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

1. A company uses an Amazon Redshift provisioned cluster as its database. The Redshift cluster has five reserved ra3.4xlarge nodes and uses key distribution.
A data engineer notices that one of the nodes frequently has a CPU load over 90%. SQL Queries that run on the node are queued. The other four nodes usually have a CPU load under 15% during daily operations.
The data engineer wants to maintain the current number of compute nodes. The data engineer also wants to balance the load more evenly across all five compute nodes.
Which solution will meet these requirements?

A) Change the primary key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.
B) Upgrade the reserved node from ra3.4xlarqe to ra3.16xlarqe.
C) Change the distribution key to the table column that has the largest dimension.
D) Change the sort key to be the data column that is most often used in a WHERE clause of the SQL SELECT statement.

2. A company needs to collect logs for an Amazon RDS for MySQL database and make the logs available for audits. The logs must track each user that modifies data in the database or makes changes to the database instance.
Which solution will meet these requirements?

A) Configure an Amazon EventBridge rule to monitor database activity. Create an AWS Lambda function to process EventBridge events and store them in Amazon OpenSearch Service.
B) Enable and configure native Amazon RDS database audit logging. Enable Amazon CloudWatch Logs.Configure metric filters and alarms. Configure AWS CloudTrail audit logging.
C) Enable Amazon CloudWatch Logs. Create metric filters to monitor database changes and instance-level changes. Configure automated notification systems to send near real-time alerts for suspicious database operations.
D) Configure AWS CloudTrail to log API calls. Use Amazon CloudWatch Logs for basic monitoring. Use IAM policies to control access to the logs. Set up scheduled reporting for log audits.

3. A media company uses software as a service (SaaS) applications to gather data by using third-party tools. The company needs to store the data in an Amazon S3 bucket. The company will use Amazon Redshift to perform analytics based on the data.
Which AWS service or feature will meet these requirements with the LEAST operational overhead?

A) Amazon Managed Streaming for Apache Kafka (Amazon MSK)
B) Amazon Kinesis
C) Amazon AppFlow
D) AWS Glue Data Catalog

4. A healthcare company uses Amazon Kinesis Data Streams to stream real-time health data from wearable devices, hospital equipment, and patient records.
A data engineer needs to find a solution to process the streaming data. The data engineer needs to store the data in an Amazon Redshift Serverless warehouse. The solution must support near real-time analytics of the streaming data and the previous day ' s data.
Which solution will meet these requirements with the LEAST operational overhead?

A) Use the Amazon Aurora zero-ETL integration with Amazon Redshift.
B) Load data into Amazon Kinesis Data Firehose. Load the data into Amazon Redshift.
C) Load the data into Amazon S3. Use the COPY command to load the data into Amazon Redshift.
D) Use the streaming ingestion feature of Amazon Redshift.

5. A financial services company stores financial data in Amazon Redshift. A data engineer wants to run real- time queries on the financial data to support a web-based trading application. The data engineer wants to run the queries from within the trading application.
Which solution will meet these requirements with the LEAST operational overhead?

A) Establish WebSocket connections to Amazon Redshift.
B) Store frequently accessed data in Amazon S3. Use Amazon S3 Select to run the queries.
C) Use the Amazon Redshift Data API.
D) Set up Java Database Connectivity (JDBC) connections to Amazon Redshift.

Solutions: