A company needs to implement a workflow to process transactions. Each transaction goes through multiple levels of validation. Each validation level depends on the preceding validation level.
The workflow must either process or reject each transaction within 24-hours. The workflow must run for less than 24 hours total.
Which solution will meet these requirements with the LEAST operational cost?

• A. Create an express workflow in AWS Step Functions. Implement a Wait for Callback pattern to wait for the validation steps to finish.
• B. Create a standard workflow in AWS Step Functions. Implement a Wait for Callback pattern to wait for the validation steps to finish.
• C. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to implement the workflow.
• D. Use AWS Lambda functions to implement the workflow. Use Amazon EventBridge to invoke the validation steps.

A data engineer needs to create an Amazon Athena table based on a subset of data from an existing Athena table named cities_world. The cities_world table contains cities that are located around the world. The data engineer must create a new table named cities_us to contain only the cities from cities_world that are located in the US.
Which SQL statement should the data engineer use to meet this requirement?

• A. MOVE city, state FROM cities_world TO cities_usa WHERE country='usa';
• B. INSERT INTO cities_usa SELECT city, state FROM cities_world WHERE country='usa';
• C. UPDATE cities_usa SET (city, state) = (SELECT city, state FROM cities_world WHERE country='usa');
• D. INSERT INTO cities_usa (city,state) SELECT city, state FROM cities_world WHERE country='usa';

A company maintains an Amazon Redshift provisioned cluster that the company uses for extract, transform, and load (ETL) operations to support critical analysis tasks. A sales team within the company maintains a Redshift cluster that the sales team uses for business intelligence (BI) tasks.
The sales team recently requested access to the data that is in the ETL Redshift cluster so the team can perform weekly summary analysis tasks. The sales team needs to join data from the ETL cluster with data that is in the sales team's BI cluster.
The company needs a solution that will share the ETL cluster data with the sales team without interrupting the critical analysis tasks. The solution must minimize usage of the computing resources of the ETL cluster.
Which solution will meet these requirements?

• A. Create database views based on the sales team's requirements. Grant the sales team direct access to the ETL cluster.
• B. Create materialized views based on the sales team's requirements. Grant the sales team direct access to the ETL cluster.
• C. Set up the sales team BI cluster as a consumer of the ETL cluster by using Redshift data sharing.
• D. Unload a copy of the data from the ETL cluster to an Amazon S3 bucket every week. Create an Amazon Redshift Spectrum table based on the content of the ETL cluster.

A data engineer notices that Amazon Athena queries are held in a queue before the queries run.
How can the data engineer prevent the queries from queueing?

• A. Allow users who run the Athena queries to an existing workgroup.
• B. Increase the query result limit.
• C. Configure provisioned capacity for an existing workgroup.
• D. Use federated queries.