Latest Snowflake DEA-C01 Actual Free Exam Questions & Community Discussion, Page 5

Question #45

A data engineer needs to create an Amazon Athena table based on a subset of data from an existing Athena table named cities_world. The cities_world table contains cities that are located around the world. The data engineer must create a new table named cities_us to contain only the cities from cities_world that are located in the US.
Which SQL statement should the data engineer use to meet this requirement?

A. INSERT INTO cities_usa (city,state) SELECT city, state FROM cities_world WHERE country='usa';

B. INSERT INTO cities_usa SELECT city, state FROM cities_world WHERE country='usa';

C. UPDATE cities_usa SET (city, state) = (SELECT city, state FROM cities_world WHERE country='usa');

D. MOVE city, state FROM cities_world TO cities_usa WHERE country='usa';

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Correct Answer: A Vote an answer

Question #46

A company has multiple applications that use datasets that are stored in an Amazon S3 bucket.
The company has an ecommerce application that generates a dataset that contains personally identifiable information (PII). The company has an internal analytics application that does not require access to the PII.
To comply with regulations, the company must not share PII unnecessarily. A data engineer needs to implement a solution that with redact PII dynamically, based on the needs of each application that accesses the dataset.
Which solution will meet the requirements with the LEAST operational overhead?

A. Create an S3 Object Lambda endpoint. Use the S3 Object Lambda endpoint to read data from the S3 bucket. Implement redaction logic within an S3 Object Lambda function to dynamically redact PII based on the needs of each application that accesses the data.

B. Create an API Gateway endpoint that has custom authorizers. Use the API Gateway endpoint to read data from the S3 bucket. Initiate a REST API call to dynamically redact PII based on the needs of each application that accesses the data.

C. Use AWS Glue to transform the data for each application. Create multiple copies of the dataset.
Give each dataset copy the appropriate level of redaction for the needs of the application that accesses the copy.

D. Create an S3 bucket policy to limit the access each application has. Create multiple copies of the dataset. Give each dataset copy the appropriate level of redaction for the needs of the application that accesses the copy.

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Correct Answer: A Vote an answer

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Question #47

A finance company receives data from third-party data providers and stores the data as objects in an Amazon S3 bucket.
The company ran an AWS Glue crawler on the objects to create a data catalog. The AWS Glue crawler created multiple tables. However, the company expected that the crawler would create only one table.
The company needs a solution that will ensure the AVS Glue crawler creates only one table.
Which combination of solutions will meet this requirement? (Choose two.)

A. Ensure that the object format and schema are the same for each object. Do not enforce consistency for the compression type of each object.

B. Ensure that the schema is the same for each object. Do not enforce consistency for the file format and compression type of each object.

C. Ensure that the structure of the prefix for each S3 object name is consistent.

D. Ensure that the object format, compression type, and schema are the same for each object.

E. Ensure that all S3 object names follow a similar pattern.

Discussion 0

Correct Answer: C,D Vote an answer

Question #48

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 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.

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 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.

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Correct Answer: B Vote an answer

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Question #49

A data engineer is using Amazon QuickSight to build a dashboard to report a company's revenue in multiple AWS Regions. The data engineer wants the dashboard to display the total revenue for a Region, regardless of the drill-down levels shown in the visual.
Which solution will meet these requirements?

A. Create a level-aware calculation - window (LAC-W) function.

B. Create a simple calculated field.

C. Create a level-aware calculation - aggregate (LAC-A) function.

D. Create a table calculation.

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Correct Answer: C Vote an answer

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Question #50

A company uses Amazon DataZone as a data governance and business catalog solution. The company stores data in an Amazon S3 data lake. The company uses AWS Glue with an AWS Glue Data Catalog.
A data engineer needs to publish AWS Glue Data Quality scores to the Amazon DataZone portal.
Which solution will meet this requirement?

A. Configure AWS Glue ETL jobs to use an Evaluate Data Quality transform. Define a data quality ruleset inside the jobs. Configure the Amazon DataZone project to have an AWS Glue data source. Enable the data quality configuration for the data source.

B. Create a data quality ruleset with Data Quality Definition language (DQDL) rules that apply to a specific AWS Glue table. Schedule the ruleset to run daily. Configure the Amazon DataZone project to have an AWS Glue data source. Enable the data quality configuration for the data source.

C. Create a data quality ruleset with Data Quality Definition language (DQDL) rules that apply to a specific AWS Glue table. Schedule the ruleset to run daily. Configure the Amazon DataZone project to have an Amazon Redshift data source. Enable the data quality configuration for the data source.

D. Configure AWS Glue ETL jobs to use an Evaluate Data Quality transform. Define a data quality ruleset inside the jobs. Configure the Amazon DataZone project to have an Amazon Redshift data source. Enable the data quality configuration for the data source.

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Correct Answer: B Vote an answer

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Question #51

A media company wants to improve a system that recommends media content to customers 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?

A. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from Amazon Elastic Container Registry (Amazon ECR).

B. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from a Git repository.

C. Use API calls to access and integrate third-party datasets from AWS Data Exchange.

D. Use API calls to access and integrate third-party datasets from AWS DataSync.

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Correct Answer: C Vote an answer

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Question #52

A company needs to implement real-time analytics for a retail shopping platform. The company wants to capture clickstream data, process the data, and load the data into Amazon Redshift for analysis. The solution must handle hundreds of megabytes of data every second. Which solution will meet these requirements with the LEAST query latency for analytics?

A. Use Amazon DynamoDB Streams to capture the data. Use AWS Glue to process the data. Use a zero-ETL integration to load the data into Amazon Redshift.

B. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to capture the data. Use Amazon EMR to process the data. Use federated queries to access data in Amazon Redshift.

C. Use Amazon Data Firehose to capture the data. Store the data in an Amazon S3 bucket. Use the COPY command to load data into Amazon Redshift.

D. Use Amazon Kinesis Data Streams to capture the data. Use Amazon Redshift streaming ingestion to load data directly into materialized views.

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Correct Answer: D Vote an answer

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Question #53

A company uses Amazon EMR as an extract, transform, and load (ETL) pipeline to transform data that comes from multiple sources. A data engineer must orchestrate the pipeline to maximize performance.
Which AWS service will meet this requirement MOST cost effectively?

A. AWS Glue Workflows

B. Amazon Managed Workflows for Apache Airflow (Amazon MWAA)

C. Amazon EventBridge

D. AWS Step Functions

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Correct Answer: D Vote an answer

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Question #54

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?

A. Store a pointer to the custom Python scripts in the execution context object in a shared Amazon S3 bucket.

B. Store a pointer to the custom Python scripts in environment variables in a shared Amazon S3 bucket.

C. Assign the same alias to each Lambda function. Call reach Lambda function by specifying the function's alias.

D. Package the custom Python scripts into Lambda layers. Apply the Lambda layers to the Lambda functions.

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Correct Answer: D Vote an answer

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Question #55

A company uses AWS Glue jobs to implement several data pipelines. The pipelines are critical to the company.
The company needs to implement a monitoring mechanism that will alert stakeholders if the pipelines fail.
Which solution will meet these requirements with the LEAST operational overhead?

A. Create an Amazon EventBridge rule to match AWS Glue job failure events. Configure the rule to target an AWS Lambda function to process events. Configure the function to send notifications to an Amazon Simple Notification Service (Amazon SNS) topic.

B. Configure an Amazon CloudWatch Logs log group for the AWS Glue jobs. Create an Amazon EventBridge rule to match new log creation events in the log group. Configure the rule to send notifications to an Amazon Simple Notification Service (Amazon SNS) topic.

C. Configure an Amazon CloudWatch Logs log group for the AWS Glue jobs. Create an Amazon EventBridge rule to match new log creation events in the log group. Configure the rule to target an AWS Lambda function that reads the logs and sends notifications to an Amazon Simple Notification Service (Amazon SNS) topic if AWS Glue job failure logs are present.

D. Create an Amazon EventBridge rule to match AWS Glue job failure events. Define an Amazon CloudWatch metric based on the EventBridge rule. Set up a CloudWatch alarm based on the metric to send notifications to an Amazon Simple Notification Service (Amazon SNS) topic.

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Correct Answer: D Vote an answer

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