A company uses Amazon Redshift for its data warehouse. A data engineer must query a table named orders.complete_orders_history, which contains 100 columns. The query must return all columns except columns named companyId and unique_system_id.
Which Amazon Redshift SQL statement will meet this requirement?
A.
B.
C.
D.
Show Answer
Correct Answer: A
Explanation: Amazon Redshift supports the SELECT * EXCLUDE syntax to return all columns except specified columns. To exclude companyId and unique_system_id, use: SELECT * EXCLUDE (companyId, unique_system_id) FROM orders.complete_orders_history;. EXCEPT is a set operator that removes rows from one query based on another query, not columns.
Question 12
An application uses an AWS Lambda function that is configured with managed runtimes. The Lambda function successfully writes logs to the default Amazon CloudWatch Logs log group. A data engineer wants to modify the logging behavior to show only ERROR level logs for application logs and WARN level logs for system logs.
Which solution will meet these requirements?
A. Add additional permissions to the Lambda execution role.
B. Set the log level to ERROR in the Lambda function code.
C. Configure the Lambda function to use the JSON log format.
D. Configure the Lambda function to send logs to a custom log group.
Show Answer
Correct Answer: B
Explanation: For Lambda functions using managed runtimes, application log verbosity can be controlled via log levels. Among the given options, only setting the application log level to ERROR aligns with the requirement to emit only ERROR-level application logs. The other options (IAM permissions, JSON log format, or a custom log group) do not control log severity filtering. Although AWS advanced logging controls support separate application and system log levels, no configuration option for those controls is offered in the choices, making B the best match.
Question 13
A data engineer is writing a query to join two tables in Amazon Athena. The data engineer needs to choose the correct join order for the tables to optimize query performance.
Which solution will meet these requirements?
A. Specify the smaller table on the left side of the join and the larger table on the right side of the join.
B. Specify the larger table on the left side of the join and the smaller table on the right side of the join.
C. Use AWS Glue to pre-process the tables before performing the join.
D. Use table statistics to automatically determine the join order.
Show Answer
Correct Answer: B
Explanation: In Athena (Presto/Trino), the right side of a distributed hash join is typically used as the build side. Placing the smaller table on the right reduces memory usage and improves join performance. Although cost-based optimization can reorder joins when statistics are available, the question asks which join order the engineer should choose when writing the query.
Question 14
A company has a data pipeline that processes transaction data in real time. The company needs a notification system that alerts different teams based on the type of processing error without any delay. For security-related errors, the system must immediately notify the security team. For data validation errors, the system must notify the data quality team. For system errors, the system must notify the operations team.
Which solution will meet these requirements with the LEAST operational overhead?
A. Create an Amazon Simple Notification Service (Amazon SNS) topic with an AWS Lambda function subscriber that evaluates the error type and forwards the error to the appropriate email addresses.
B. Configure Amazon EventBridge rules with distinct event patterns for each error type. Route each error type to a dedicated Amazon Simple Notification Service (Amazon SNS) topic for team-specific alerts.
C. Use Amazon Simple Queue Service (Amazon SQS) with message attributes to categorize errors. Allow each team to poll their respective SQS queue for relevant errors.
D. Set up Amazon CloudWatch alarms with different metrics for each error type. Invoke a different Amazon Simple Notification Service (Amazon SNS) notification each time a metrics threshold is crossed.
Show Answer
Correct Answer: B
Explanation: Amazon EventBridge can match events by error type using event patterns and route each type directly to a dedicated Amazon SNS topic for immediate notifications. This avoids custom routing code, provides near real-time event-driven delivery, and has lower operational overhead than using a Lambda router. SQS requires polling and is not immediate, while CloudWatch alarms are intended for metric thresholds rather than per-event error routing.
Question 15
A company stores a 100 MB dataset in an Amazon S3 bucket as an Apache Parquet file. A data engineer needs to profile the data before performing data preparation steps on the data.
Which solution will meet this requirement in the MOST operationally efficient way?
A. Create a profile job on the dataset in AWS Glue DataBrew. Review the profile job results.
B. Stream the data into Amazon Managed Service for Apache Flink for SQL queries. Use the Apache Flink dashboard to profile the data.
C. Ingest the data into Amazon Redshift Spectrum. Use SQL queries to profile the data.
D. Load the data into an Amazon QuickSight dataset. Build a topic to profile the data with questions.
Show Answer
Correct Answer: A
Explanation: AWS Glue DataBrew includes built-in data profiling capabilities designed to analyze datasets stored in Amazon S3, including Parquet files. A profile job generates statistics, schema information, missing values, distributions, and data quality insights with minimal setup, making it the most operationally efficient choice before data preparation. The other options require provisioning or using services that are not intended primarily for data profiling and involve more operational overhead.
Question 16
A data engineer needs a fully automated solution to check for new data in multiple databases and process data that the solution finds. The solution must run every hour. The solution must be compatible with Amazon RDS, Amazon DynamoDB, and Amazon OpenSearch Service. The solution must be able to process up to 10 MB of data at one time. The solution must be optimized for costs and operational overhead. The solution must have robust error handling capabilities.
Which solution will meet these requirements?
A. Use Amazon EventBridge to invoke AWS Step Functions every hour to deploy an AWS Lambda function to check for data. Configure Step Functions steps to process data that the Lambda function finds. Implement error handling in each state.
B. Use Amazon EventBridge to invoke an AWS Lambda function every hour to check for data. Configure the function to send a message to an Amazon Simple Queue Service (Amazon SQS) queue when the function finds new data. Use a second Lambda function to read the queue and perform the processing.
C. Configure an Apache Spark application to run on Amazon EMR to check for data. Implement error handling in the application. Use Amazon EventBridge to invoke the application every hour.
D. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to create a workflow that runs a directed acyclic graph (DAG) every hour to check for data. Configure the DAG to process identified data. Implement error handling in a Python operator.
Show Answer
Correct Answer: A
Explanation: EventBridge can trigger a Step Functions state machine every hour. A Lambda task can poll Amazon RDS, DynamoDB, and OpenSearch Service for new data, and Step Functions can orchestrate the processing with built-in retries, catches, and error handling. This serverless approach has low operational overhead and directly satisfies the explicit requirement for robust error handling better than a simple Lambda+SQS flow.
Sources:
https://www.dumpspedia.com/aws-certified-data-engineer-associate-dea-c01-dumps.html
Question 17
A company needs to store semi-structured transactional data for an application in a database. The database must be serverless. The application writes the data infrequently, but it reads the data frequently. The application must retrieve the data within milliseconds.
Which solution will meet these requirements with the LEAST operational overhead?
A. Store the data in an Amazon S3 Standard bucket. Enable S3 Transfer Acceleration.
B. Store the data in an Amazon S3 Apache Iceberg table. Enable S3 Transfer Acceleration.
C. Store the data in an Amazon RDS for MySQL cluster. Configure RDS Optimized Reads for the cluster.
D. Store the data in an Amazon DynamoDB table. Configure a DynamoDB Accelerator cache.
Show Answer
Correct Answer: D
Explanation: Amazon DynamoDB is a fully managed serverless NoSQL database designed for semi-structured data. It provides single-digit millisecond reads, and adding DynamoDB Accelerator (DAX) further reduces read latency for frequently accessed data. The workload is write-infrequent and read-heavy, making DAX an appropriate fit. Amazon S3 and Iceberg are object storage/analytics solutions rather than low-latency transactional databases, and Amazon RDS is not serverless in the configuration described.
Question 18
A company needs a solution that restricts access to Amazon S3 data and encrypts the data by using AWS managed keys. The solution must manage database credentials that an AWS Lambda function uses and must rotate the credentials automatically.
Which solution will meet these requirements?
A. Use S3 bucket policies to control access. Use server-side encryption with Amazon S3 managed keys (SSE-S3) to encrypt the data. Store the database credentials as Lambda environment variables.
B. Use IAM policies to control access. Use server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the data. Configure AWS Secrets Manager to store and automatically rotate the credentials by using a Lambda function.
C. Use S3 ACLs to control access. Use server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the data. Store the credentials in AWS Systems Manager Parameter Store and automatically rotate the credentials by using a Lambda function.
D. Use IAM policies to control access. Use server-side encryption with Amazon S3 managed keys (SSE-S3) to encrypt the data. Store the credentials in AWS Systems Manager Parameter Store. Configure a scheduled Lambda function to rotate the credentials.
Show Answer
Correct Answer: B
Explanation: IAM policies are the recommended mechanism to control access to Amazon S3. Encryption with AWS managed keys is satisfied by SSE-KMS using AWS KMS keys managed by AWS. AWS Secrets Manager is designed to securely store database credentials and supports automatic rotation through a Lambda rotation function. SSE-S3 uses S3-managed keys rather than AWS KMS managed keys, and storing credentials in Lambda environment variables or Parameter Store does not best meet the automatic database credential rotation requirement.
Question 19
A university is developing an educational application that analyzes student essays. The application provides personalized feedback with accurate citations to the university's textbooks. The application needs to process essays in multiple languages. Application responses must include direct references to specific sections in the course materials and must be in the student’s selected language.
Which solution will meet these requirements with the LEAST operational overhead?
A. Build a custom vector database by using Amazon OpenSearch Serverless. Store textbook content as multilingual embeddings. Create an AWS Lambda function that queues the database when generating responses with Amazon Bedrock.
B. Create a knowledge base in Amazon Bedrock Knowledge Bases with the university’s textbooks. Configure a multilingual model to generate responses with source citations.
C. Use Amazon Comprehend to detect the language and key topics in the essays. Use Amazon Kendra to search for relevant textbook passages. Create an AWS Lambda function that formats the textbook passages into feedback.
D. Use Amazon SageMaker to host a custom-trained large language model (LLM) that has been fine-tuned on the university’s textbooks to generate personalized feedback with citations.
Show Answer
Correct Answer: B
Explanation: Amazon Bedrock Knowledge Bases provides a managed RAG solution that indexes the university textbooks, retrieves relevant passages, and can return source citations. Using a multilingual foundation model enables responses in the student's selected language while grounding answers in the course materials. This avoids building and operating a custom vector database, search pipeline, or hosting a fine-tuned model, resulting in the least operational overhead.
Sources:
https://aws.amazon.com/blogs/publicsector/empowering-personalized-learning-at-scale-loyola-marymount-universitys-ai-course-companion
Question 20
A media company uploads large video files to Amazon S3 for processing. After processing, the company needs to keep the original files for 90 days in case the files require reprocessing. After 90 days, the company can delete the files to reduce storage costs. The company stores the processed videos in a different S3 bucket.
Which S3 Lifecycle configuration will meet these requirements for the original files MOST cost-effectively?
A. Store the files in S3 Standard for 90 days. Transition the files to S3 Glacier Flexible Retrieval for long-term storage. Then expire the files.
B. Store the files in S3 Standard for 90 days. Enable versioning. Enable Object Lock on the files for 90 days. Then expire the files.
C. Store the files in S3 Standard for 90 days. Implement S3 Lifecycle management to expire the files.
D. Store the files in S3 Intelligent-Tiering for 90 days. Enable versioning. Add S3 Lifecycle management to expire the files.
Show Answer
Correct Answer: C
Explanation: The requirement is to retain the original objects for 90 days and then delete them. There is no need for archival beyond 90 days, versioning, Object Lock, or Intelligent-Tiering. A lifecycle expiration rule that deletes objects after 90 days is the simplest and most cost-effective solution while keeping the objects in S3 Standard during the required retention period.
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