DEA-C01 by Snowflake Valid Free Exam Practice Test

Question 1

A manufacturing company has many IoT devices in facilities around the world. The company uses Amazon Kinesis Data Streams to collect data from the devices. The data includes device ID, capture date, measurement type, measurement value, and facility ID. The company uses facility ID as the partition key.
The company's operations team recently observed many WriteThroughputExceeded exceptions.
The operations team found that some shards were heavily used but other shards were generally idle.
How should the company resolve the issues that the operations team observed?

A. Change the partition key from facility ID to capture date. B. Change the partition key from facility ID to a randomly generated key. C. Increase the number of shards. D. Archive the data on the producer's side.

Correct Answer: B

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Question 2

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 Amazon Redshift 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 AWS Glue data source. Enable the data quality configuration for the data source.

Correct Answer: B

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Question 3

A company is designing a serverless data processing workflow in AWS Step Functions that involves multiple steps. The processing workflow ingests data from an external API, transforms the data by using multiple AWS Lambda functions, and loads the transformed data into Amazon DynamoDB.
The company needs the workflow to perform specific steps based on the content of the incoming data.
Which Step Functions state type should the company use to meet this requirement?

A. Choice B. Task C. Parallel D. Map

Correct Answer: A

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Question 4

A finance company uses Amazon Redshift as a data warehouse. The company stores the data in a shared Amazon S3 bucket. The company uses Amazon Redshift Spectrum to access the data that is stored in the S3 bucket. The data comes from certified third-party data providers. Each third-party data provider has unique connection details.
To comply with regulations, the company must ensure that none of the data is accessible from outside the company's AWS environment.
Which combination of steps should the company take to meet these requirements? (Choose two.)

A. Define table constraints for the primary keys and the foreign keys. B. Replace the existing Redshift cluster with a new Redshift cluster that is in a private subnet. Use an interface VPC endpoint to connect to the Redshift cluster. Use a NAT gateway to give Redshift access to the S3 bucket. C. Turn on enhanced VPC routing for the Amazon Redshift cluster. Set up an AWS Direct Connect connection and configure a connection between each data provider and the finance company's VPC. D. Use federated queries to access the data from each data provider. Do not upload the data to the S3 bucket. Perform the federated queries through a gateway VPC endpoint. E. Create an AWS CloudHSM hardware security module (HSM) for each data provider. Encrypt each data provider's data by using the corresponding HSM for each data provider.

Correct Answer: B,C

Question 5

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. Package the custom Python scripts into Lambda layers. Apply the Lambda layers to the Lambda functions. B. Store a pointer to the custom Python scripts in the execution context object 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. Store a pointer to the custom Python scripts in environment variables in a shared Amazon S3 bucket.

Correct Answer: A

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Question 6

A company has a production AWS account that runs company workloads. The company's security team created a security AWS account to store and analyze security logs from the production AWS account. The security logs in the production AWS account are stored in Amazon CloudWatch Logs.
The company needs to use Amazon Kinesis Data Streams to deliver the security logs to the security AWS account.
Which solution will meet these requirements?

A. Create a destination data stream in the production AWS account. In the production AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the security AWS account. B. Create a destination data stream in the production AWS account. In the security AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the production AWS account. C. Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the production AWS account. D. Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the security AWS account.

Correct Answer: C

Question 7

A data engineer is building an automated extract, transform, and load (ETL) ingestion pipeline by using AWS Glue. The pipeline ingests compressed files that are in an Amazon S3 bucket. The ingestion pipeline must support incremental data processing.
Which AWS Glue feature should the data engineer use to meet this requirement?

A. Triggers B. Workflows C. Job bookmarks D. Classifiers

Correct Answer: C

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Question 8

A company adds new data to a large CSV file in an Amazon S3 bucket every day. The file contains company sales data from the previous 5 years. The file currently includes more than
5,000 rows. The CSV file structure is shown below with sample data:

The company needs to use Amazon Athena to run queries on the CSV file to fetch data from a specific time period.
Which solution will meet this requirement MOST cost-effectively?

A. Write an Apache Spark script to convert the CSV data to JSON format. Create an AWS Glue job to run the script every day. Catalog the JSON data in AWS Glue. Run the Athena queries on the JSON data. B. Use prefixes to partition the data in the S3 bucket. Use the SALE_DATE column to create a partition for each day. Catalog the data in AWS Glue and ensure that the partitions are added.
Update the Athena queries to use the new partitions. C. Create an Amazon RDS database. Create a table named SALES that matches the schema of the CSV file. Create an index on the SALE_DATE column. Create an AWS Lambda function to load the CSV data into the RDS database. Use S3 Event Notifications to invoke the Lambda function. D. Launch an Amazon EMR cluster. Specify AWS Glue Data Catalog as the default Apache Hive metastore. Use Presto in Trino to run queries on the data.

Correct Answer: B

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Question 9

A data engineer notices that Amazon Athena queries are held in a queue before the queries run.
How can the data engineer prevent the queries from queueing?

A. Use federated queries. B. Configure provisioned capacity for an existing workgroup. C. Increase the query result limit. D. Allow users who run the Athena queries to an existing workgroup.

Correct Answer: B

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Question 10

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. Implement S3 Lifecycle management to expire the files. B. 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. C. Store the files in S3 Intelligent-Tiering for 90 days. Enable versioning. Add S3 Lifecycle management to expire the files. D. Store the files in S3 Standard for 90 days. Enable versioning. Enable Object Lock on the files for
90 days. Then expire the files.

Correct Answer: A

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Question 11

A company stores raw clickstream data in an Amazon S3 bucket. The company needs a solution to process the data every day by using complex PySpark transformations that rely on custom internal libraries. After the data is transformed, the company must store the data in Amazon Redshift for analytics. The solution must be highly scalable to handle large data workloads. Which solution will meet these requirements with the LEAST operational overhead?

A. Use Amazon EC2 Auto Scaling groups with a custom AMI that contains the custom libraries to run a PySpark application. B. Use Amazon SageMaker Processing jobs to run PySpark code that uses native SageMaker libraries. C. Use Amazon EMR to run PySpark jobs. Use bootstrap actions to install the custom libraries D. Use AWS Glue Studio to build and schedule PySpark jobs. Configure an AWS Glue data connection that includes the custom libraries.

Correct Answer: D

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Snowflake SnowPro Advanced: Data Engineer Certification - DEA-C01 Exam Practice Test