A company stores its processed data in an S3 bucket. The company has a strict data access policy. The company uses IAM roles to grant teams within the company different levels of access to the S3 bucket.
The company wants to receive notifications when a user violates the data access policy. Each notification must include the username of the user who violated the policy.
Which solution will meet these requirements?

• A. Use AWS CloudTrail to track object-level events for the S3 bucket. Forward events to Amazon CloudWatch to set up CloudWatch alarms.
• B. Use Amazon S3 server access logs to monitor access to the bucket. Forward the access logs to an Amazon CloudWatch log group. Use metric filters on the log group to set up CloudWatch alarms.
• C. Use AWS Config rules to detect violations of the data access policy. Set up compliance alarms.
• D. Use Amazon CloudWatch metrics to gather object-level metrics. Set up CloudWatch alarms.

The company stores a large volume of customer records in Amazon S3. To comply with regulations, the company must be able to access new customer records immediately for the first
30 days after the records are created. The company accesses records that are older than 30 days infrequently.
The company needs to cost-optimize its Amazon S3 storage.
Which solution will meet these requirements MOST cost-effectively?

• A. Transition records to S3 Glacier Deep Archive storage after 30 days.
• B. Use S3 Intelligent-Tiering storage.
• C. Use S3 Standard-Infrequent Access (S3 Standard-IA) storage for all customer records.
• D. Apply a lifecycle policy to transition records to S3 Standard Infrequent-Access (S3 Standard-IA) storage after 30 days.

A company analyzes data in a data lake every quarter to perform inventory assessments. A data engineer uses AWS Glue DataBrew to detect any personally identifiable formation (PII) about customers within the data. The company's privacy policy considers some custom categories of information to be PII. However, the categories are not included in standard DataBrew data quality rules.
The data engineer needs to modify the current process to scan for the custom PII categories across multiple datasets within the data lake.
Which solution will meet these requirements with the LEAST operational overhead?

• A. Implement regex patterns to extract PII information from fields during extract transform, and load (ETL) operations into the data lake.
• B. Develop custom Python scripts to detect the custom PII categories. Call the scripts from DataBrew.
• C. Implement custom data quality rules in DataBrew. Apply the custom rules across datasets.
• D. Manually review the data for custom PII categories.

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

• A. Create an Amazon EMR provisioned cluster. Add a Python open source data quality package to the EMR cluster. Use the Python package to write code for data quality rules and to copy the data from the S3 bucket to the EMR cluster. Copy the data from the S3 bucket to the EMR cluster. Run the data quality rules.
• B. Create an AWS Lambda function to check data quality and to raise exceptions in the code. Run the function when data is added to the S3 bucket. Create an Amazon CloudWatch alarm for exceptions in the code.
• C. 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.
• D. Create AWS Lambda functions to evaluate data quality rules. Use AWS Step Functions to orchestrate a workflow that publishes notifications when the data fails to meet data quality rules.

A company has a business intelligence platform on AWS. The company uses an AWS Storage Gateway Amazon S3 File Gateway to transfer files from the company's on-premises environment to an Amazon S3 bucket.
A data engineer needs to setup a process that will automatically launch an AWS Glue workflow to run a series of AWS Glue jobs when each file transfer finishes successfully.
Which solution will meet these requirements with the LEAST operational overhead?

• A. Set up an Amazon EventBridge event that initiates the AWS Glue workflow after every successful S3 File Gateway file transfer event.
• B. Set up an on-demand AWS Glue workflow so that the data engineer can start the AWS Glue workflow when each file transfer is complete.
• C. Set up an AWS Lambda function that will invoke the AWS Glue Workflow. Set up an event for the creation of an S3 object as a trigger for the Lambda function.
• D. Determine when the file transfers usually finish based on previous successful file transfers. Set up an Amazon EventBridge scheduled event to initiate the AWS Glue jobs at that time of day.