Free Snowflake DEA-C01 Exam Dumps Questions & Answers

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 security AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the production AWS account.
• B.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.
• C.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.
• 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.

A company wants to use Apache Spark jobs that run on an Amazon EMR cluster to process streaming data. The Spark jobs will transform and store the data in an Amazon S3 bucket. The company will use Amazon Athena to perform analysis.
The company needs to optimize the data format for analytical queries.
Which solutions will meet these requirements with the SHORTEST query times? (Choose two.)

• A.Use ORC format. Use AWS Glue Data Catalog to track schema changes.
• B.Use Avro format. Use AWS Glue Data Catalog to track schema changes.
• C.Use ORC format. Store schema definitions in separate files in Amazon S3.
• D.Use Apache Parquet format. Use an external Amazon DynamoDB table to track schema changes.
• E.Use Apache Parquet format. Use AWS Glue Data Catalog to track schema changes.

A company has AWS resources in multiple AWS Regions. The company has an Amazon EFS file system in each Region where the company operates. The company's data science team operates within only a single Region. The data that the data science team works with must remain within the team's Region.
A data engineer needs to create a single dataset by processing files that are in each of the company's Regional EFS file systems. The data engineer wants to use an AWS Step Functions state machine to orchestrate AWS Lambda functions to process the data.
Which solution will meet these requirements with the LEAST effort?

• A.Configure each of the Regional EFS file systems to replicate data to the data science team's Region. In the data science team's Region, configure the Lambda functions to mount the replica file systems. Use the Lambda functions to process the data.
• B.Peer the VPCs that host the EFS file systems in each Region with the VPC that is in the data science team's Region. Enable EFS file locking.
  Configure the Lambda functions in the data science team's Region to mount each of the Region specific file systems. Use the Lambda functions to process the data.
• C.Use AWS DataSync to transfer files from each of the Regional EFS files systems to the file system that is in the data science team's Region.Configure the Lambda functions in the data science team's Region to mount the file system that is in the same Region. Use the Lambda functions to process the data.
• D.Deploy the Lambda functions to each Region. Mount the Regional EFS file systems to the Lambda functions. Use the Lambda functions to process the data. Store the output in an Amazon S3 bucket in the data science team's Region.

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?

• A.Compress the .csv files by using Snappy compression.
• B.Change the data format from .csv to JSON format. Apply Snappy compression.
• C.Compress the .csv files by using gzip compression.
• D.Change the data format from .csv to Apache Parquet. Apply Snappy compression.

A data engineer needs to debug an AWS Glue job that reads from Amazon S3 and writes to Amazon Redshift. The data engineer enabled the bookmark feature for the AWS Glue job.
The data engineer has set the maximum concurrency for the AWS Glue job to 1.
The AWS Glue job is successfully writing the output to Amazon Redshift. However, the Amazon S3 files that were loaded during previous runs of the AWS Glue job are being reprocessed by subsequent runs.
What is the likely reason the AWS Glue job is reprocessing the files?

• A.The AWS Glue job does not have the s3:GetObjectAcl permission that is required for bookmarks to work correctly.
• B.The maximum concurrency for the AWS Glue job is set to 1.
• C.The AWS Glue job does not have a required commit statement.
• D.The data engineer incorrectly specified an older version of AWS Glue for the Glue job.