A data engineer maintains a materialized view that is based on an Amazon Redshift database.
The view has a column named load_date that stores the date when each row was loaded.
The data engineer needs to reclaim database storage space by deleting all the rows from the materialized view.
Which command will reclaim the MOST database storage space?

• A. TRUNCATE materialized_view_name
• B. VACUUM table_name where load_date<=current_date materializedview
• C. DELETE FROM materialized_view_name where load_date<=current_date
• D. DELETE FROM materialized_view_name where 1=1

A data engineer uses Amazon Redshift to run resource-intensive analytics processes once every month. Every month, the data engineer creates a new Redshift provisioned cluster. The data engineer deletes the Redshift provisioned cluster after the analytics processes are complete every month. Before the data engineer deletes the cluster each month, the data engineer unloads backup data from the cluster to an Amazon S3 bucket.
The data engineer needs a solution to run the monthly analytics processes that does not require the data engineer to manage the infrastructure manually.
Which solution will meet these requirements with the LEAST operational overhead?

• A. Use AWS CloudFormation templates to automatically process the analytics workload.
• B. Use Amazon Redshift Serverless to automatically process the analytics workload.
• C. Use Amazon Step Functions to pause the Redshift cluster when the analytics processes are complete and to resume the cluster to run new processes every month.
• D. Use the AWS CLI to automatically process the analytics workload.

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A healthcare company stores patient records in an on-premises MySQL database. The company creates an application to access the MySQL database. The company must enforce security protocols to protect the patient records. The company currently rotates database credentials every 30 days to minimize the risk of unauthorized access.
The company wants a solution that does require the company to modify the application code for each credential rotation.
Which solution will meet this requirement with the LEAST operational overhead?

• A. Use AWS Key Management Service (AWS KMS) to generate encryption keys. Configure automatic key rotation. Store the encrypted credentials in an Amazon DynamoDB table.
• B. Assign an IAM role access permissions to the database. Configure the application to obtain temporary credentials through the IAM role.
• C. Store credentials in an encrypted Amazon S3 bucket. Rotate the credentials every month by using an S3 Lifecycle policy. Use bucket policies to control access.
• D. Use AWS Secrets Manager to automatically rotate credentials. Allow the application to retrieve the credentials by using API calls.

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A company uses AWS Step Functions to orchestrate a data pipeline. The pipeline consists of Amazon EMR jobs that ingest data from data sources and store the data in an Amazon S3 bucket. The pipeline also includes EMR jobs that load the data to Amazon Redshift.
The company's cloud infrastructure team manually built a Step Functions state machine. The cloud infrastructure team launched an EMR cluster into a VPC to support the EMR jobs.
However, the deployed Step Functions state machine is not able to run the EMR jobs.
Which combination of steps should the company take to identify the reason the Step Functions state machine is not able to run the EMR jobs? (Choose two.)

• A. Verify that the Step Functions state machine code has all IAM permissions that are necessary to create and run the EMR jobs. Verify that the Step Functions state machine code also includes IAM permissions to access the Amazon S3 buckets that the EMR jobs use. Use Access Analyzer for S3 to check the S3 access properties.
• B. Query the flow logs for the VPC. Determine whether the traffic that originates from the EMR cluster can successfully reach the data providers. Determine whether any security group that might be attached to the Amazon EMR cluster allows connections to the data source servers on the informed ports.
• C. Check the retry scenarios that the company configured for the EMR jobs. Increase the number of seconds in the interval between each EMR task. Validate that each fallback state has the appropriate catch for each decision state. Configure an Amazon Simple Notification Service (Amazon SNS) topic to store the error messages.
• D. Check for entries in Amazon CloudWatch for the newly created EMR cluster. Change the AWS Step Functions state machine code to use Amazon EMR on EKS. Change the IAM access policies and the security group configuration for the Step Functions state machine code to reflect inclusion of Amazon Elastic Kubernetes Service (Amazon EKS).
• E. Use AWS CloudFormation to automate the Step Functions state machine deployment. Create a step to pause the state machine during the EMR jobs that fail. Configure the step to wait for a human user to send approval through an email message. Include details of the EMR task in the email message for further analysis.

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Pivoting in SQL is mainly used to transform data from:

• A. Multiple columns into multiple rows
• B. Only one column to one row
• C. One row to one column
• D. Multiple rows into multiple columns