Latest Snowflake DEA-C01 Actual Free Exam Questions & Community Discussion, Page 6

Question #56

A data engineer is using Amazon Athena to analyze sales data that is in Amazon S3. The data engineer writes a query to retrieve sales amounts for 2023 for several products from a table named sales_data. However, the query does not return results for all of the products that are in the sales_data table. The data engineer needs to troubleshoot the query to resolve the issue.
The data engineer's original query is as follows:
SELECT product_name, sum(sales_amount)
FROM sales_data
WHERE year = 2023
GROUP BY product_name
How should the data engineer modify the Athena query to meet these requirements?

A. Add HAVING sum(sales_amount) > 0 after the GROUP BY clause.

B. Change WHERE year = 2023 to WHERE extract(year FROM sales_data) = 2023.

C. Remove the GROUP BY clause.

D. Replace sum(sales_amount) with count(*) for the aggregation.

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Correct Answer: A Vote an answer

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Question #57

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. Use Amazon DynamoDB Streams to capture table changes. Use an AWS Lambda function to process and update the data in Amazon OpenSearch Service.

C. 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.

D. Use a custom OpenSearch plugin to sync data from the Amazon DynamoDB tables.

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Correct Answer: B Vote an answer

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Question #58

A retail company stores order information in an Amazon Aurora table named Orders. The company needs to create operational reports from the Orders table with minimal latency. The Orders table contains billions of rows, and over 100,000 transactions can occur each second.
A marketing team needs to join the Orders data with an Amazon Redshift table named Campaigns in the marketing team's data warehouse. The operational Aurora database must not be affected.
Which solution will meet these requirements with the LEAST operational effort?

A. Use AWS Database Migration Service (AWS DMS) Serverless to replicate the Orders table to Amazon Redshift. Create a materialized view in Amazon Redshift to join with the Campaigns table.

B. Use AWS Glue to replicate the Orders table to Amazon Redshift. Create a materialized view in Amazon Redshift to join with the Campaigns table.

C. Use the Aurora zero-ETL integration with Amazon Redshift to replicate the Orders table. Create a materialized view in Amazon Redshift to join with the Campaigns table.

D. Use federated queries to query the Orders table directly from Aurora. Create a materialized view in Amazon Redshift to join with the Campaigns table.

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Correct Answer: C Vote an answer

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Question #59

A company stores a large dataset in an Amazon S3 bucket. A data engineer frequently runs complex queries on the dataset by using Amazon Athena. The data engineer needs to optimize query performance and optimize costs for queries that are run multiple times with the same parameters. Which solution will meet these requirements?

A. Use Amazon Redshift Spectrum to query the data in Amazon S3.

B. Convert the dataset to JSON format before running Athena queries.

C. Configure query result reuse settings in the Athena workgroup.

D. Use Amazon EMR to pre-process the data before running Athena queries.

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Correct Answer: C Vote an answer

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Question #60

A company uses an Amazon S3 bucket to integrate multiple data sources into a central data lake.
The company needs to perform multiple transformations and data cleaning processes on the data to make the data accessible to business partners.
The company needs a solution that will give multiple business partners the ability to run SQL queries on the central data lake during normal business hours.
Which solution will meet these requirements MOST cost-effectively?

A. Use an AWS Glue Flex Job after normal business hours to process the previous day's data, apply all necessary transformations. and load the prepared data into Amazon Redshift Serverless.

B. Use an AWS Glue Flex job after normal business hours to process the previous day's data, apply all necessary transformations, and load the prepared data into an Amazon Redshift provisioned cluster.

C. Use an AWS Lambda function after normal business hours to process the previous day's data, apply all necessary transformations, and load the prepared data into an Amazon Redshift provisioned cluster.

D. Use a provisioned Amazon EMR cluster after normal business hours to process the previous day's data, apply all necessary transformations, and load the prepared data into Amazon Redshift Serverless.

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Correct Answer: A Vote an answer

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Question #61

A company uses AWS Key Management Service (AWS KMS) to encrypt an Amazon Redshift cluster. The company wants to configure a cross-Region snapshot of the Redshift cluster as part of disaster recovery (DR) strategy.
A data engineer needs to use the AWS CLI to create the cross-Region snapshot.
Which combination of steps will meet these requirements? (Choose two.)

A. Create a KMS key and configure a snapshot copy grant in the destination AWS Region.

B. In the source AWS Region, enable snapshot copying. Specify the name of the snapshot copy grant that is created in the source AWS Region.

C. Create a KMS key and configure a snapshot copy grant in the source AWS Region.

D. In the source AWS Region, enable snapshot copying. Specify the name of the snapshot copy grant that is created in the destination AWS Region.

E. Convert the cluster to a Multi-AZ deployment.

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Correct Answer: A,D Vote an answer

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Question #62

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.)

A. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate the Athena queries in AWS Batch.

B. 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.

C. Use an AWS Lambda function and the Athena Boto3 client start_query_execution API call to invoke the Athena queries programmatically.

D. 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.

E. Use an AWS Glue Python shell job and the Athena Boto3 client start_query_execution API call to invoke the Athena queries programmatically.

Discussion 0

Correct Answer: C,D Vote an answer

Question #63

A company has a data pipeline that uses an Amazon RDS instance, AWS Glue jobs, and an Amazon S3 bucket. The RDS instance and AWS Glue jobs run in a private subnet of a VPC and in the same security group.
A user made a change to the security group that prevents the AWS Glue jobs from connecting to the RDS instance. After the change, the security group contains a single rule that allows inbound SSH traffic from a specific IP address.
The company must resolve the connectivity issue.
Which solution will meet this requirement?

A. Add an inbound rule that allows all TCP traffic on all TCP ports. Set the DNS name of the RDS instance as the source.

B. Add an inbound rule that allows all TCP traffic on all TCP ports. Set the security group as the source.

C. Replace the source of the existing SSH rule with the private IP address of the RDS instance.Create an outbound rule with the same source, destination, and protocol as the inbound SSH rule.

D. Add an inbound rule that allows all TCP traffic on all UDP ports. Set the private IP address of the RDS instance as the source.

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Correct Answer: B Vote an answer

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Question #64

A retail company stores data from a product lifecycle management (PLM) application in an on- premises MySQL database. The PLM application frequently updates the database when transactions occur.
The company wants to gather insights from the PLM application in near real time. The company wants to integrate the insights with other business datasets and to analyze the combined dataset by using an Amazon Redshift data warehouse.
The company has already established an AWS Direct Connect connection between the on- premises infrastructure and AWS.
Which solution will meet these requirements with the LEAST development effort?

A. Run a scheduled AWS Glue extract, transform, and load (ETL) job to get the MySQL database updates by using a Java Database Connectivity (JDBC) connection. Set Amazon Redshift as the destination for the ETL job.

B. Run scheduled AWS DataSync tasks to synchronize data from the MySQL database. Set Amazon Redshift as the destination for the tasks.

C. Run a full load plus CDC task in AWS Database Migration Service (AWS DMS) to continuously replicate the MySQL database changes. Set Amazon Redshift as the destination for the task.

D. Use the Amazon AppFlow SDK to build a custom connector for the MySQL database to continuously replicate the database changes. Set Amazon Redshift as the destination for the connector.

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Correct Answer: C Vote an answer

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Question #65

A data engineer must implement a data cataloging solution to track schema changes in an Amazon Redshift table.
Which solution will meet these requirements?

A. Schedule an AWS Glue crawler to run every day on the table. Configure the crawler to update an Apache Hive metastore.

B. Schedule an AWS Glue crawler to run every day on the table by using the Java Database Connectivity (JDBC) driver. Configure the crawler to update an AWS Glue Data Catalog.

C. Use the AWS Schema Conversion Tool (AWS SCT) to log the table metadata to an Apache Hive metastore. Use Amazon EventBridge Scheduler to update the metastore every day.

D. Use AWS DataSync to log the table metadata to an AWS Glue Data Catalog. Use an AWS Glue crawler to update the Data Catalog every day.

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Correct Answer: B Vote an answer

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Question #66

A company stores server logs in an Amazon S3 bucket. The company needs to keep the logs for
1 year. The logs are not required after 1 year.
A data engineer needs a solution to automatically delete logs that are older than 1 year.
Which solution will meet these requirements with the LEAST operational overhead?

A. Schedule a cron job on an Amazon EC2 instance to delete the logs after 1 year.

B. Define an S3 Lifecycle configuration to delete the logs after 1 year.

C. Configure an AWS Step Functions state machine to delete the logs after 1 year.

D. Create an AWS Lambda function to delete the logs after 1 year.

Discussion 0

Correct Answer: B Vote an answer

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