DEA-C01

A data engineer is configuring an AWS Glue job to read data from an Amazon S3 bucket. The data engineer has set up the necessary AWS Glue connection details and an associated IAM role. However, when the data engineer attempts to run the AWS Glue job, the data engineer receives an error message that indicates that there are problems with the Amazon S3 VPC gateway endpoint. The data engineer must resolve the error and connect the AWS Glue job to the S3 bucket. Which solution will meet this requirement? Options: A. Update the AWS Glue security group to allow inbound traffic from the Amazon S3 VPC gateway endpoint. B. Configure an S3 bucket policy to explicitly grant the AWS Glue job permissions to access the S3 bucket. C. Review the AWS Glue job code to ensure that the AWS Glue connection details include a fully qualified domain name. D. Verify that the VPC's route table includes inbound and outbound routes for the Amazon S3 VPC gateway endpoint.

A retail company has a customer data hub in an Amazon S3 bucket. Employees from many countries use the data hub to support company-wide analytics. A governance team must ensure that the company's data analysts can access data only for customers who are within the same country as the analysts. Which solution will meet these requirements with the LEAST operational effort? Options: A. Create a separate table for each country's customer data. Provide access to each analyst based on the country that the analyst serves. B. Register the S3 bucket as a data lake location in AWS Lake Formation. Use the Lake Formation row-level security features to enforce the company's access policies. C. Move the data to AWS Regions that are close to the countries where the customers are. Provide access to each analyst based on the country that the analyst serves. D. Load the data into Amazon Redshift. Create a view for each country. Create separate IAM roles for each country to provide access to data from each country. Assign the appropriate roles to the analysts.

A media company wants to improve a system that recommends media content to customer based on user behavior and preferences. To improve the recommendation system, the company needs to incorporate insights from third-party datasets into the company's existing analytics platform. The company wants to minimize the effort and time required to incorporate third-party datasets. Which solution will meet these requirements with the LEAST operational overhead? Options: A. Use API calls to access and integrate third-party datasets from AWS Data Exchange. B. Use API calls to access and integrate third-party datasets from AWS DataSync. C. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from AWS CodeCommit repositories. D. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from Amazon Elastic Container Registry (Amazon ECR).

A financial company wants to implement a data mesh. The data mesh must support centralized data governance, data analysis, and data access control. The company has decided to use AWS Glue for data catalogs and extract, transform, and load (ETL) operations. Which combination of AWS services will implement a data mesh? (Choose two.) Options: A. Use Amazon Aurora for data storage. Use an Amazon Redshift provisioned cluster for data analysis. B. Use Amazon S3 for data storage. Use Amazon Athena for data analysis. C. Use AWS Glue DataBrew for centralized data governance and access control. D. Use Amazon RDS for data storage. Use Amazon EMR for data analysis. E. Use AWS Lake Formation for centralized data governance and access control.

A data engineer maintains custom Python scripts that perform a data formatting process that many AWS Lambda functions use. When the data engineer needs to modify the Python scripts, the data engineer must manually update all the Lambda functions. The data engineer requires a less manual way to update the Lambda functions. Which solution will meet this requirement? Options: A. Store a pointer to the custom Python scripts in the execution context object in a shared Amazon S3 bucket. B. Package the custom Python scripts into Lambda layers. Apply the Lambda layers to the Lambda functions. C. Store a pointer to the custom Python scripts in environment variables in a shared Amazon S3 bucket. D. Assign the same alias to each Lambda function. Call reach Lambda function by specifying the function's alias.

A company created an extract, transform, and load (ETL) data pipeline in AWS Glue. A data engineer must crawl a table that is in Microsoft SQL Server. The data engineer needs to extract, transform, and load the output of the crawl to an Amazon S3 bucket. The data engineer also must orchestrate the data pipeline. Which AWS service or feature will meet these requirements MOST cost-effectively? Options: A. AWS Step Functions B. AWS Glue workflows C. AWS Glue Studio D. Amazon Managed Workflows for Apache Airflow (Amazon MWAA)

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

A company uses Amazon Athena for one-time queries against data that is in Amazon S3. The company has several use cases. The company must implement permission controls to separate query processes and access to query history among users, teams, and applications that are in the same AWS account. Which solution will meet these requirements? Options: A. Create an S3 bucket for each use case. Create an S3 bucket policy that grants permissions to appropriate individual IAM users. Apply the S3 bucket policy to the S3 bucket. B. Create an Athena workgroup for each use case. Apply tags to the workgroup. Create an IAM policy that uses the tags to apply appropriate permissions to the workgroup. C. Create an IAM role for each use case. Assign appropriate permissions to the role for each use case. Associate the role with Athena. D. Create an AWS Glue Data Catalog resource policy that grants permissions to appropriate individual IAM users for each use case. Apply the resource policy to the specific tables that Athena uses.

A data engineer needs to schedule a workflow that runs a set of AWS Glue jobs every day. The data engineer does not require the Glue jobs to run or finish at a specific time. Which solution will run the Glue jobs in the MOST cost-effective way? Options: A. Choose the FLEX execution class in the Glue job properties. B. Use the Spot Instance type in Glue job properties. C. Choose the STANDARD execution class in the Glue job properties. D. Choose the latest version in the GlueVersion field in the Glue job properties.

A data engineer needs to create an AWS Lambda function that converts the format of data from .csv to Apache Parquet. The Lambda function must run only if a user uploads a .csv file to an Amazon S3 bucket. Which solution will meet these requirements with the LEAST operational overhead? Options: A. Create an S3 event notification that has an event type of s3:ObjectCreated:*. Use a filter rule to generate notifications only when the suffix includes .csv. Set the Amazon Resource Name (ARN) of the Lambda function as the destination for the event notification. B. Create an S3 event notification that has an event type of s3:ObjectTagging:* for objects that have a tag set to .csv. Set the Amazon Resource Name (ARN) of the Lambda function as the destination for the event notification. C. Create an S3 event notification that has an event type of s3:*. Use a filter rule to generate notifications only when the suffix includes .csv. Set the Amazon Resource Name (ARN) of the Lambda function as the destination for the event notification. D. Create an S3 event notification that has an event type of s3:ObjectCreated:*. Use a filter rule to generate notifications only when the suffix includes .csv. Set an Amazon Simple Notification Service (Amazon SNS) topic as the destination for the event notification. Subscribe the Lambda function to the SNS topic.

A data engineer needs Amazon Athena queries to finish faster. The data engineer notices that all the files the Athena queries use are currently stored in uncompressed .csv format. The data engineer also notices that users perform most queries by selecting a specific column. Which solution will MOST speed up the Athena query performance? Options: A. Change the data format from .csv to JSON format. Apply Snappy compression. B. Compress the .csv files by using Snappy compression. C. Change the data format from .csv to Apache Parquet. Apply Snappy compression. D. Compress the .csv files by using gzip compression.

A manufacturing company collects sensor data from its factory floor to monitor and enhance operational efficiency. The company uses Amazon Kinesis Data Streams to publish the data that the sensors collect to a data stream. Then Amazon Kinesis Data Firehose writes the data to an Amazon S3 bucket. The company needs to display a real-time view of operational efficiency on a large screen in the manufacturing facility. Which solution will meet these requirements with the LOWEST latency? Options: A. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Use a connector for Apache Flink to write data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard. B. Configure the S3 bucket to send a notification to an AWS Lambda function when any new object is created. Use the Lambda function to publish the data to Amazon Aurora. Use Aurora as a source to create an Amazon QuickSight dashboard. C. Use Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to process the sensor data. Create a new Data Firehose delivery stream to publish data directly to an Amazon Timestream database. Use the Timestream database as a source to create an Amazon QuickSight dashboard. D. Use AWS Glue bookmarks to read sensor data from the S3 bucket in real time. Publish the data to an Amazon Timestream database. Use the Timestream database as a source to create a Grafana dashboard.

A company stores daily records of the financial performance of investment portfolios in .csv format in an Amazon S3 bucket. A data engineer uses AWS Glue crawlers to crawl the S3 data. The data engineer must make the S3 data accessible daily in the AWS Glue Data Catalog. Which solution will meet these requirements? Options: A. Create an IAM role that includes the AmazonS3FullAccess policy. Associate the role with the crawler. Specify the S3 bucket path of the source data as the crawler's data store. Create a daily schedule to run the crawler. Configure the output destination to a new path in the existing S3 bucket. B. Create an IAM role that includes the AWSGlueServiceRole policy. Associate the role with the crawler. Specify the S3 bucket path of the source data as the crawler's data store. Create a daily schedule to run the crawler. Specify a database name for the output. C. Create an IAM role that includes the AmazonS3FullAccess policy. Associate the role with the crawler. Specify the S3 bucket path of the source data as the crawler's data store. Allocate data processing units (DPUs) to run the crawler every day. Specify a database name for the output. D. Create an IAM role that includes the AWSGlueServiceRole policy. Associate the role with the crawler. Specify the S3 bucket path of the source data as the crawler's data store. Allocate data processing units (DPUs) to run the crawler every day. Configure the output destination to a new path in the existing S3 bucket.

A company loads transaction data for each day into Amazon Redshift tables at the end of each day. The company wants to have the ability to track which tables have been loaded and which tables still need to be loaded. A data engineer wants to store the load statuses of Redshift tables in an Amazon DynamoDB table. The data engineer creates an AWS Lambda function to publish the details of the load statuses to DynamoDB. How should the data engineer invoke the Lambda function to write load statuses to the DynamoDB table? Options: A. Use a second Lambda function to invoke the first Lambda function based on Amazon CloudWatch events. B. Use the Amazon Redshift Data API to publish an event to Amazon EventBridge. Configure an EventBridge rule to invoke the Lambda function. C. Use the Amazon Redshift Data API to publish a message to an Amazon Simple Queue Service (Amazon SQS) queue. Configure the SQS queue to invoke the Lambda function. D. Use a second Lambda function to invoke the first Lambda function based on AWS CloudTrail events.

A data engineer needs to securely transfer 5 TB of data from an on-premises data center to an Amazon S3 bucket. Approximately 5% of the data changes every day. Updates to the data need to be regularly proliferated to the S3 bucket. The data includes files that are in multiple formats. The data engineer needs to automate the transfer process and must schedule the process to run periodically. Which AWS service should the data engineer use to transfer the data in the MOST operationally efficient way? Options: A. AWS DataSync B. AWS Glue C. AWS Direct Connect D. Amazon S3 Transfer Acceleration

A company uses an on-premises Microsoft SQL Server database to store financial transaction data. The company migrates the transaction data from the on-premises database to AWS at the end of each month. The company has noticed that the cost to migrate data from the on-premises database to an Amazon RDS for SQL Server database has increased recently. The company requires a cost-effective solution to migrate the data to AWS. The solution must cause minimal downtown for the applications that access the database. Which AWS service should the company use to meet these requirements? Options: A. AWS Lambda B. AWS Database Migration Service (AWS DMS) C. AWS Direct Connect D. AWS DataSync

A data engineer is building a data pipeline on AWS by using AWS Glue extract, transform, and load (ETL) jobs. The data engineer needs to process data from Amazon RDS and MongoDB, perform transformations, and load the transformed data into Amazon Redshift for analytics. The data updates must occur every hour. Which combination of tasks will meet these requirements with the LEAST operational overhead? (Choose two.) Options: A. Configure AWS Glue triggers to run the ETL jobs every hour. B. Use AWS Glue DataBrew to clean and prepare the data for analytics. C. Use AWS Lambda functions to schedule and run the ETL jobs every hour. D. Use AWS Glue connections to establish connectivity between the data sources and Amazon Redshift. E. Use the Redshift Data API to load transformed data into Amazon Redshift.

A company uses an Amazon Redshift cluster that runs on RA3 nodes. The company wants to scale read and write capacity to meet demand. A data engineer needs to identify a solution that will turn on concurrency scaling. Which solution will meet this requirement? Options: A. Turn on concurrency scaling in workload management (WLM) for Redshift Serverless workgroups. B. Turn on concurrency scaling at the workload management (WLM) queue level in the Redshift cluster. C. Turn on concurrency scaling in the settings during the creation of any new Redshift cluster. D. Turn on concurrency scaling for the daily usage quota for the Redshift cluster.

A data engineer must orchestrate a series of Amazon Athena queries that will run every day. Each query can run for more than 15 minutes. Which combination of steps will meet these requirements MOST cost-effectively? (Choose two.) Options: A. Use an AWS Lambda function and the Athena Boto3 client start_query_execution API call to invoke the Athena queries programmatically. B. Create an AWS Step Functions workflow and add two states. Add the first state before the Lambda function. Configure the second state as a Wait state to periodically check whether the Athena query has finished using the Athena Boto3 get_query_execution API call. Configure the workflow to invoke the next query when the current query has finished running. C. Use an AWS Glue Python shell job and the Athena Boto3 client start_query_execution API call to invoke the Athena queries programmatically. D. Use an AWS Glue Python shell script to run a sleep timer that checks every 5 minutes to determine whether the current Athena query has finished running successfully. Configure the Python shell script to invoke the next query when the current query has finished running. E. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate the Athena queries in AWS Batch.

A company is migrating on-premises workloads to AWS. The company wants to reduce overall operational overhead. The company also wants to explore serverless options. The company's current workloads use Apache Pig, Apache Oozie, Apache Spark, Apache Hbase, and Apache Flink. The on-premises workloads process petabytes of data in seconds. The company must maintain similar or better performance after the migration to AWS. Which extract, transform, and load (ETL) service will meet these requirements? Options: A. AWS Glue B. Amazon EMR C. AWS Lambda D. Amazon Redshift