Question 1

A data engineering team is planning to use AWS Glue for their ETL jobs.

Which feature of AWS Glue should they use to simplify and automate the process of data discovery, conversion, and mapping to make the data available for analytics?

Options :

A : Glue Studio.

B : Glue Data Catalog.

C : Glue Job Bookmarks.

D : Glue Schema Registry.

Answer: B

Question 2

A financial analytics company stores large CSV files containing transaction data in an Amazon S3 bucket. They need to implement a solution that allows their data engineers to run SQL queries directly on these CSV files stored in S3, without the need for additional data transformation or loading into a database.

Which AWS service should the company use to query CSV files directly in the S3 bucket?

Options :

A : Use Amazon Redshift Spectrum to execute SQL queries on CSV files in S3.

B : Use Amazon EMR with a Hive metastore to query the CSV files in the S3 bucket.

C : Use Amazon Athena to run SQL queries directly on the CSV files stored in S3.

D : Use AWS Data Pipeline to transfer CSV data from S3 to Amazon RDS for querying.

Answer: C

Question 3

A Cloud Data Engineering Consultant is tasked with setting up a centralized logging solution for multiple AWS Lambda functions used by a client's serverless application. The application has critical real-time processing components, and the engineering consultant must ensure that logging is set up to capture and respond to error conditions rapidly. The logs must be analyzed for specific error patterns, and notifications must be sent out when these patterns are detected.

Which of the following steps should the Cloud Data Engineering Consultant take to establish a robust logging and notification system using Amazon CloudWatch Logs? (Select TWO)

Options :

A : Configure each Lambda function to automatically send execution logs to CloudWatch Logs and set up metric filters to match the specific error patterns.

B : Directly modify each Lambda function-s code to include API calls that send logs to a dedicated CloudWatch Logs group.

C : Set up CloudWatch Alarms based on the metric filters, triggering notifications through Amazon Simple Notification Service (SNS) when error patterns are found.

D : Use Amazon Kinesis Data Firehose to collect logs from Lambda functions and then process them with Amazon CloudWatch for real-time analysis.

E : Implement a custom logging layer within the Lambda functions to batch and push logs asynchronously to an Amazon DynamoDB table for subsequent analysis and alerting.

Answer: A,C

Question 4

A Cloud Data Engineering team is managing a data lake built on Amazon S3. The data lake is continuously updated with new data while also being accessed for various analytics and reporting purposes. To safeguard against accidental deletion or overwriting of data and to ensure the ability to restore previous versions of data files, the team needs to implement an appropriate data protection strategy on S3.

What should they prioritize to meet these requirements effectively?

Options :

A : Use S3 Lifecycle policies to transition older, unused data to S3 Glacier, and enable MFA Delete on the bucket to prevent accidental data deletions.

B : Enable versioning on the S3 buckets and periodically create and store snapshots of the entire data lake to a separate S3 bucket for backup purposes.

C : Enable S3 versioning across all buckets in the data lake, allowing each object version to be preserved, retrieved, and restored if needed.

D : Implement Amazon S3 Intelligent-Tiering on all objects in the data lake, ensuring that older versions of files are automatically moved to cost-effective storage tiers.

Answer: C

Question 5

A Cloud Data Engineering Team needs to devise a strategy to delete data from their Amazon S3-based data lake in compliance with business and legal data retention policies. The policies require data to be retained for a fixed period, after which it must be securely and verifiably destroyed.

Which of the following options would best fulfill these data deletion requirements? (Select TWO)

Options :

A : Use AWS Lambda functions to manually review and delete data that has exceeded the retention period.

B : Set up MFA Delete on Amazon S3 to require multi-factor authentication before any data deletion operation is permitted.

C : Configure Amazon Macie to automatically identify and remove sensitive data that should no longer be stored.

D : Implement Amazon S3 lifecycle policies to automatically expire objects after a defined retention period.

E : Enable Amazon S3 Object Lock with a governance mode retention period to prevent data deletion until the retention period expires.

Answer: D,E

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