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Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions:

1. A data engineer needs to join data from multiple sources to perform a one-time analysis job. The data is stored in Amazon DynamoDB, Amazon RDS, Amazon Redshift, and Amazon S3.
Which solution will meet this requirement MOST cost-effectively?

A) Use Redshift Spectrum to query data from DynamoDB, Amazon RDS, and Amazon S3 directly from Redshift.
B) Use Amazon Athena Federated Query to join the data from all data sources.
C) Copy the data from DynamoDB, Amazon RDS, and Amazon Redshift into Amazon S3. Run Amazon Athena queries directly on the S3 files.
D) Use an Amazon EMR provisioned cluster to read from all sources. Use Apache Spark to join the data and perform the analysis.

2. A data engineer has a one-time task to read data from objects that are in Apache Parquet format in an Amazon S3 bucket. The data engineer needs to query only one column of the data.
Which solution will meet these requirements with the LEAST operational overhead?

A) Run an AWS Glue crawler on the S3 objects. Use a SQL SELECT statement in Amazon Athena to query the required column.
B) Prepare an AWS Glue DataBrew project to consume the S3 objects and to query the required column.
C) Confiqure an AWS Lambda function to load data from the S3 bucket into a pandas dataframe- Write a SQL SELECT statement on the dataframe to query the required column.
D) Use S3 Select to write a SQL SELECT statement to retrieve the required column from the S3 objects.

3. A company uses Amazon S3 to store data and Amazon QuickSight to create visualizations.
The company has an S3 bucket in an AWS account named Hub-Account. The S3 bucket is encrypted by an AWS Key Management Service (AWS KMS) key. The company's QuickSight instance is in a separate account named BI-Account The company updates the S3 bucket policy to grant access to the QuickSight service role. The company wants to enable cross-account access to allow QuickSight to interact with the S3 bucket.
Which combination of steps will meet this requirement? (Select TWO.)

A) Add the 53 bucket as a resource that the QuickSight service role can access.
B) Use AWS Resource Access Manager (AWS RAM) to share the S3 bucket with the Bl-Account account.
C) Use the existing AWS KMS key to encrypt connections from QuickSight to the S3 bucket.
D) Add an IAM policy to the QuickSight service role to give QuickSight access to the KMS key that encrypts the S3 bucket.
E) Add the KMS key as a resource that the QuickSight service role can access.

4. A data engineer has two datasets that contain sales information for multiple cities and states. One dataset is named reference, and the other dataset is named primary.
The data engineer needs a solution to determine whether a specific set of values in the city and state columns of the primary dataset exactly match the same specific values in the reference dataset. The data engineer wants to use Data Quality Definition Language (DQDL) rules in an AWS Glue Data Quality job.
Which rule will meet these requirements?

A) ReferentialIntegrity "city,state" "reference.{ref_city,ref_state}" = 100
B) DatasetMatch "reference" "city->ref_city, state->ref_state" = 100
C) ReferentialIntegrity "city,state" "reference.{ref_city,ref_state}" = 1.0
D) DatasetMatch "reference" "city->ref_city, state->ref_state" = 1.0

5. A company stores sensitive data in an Amazon Redshift table. The company needs to give specific users the ability to access the sensitive data. The company must not create duplication in the data.
Customer support users must be able to see the last four characters of the sensitive data. Audit users must be able to see the full value of the sensitive data. No other users can have the ability to access the sensitive information.
Which solution will meet these requirements?

A) Enable metadata security on the Redshift cluster. Create IAM users and IAM roles for the customer support users and the audit users. Grant the IAM users and IAM roles permissions to view the metadata in the Redshift cluster.
B) Create an AWS Glue job to redact the sensitive data and to load the data into a new Redshift table.
C) Create a row-level security policy to allow access based on each user role. Create IAM roles that have specific access permissions. Attach the security policy to the table.
D) Create a dynamic data masking policy to allow access based on each user role. Create IAM roles that have specific access permissions. Attach the masking policy to the column that contains sensitive data.

Solutions: