region where the data engineer works. The pipeline uses Active Directory as an identity and authentication system. The pipeline uses a custom identity broker application to verify that employees are signed in to Active Directory and to obtain temporary credentials by using the AssumeRole API operation.

Which solution will meet the locality requirements with the LEAST administrative effort?

Options:

A.

Create an IAM role that has permissions to create resources. Create a policy for each Region that ensures users can create resources only in that Region. Pass the policy as the session policy when employees obtain the temporary credentials.

B.

Create an IAM role for data engineers in each Region separately. Instruct each data engineer to obtain temporary credentials by assuming the appropriate Region-specific IAM role.

C.

Create an IAM group for each Region. Include the required IAM policies for each IAM group. Add users to each IAM group so that when users log in by obtaining the temporary credentials, the users will receive the appropriate access based on the IAM group.

D.

Create individual IAM policies that allow users to create resources in a specific Region. Assign the policies to each data engineer. Allow users to assume the individually assigned role when the users log in to AWS.

Question 78

A company wants to ingest streaming data into an Amazon Redshift data warehouse from an Amazon Managed Streaming for Apache Kafka (Amazon MSK) cluster. A data engineer needs to develop a solution that provides low data access time and that optimizes storage costs.

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

Options:

A.

Create an external schema that maps to the MSK cluster. Create a materialized view that references the external schema to consume the streaming data from the MSK topic.

B.

Develop an AWS Glue streaming extract, transform, and load (ETL) job to process the incoming data from Amazon MSK. Load the data into Amazon S3. Use Amazon Redshift Spectrum to read the data from Amazon S3.

C.

Create an external schema that maps to the streaming data source. Create a new Amazon Redshift table that references the external schema.

D.

Create an Amazon S3 bucket. Ingest the data from Amazon MSK. Create an event-driven AWS Lambda function to load the data from the S3 bucket to a new Amazon Redshift table.

Question 79

A company is developing machine learning (ML) models. A data engineer needs to apply data quality rules to training data. The company stores the training data in an Amazon S3 bucket.

Options:

A.

Create an AWS Lambda function to check data quality and to raise exceptions in the code.

B.

Create an AWS Glue DataBrew project for the data in the S3 bucket. Create a ruleset for the data quality rules. Create a profile job to run the data quality rules. Use Amazon EventBridge to run the profile job when data is added to the S3 bucket.

C.

Create an Amazon EMR provisioned cluster. Add a Python data quality package.

D.

Create AWS Lambda functions to evaluate data quality rules and orchestrate with AWS Step Functions.

Question 80

A telecommunications company collects network usage data throughout each day at a rate of several thousand data points each second. The company runs an application to process the usage data in real time. The company aggregates and stores the data in an Amazon Aurora DB instance.

Sudden drops in network usage usually indicate a network outage. The company must be able to identify sudden drops in network usage so the company can take immediate remedial actions.

Which solution will meet this requirement with the LEAST latency?

Options:

A.

Create an AWS Lambda function to query Aurora for drops in network usage. Use Amazon EventBridge to automatically invoke the Lambda function every minute.

B.

Modify the processing application to publish the data to an Amazon Kinesis data stream. Create an Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) application to detect drops in network usage.

C.

Replace the Aurora database with an Amazon DynamoDB table. Create an AWS Lambda function to query the DynamoDB table for drops in network usage every minute. Use DynamoDB Accelerator (DAX) between the processing application and DynamoDB table.

D.

Create an AWS Lambda function within the Database Activity Streams feature of Aurora to detect drops in network usage.

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Total 289 questions
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