QUESTION 41
A data engineer is optimizing query performance in Amazon Athena notebooks that use Apache Spark to analyze large datasets that are stored in Amazon S3. The data is partitioned. An AWS Glue crawler updates the partitions. The data engineer wants to minimize the amount of data that is scanned to improve efficiency of Athena queries. Which solution will meet these requirements?

A. Apply partition filters in the queries.
B. Increase the frequency of AWS Glue crawler invocations to update the data catalog more often.
C. Organize the data that is in Amazon S3 by using a nested directory structure.
D. Configure Spark to use in-memory caching for frequently accessed data.

Correct Answer: A

QUESTION 42
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? (Select TWO.)

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.

Correct Answer: BE

QUESTION 43
A company has a data processing pipeline that includes several dozen steps. The data processing pipeline needs to send alerts in real time when a step fails or succeeds. The data processing pipeline uses a combination of Amazon S3 buckets, AWS Lambda functions, and AWS Step Functions state machines. A data engineer needs to create a solution to monitor the entire pipeline. Which solution will meet these requirements?

A. Configure the Step Functions state machines to store notifications in an Amazon S3 bucket when the state machines finish running. Enable S3 event notifications on the S3 bucket.
B. Configure the AWS Lambda functions to store notifications in an Amazon S3 bucket when the state machines finish running. Enable S3 event notifications on the S3 bucket.
C. Use AWS CloudTrail to send a message to an Amazon Simple Notification Service (Amazon SNS) topic that sends notifications when a state machine fails to run or succeeds to run.
D. Configure an Amazon EventBridge rule to react when the execution status of a state machine changes. Configure the rule to send a message to an Amazon Simple Notification Service (Amazon SNS) topic that sends notifications.

Correct Answer: D

QUESTION 44
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?

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.

Correct Answer: B

QUESTION 45
A company has three subsidiaries. Each subsidiary uses a different data warehousing solution. The first subsidiary hosts its data warehouse in Amazon Redshift. The second subsidiary uses Teradata Vantage on AWS. The third subsidiary uses Google BigQuery. The company wants to aggregate all the data into a central Amazon S3 data lake. The company wants to use Apache Iceberg as the table format. A data engineer needs to build a new pipeline to connect to all the data sources, run transformations by using each source engine, join the data, and write the data to Iceberg. Which solution will meet these requirements with the LEAST operational effort?

A. Use native Amazon Redshift, Teradata, and BigQuery connectors to build the pipeline in AWS Glue. Use native AWS Glue transforms to join the data. Run a Merge operation on the data lake Iceberg table.
B. Use the Amazon Athena federated query connectors for Amazon Redshift, Teradata, and BigQuery to build the pipeline in Athena. Write a SQL query to read from all the data sources, join the data, and run a Merge operation on the data lake Iceberg table.
C. Use the native Amazon Redshift connector, the Java Database Connectivity (JDBC) connector for Teradata, and the open source Apache Spark BigQuery connector to build the pipeline in Amazon EMR. Write code in PySpark to join the data. Run a Merge operation on the data lake Iceberg table.
D. Use the native Amazon Redshift, Teradata, and BigQuery connectors in Amazon Appflow to write data to Amazon S3 and AWS Glue Data Catalog. Use Amazon Athena to join the data. Run a Merge operation on the data lake Iceberg table.

Correct Answer: B

QUESTION 46
A company has a gaming application that stores data in Amazon DynamoDB tables. A data engineer needs to ingest the game data into an Amazon OpenSearch Service cluster. Data updates must occur in near real time. Which solution will meet these requirements?

A. Use AWS Step Functions to periodically export data from the Amazon DynamoDB tables to an Amazon S3 bucket. Use an AWS Lambda function to load the data into Amazon OpenSearch Service.
B. Configure an AWS Glue job to have a source of Amazon DynamoDB and a destination of Amazon OpenSearch Service to transfer data in near real time.
C. Use Amazon DynamoDB Streams to capture table changes. Use an AWS Lambda function to process and update the data in Amazon OpenSearch Service.
D. Use a custom OpenSearch plugin to sync data from the Amazon DynamoDB tables.

Correct Answer: C

QUESTION 47
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?

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.

Correct Answer: B

QUESTION 48
A company wants to migrate an application and an on-premises Apache Kafka server to AWS. The application processes incremental updates that an on-premises Oracle database sends to the Kafka server. The company wants to use the replatform migration strategy instead of the refactor strategy. Which solution will meet these requirements with the LEAST management overhead?

A. Amazon Kinesis Data Streams
B. Amazon Managed Streaming for Apache Kafka (Amazon MSK) provisioned cluster
C. Amazon Data Firehose
D. Amazon Managed Streaming for Apache Kafka (Amazon MSK) Serverless

Correct Answer: D

QUESTION 49
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 EL 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. Set up the sales team BI cluster as a consumer of the ETL cluster by using Redshift data sharing.
B. Create materialized views based on the sales team’s requirements. Grant the sales team direct access to the ETL cluster.
C. Create database views based on the sales team’s requirements. Grant the sales team direct access to the ETL cluster.
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.

Correct Answer: A

QUESTION 50
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 a standard workflow in AWS Step Functions. Implement a Wait for Callback pattern to wait for the validation steps to finish.
B. Create an express workflow in AWS Step Functions. Implement a Wait for Callback pattern to wait for the validation steps to finish.
C. Use AWS Lambda functions to implement the workflow. Use Amazon EventBridge to invoke the validation steps.
D. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to implement the workflow.

Correct Answer: A

QUESTION 51
A company stores petabytes of data in thousands of Amazon S3 buckets in the S3 Standard storage class. The data supports analytics workloads that have unpredictable and variable data access patterns. The company does not access some data for months. However, the company must be able to retrieve all data within milliseconds. The company needs to optimize S3 storage costs. Which solution will meet these requirements with the LEAST operational overhead?

A. Use S3 Storage Lens standard metrics to determine when to move objects to more cost-optimized storage classes. Create S3 Lifecycle policies for the S3 buckets to move objects to cost-optimized storage classes. Continue to refine the S3 Lifecycle policies in the future to optimize storage costs.
B. Use S3 Storage Lens activity metrics to identify S3 buckets that the company accesses infrequently. Configure S3 Lifecycle rules to move objects from S3 Standard to the S3 Standard-Infrequent Access (S3 Standard-IA) and S3 Glacier storage classes based on the age of the data.
C. Use S3 Intelligent-Tiering. Activate the Deep Archive Access tier.
D. Use S3 Intelligent-Tiering. Use the default access tier.

Correct Answer: D

QUESTION 52
A company has a data lake in Amazon S3. The company collects AWS CloudTrail logs for multiple applications. The company stores the logs in the data lake, catalogs the logs in AWS Glue, and partitions the logs based on the year. The company uses Amazon Athena to analyze the logs. Recently, customers reported that a query on one of the Athena tables did not return any data. A data engineer must resolve the issue. Which combination of troubleshooting steps should the data engineer take? (Select TWO.)

A. Confirm that Athena is pointing to the correct Amazon S3 location.
B. Increase the query timeout duration.
C. Use the MSCK REPAIR TABLE command.
D. Restart Athena.
E. Delete and recreate the problematic Athena table.

Correct Answer: AC

QUESTION 53
The company stores a large volume of customer records in Amazon S3. To comply with regulations, the company must be able to access new customer records immediately for the first 30 days after the records are created. The company accesses records that are older than 30 days infrequently. The company needs to cost-optimize its Amazon S3 storage. Which solution will meet these requirements MOST cost-effectively?

A. Apply a lifecycle policy to transition records to S3 Standard Infrequent-Access (S3 Standard-IA) storage after 30 days.
B. Use S3 Intelligent-Tiering storage.
C. Transition records to S3 Glacier Deep Archive storage after 30 days.
D. Use S3 Standard-Infrequent Access (S3 Standard-IA) storage for all customer records.

Correct Answer: A

QUESTION 54
A data engineer runs Amazon Athena queries on data that is in an Amazon S3 bucket. The Athena queries use AWS Glue Data Catalog as a metadata table. The data engineer notices that the Athena query plans are experiencing a performance bottleneck. The data engineer determines that the cause of the performance bottleneck is the large number of partitions that are in the S3 bucket. The data engineer must resolve the performance bottleneck and reduce Athena query planning time. Which solutions will meet these requirements? (Select TWO.)

A. Create an AWS Glue partition index. Enable partition filtering.
B. Bucket the data based on a column that the data have in common in a WHERE clause of the user query.
C. Use Athena partition projection based on the S3 bucket prefix.
D. Transform the data that is in the S3 bucket to Apache Parquet format.
E. Use the Amazon EMR S3DistCP utility to combine smaller objects in the S3 bucket into larger objects.

Correct Answer: AC

QUESTION 55
A data engineer needs to optimize the performance of a data pipeline that handles retail orders. Data about the orders is ingested daily into an Amazon S3 bucket. The data engineer runs queries once each week to extract metrics from the orders data based the order date for multiple date ranges. The data engineer needs an optimization solution that ensures the query performance will not degrade when the volume of data increases. Which solution will meet this requirement MOST cost-effectively?

A. Partition the data based on order date. Use Amazon Athena to query the data.
B. Partition the data based on order date. Use Amazon Redshift to query the data.
C. Partition the data based on load date. Use Amazon EMR to query the data.
D. Partition the data based on load date. Use Amazon Aurora to query the data.

Correct Answer: A

QUESTION 56
A company uploads .csv files to an Amazon S3 bucket. The company’s data platform team has set up an AWS Glue crawler to perform data discovery and to create the tables and schemas. An AWS Glue job writes processed data from the tables to an Amazon Redshift database. The AWS Glue job handles column mapping and creates the Amazon Redshift tables in the Redshift database appropriately. If the company reruns the AWS Glue job for any reason, duplicate records are introduced into the Amazon Redshift tables. The company needs a solution that will update the Redshift tables without duplicates. Which solution will meet these requirements?

A. Modify the AWS Glue job to copy the rows into a staging Redshift table. Add SQL commands to update the existing rows with new values from the staging Redshift table.
B. Modify the AWS Glue job to load the previously inserted data into a MySQL database. Perform an upset operation in the MySQL database. Copy the results to the Amazon Redshift tables.
C. Use Apache Spark’s DataFrame dropDuplicates() API to eliminate duplicates. Write the data to the Redshift tables.
D. Use the AWS Glue ResolveChoice built-in transform to select the value of the column from the most recent record.

Correct Answer: A

QUESTION 57
Files from multiple data sources arrive in an Amazon S3 bucket on a regular basis. A data engineer wants to ingest new files into Amazon Redshift in near real time when the new files arrive in the S3 bucket. Which solution will meet these requirements?

A. Use the query editor v2 to schedule a COPY command to load new files into Amazon Redshift.
B. Use the zero-ETL integration between Amazon Aurora and Amazon Redshift to load new files into Amazon Redshift.
C. Use AWS Glue job bookmarks to extract, transform, and load (ETL) load new files into Amazon Redshift.
D. Use S3 Event Notifications to invoke an AWS Lambda function that loads new files into Amazon Redshift.

Correct Answer: D

QUESTION 58
A retail company uses an Amazon Redshift data warehouse and an Amazon S3 bucket. The company ingests retail order data into the S3 bucket every day. The company stores all order data at a single path within the S3 bucket. The data has more than 100 columns. The company ingests the order data from a third-party application that generates more than 30 files in CSV format every day. Each CSV file is between 50 and 70 MB in size. The company uses Amazon Redshift Spectrum to run queries that select sets of columns. Users aggregate metrics based on daily orders. Recently, users have reported that the performance of the queries has degraded. A data engineer must resolve the performance issues for the queries. Which combination of steps will meet this requirement with LEAST developmental effort? (Select TWO.)

A. Configure the third-party application to create the files in a columnar format.
B. Develop an AWS Glue ETL job to convert the multiple daily CSV files to one file for each day.
C. Partition the order data in the S3 bucket based on order date.
D. Configure the third-party application to create the files in JSON format.
E. Load the JSON data into the Amazon Redshift table in a SUPER type column.

Correct Answer: AC

QUESTION 59
A company implements a data mesh that has a central governance account. The company needs to catalog all data in the governance account. The governance account uses AWS Lake Formation to centrally share data and grant access permissions. The company has created a new data product that includes a group of Amazon Redshift Serverless tables. A data engineer needs to share the data product with a marketing team. The marketing team must have access to only a subset of columns. The data engineer needs to share the same data product with a compliance team. The compliance team must have access to a different subset of columns than the marketing team needs access to. Which combination of steps should the data engineer take to meet these requirements? (Select TWO.)

A. Create views of the tables that need to be shared. Include only the required columns.
B. Create an Amazon Redshift data share that includes the tables that need to be shared.
C. Create an Amazon Redshift managed VPC endpoint in the marketing team’s account. Grant the marketing team access to the views.
D. Share the Amazon Redshift data share to the Lake Formation catalog in the governance account.
E. Share the Amazon Redshift data share to the Amazon Redshift Serverless workgroup in the marketing team’s account.

Correct Answer: AD

QUESTION 60
An airline company is collecting metrics about flight activities for analytics. The company is conducting a proof of concept (POC) test to show how analytics can provide insights that the company can use to increase on-time departures. The POC test uses objects in Amazon S3 that contain the metrics in cs format. The POC test uses Amazon Athena to query the data. The data is partitioned in the S3 bucket by date. As the amount of data increases, the company wants to optimize the storage solution to improve query performance. Which combination of solutions will meet these requirements? (Select TWO.)

A. Add a randomized string to the beginning of the keys in Amazon S3 to get more throughput across partitions.
B. Use an S3 bucket that is in the same account that uses Athena to query the data.
C. Use an S3 bucket that is in the same AWS Region where the company runs Athena queries.
D. Preprocess the csv data to JSON format by fetching only the document keys that the query requires.
E. Preprocess the .csv data to Apache Parquet format by fetching only the data blocks that are needed for predicates.

Correct Answer: CE