Free DAS-C01 Exam Braindumps

An insurance company has raw data in JSON format that is sent without a predefined schedule through an Amazon Kinesis Data Firehose delivery stream to an Amazon S3 bucket. An AWS Glue crawler is scheduled to run every 8 hours to update the schema in the data catalog of the tables stored in the S3 bucket. Data analysts analyze the data using Apache Spark SQL on Amazon EMR set up with AWS Glue Data Catalog as the metastore. Data analysts say that, occasionally, the data they receive is stale. A data engineer needs to provide access to the most up-to-date data.
Which solution meets these requirements?

1. A. Create an external schema based on the AWS Glue Data Catalog on the existing Amazon Redshift cluster to query new data in Amazon S3 with Amazon Redshift Spectrum.
2. B. Use Amazon CloudWatch Events with the rate (1 hour) expression to execute the AWS Glue crawler every hour.
3. C. Using the AWS CLI, modify the execution schedule of the AWS Glue crawler from 8 hours to 1 minute.
4. D. Run the AWS Glue crawler from an AWS Lambda function triggered by an S3:ObjectCreated:* eventnotification on the S3 bucket.

Correct Answer: D
https://docs.aws.amazon.com/AmazonS3/latest/dev/NotificationHowTo.html "you can use a wildcard (for example, s3:ObjectCreated:*) to request notification when an object is created regardless of the API used" "AWS Lambda can run custom code in response to Amazon S3 bucket events. You upload your custom code to AWS Lambda and create what is called a Lambda function. When Amazon S3 detects an event of a specific type (for example, an object created event), it can publish the event to AWS Lambda and invoke your function in Lambda. In response, AWS Lambda runs your function."

A transportation company uses IoT sensors attached to trucks to collect vehicle data for its global delivery fleet. The company currently sends the sensor data in small .csv files to Amazon S3. The files are then loaded into a 10-node Amazon Redshift cluster with two slices per node and queried using both Amazon Athena and Amazon Redshift. The company wants to optimize the files to reduce the cost of querying and also improve the speed of data loading into the Amazon Redshift cluster.
Which solution meets these requirements?

1. A. Use AWS Glue to convert all the files from .csv to a single large Apache Parquet fil
2. B. COPY the file into Amazon Redshift and query the file with Athena from Amazon S3.
3. C. Use Amazon EMR to convert each .csv file to Apache Avr
4. D. COPY the files into Amazon Redshift and query the file with Athena from Amazon S3.
5. E. Use AWS Glue to convert the files from .csv to a single large Apache ORC fil
6. F. COPY the file into Amazon Redshift and query the file with Athena from Amazon S3.
7. G. Use AWS Glue to convert the files from .csv to Apache Parquet to create 20 Parquet file
8. H. COPY the files into Amazon Redshift and query the files with Athena from Amazon S3.

Correct Answer: D

A company’s data analyst needs to ensure that queries executed in Amazon Athena cannot scan more than a prescribed amount of data for cost control purposes. Queries that exceed the prescribed threshold must be canceled immediately.
What should the data analyst do to achieve this?

1. A. Configure Athena to invoke an AWS Lambda function that terminates queries when the prescribed threshold is crossed.
2. B. For each workgroup, set the control limit for each query to the prescribed threshold.
3. C. Enforce the prescribed threshold on all Amazon S3 bucket policies
4. D. For each workgroup, set the workgroup-wide data usage control limit to the prescribed threshold.

Correct Answer: B
https://docs.aws.amazon.com/athena/latest/ug/manage-queries-control-costs-with-workgroups.html

A company is migrating its existing on-premises ETL jobs to Amazon EMR. The code consists of a series of jobs written in Java. The company needs to reduce overhead for the system administrators without changing the underlying code. Due to the sensitivity of the data, compliance requires that the company use root device volume encryption on all nodes in the cluster. Corporate standards require that environments be provisioned though AWS CloudFormation when possible.
Which solution satisfies these requirements?

1. A. Install open-source Hadoop on Amazon EC2 instances with encrypted root device volume
2. B. Configure the cluster in the CloudFormation template.
3. C. Use a CloudFormation template to launch an EMR cluste
4. D. In the configuration section of the cluster, define a bootstrap action to enable TLS.
5. E. Create a custom AMI with encrypted root device volume
6. F. Configure Amazon EMR to use the custom AMI using the CustomAmild property in the CloudFormation template.
7. G. Use a CloudFormation template to launch an EMR cluste
8. H. In the configuration section of the cluster, define a bootstrap action to encrypt the root device volume of every node.

Correct Answer: C

A company leverages Amazon Athena for ad-hoc queries against data stored in Amazon S3. The company wants to implement additional controls to separate query execution and query history among users, teams, or applications running in the same AWS account to comply with internal security policies.
Which solution meets these requirements?

1. A. Create an S3 bucket for each given use case, create an S3 bucket policy that grants permissions to appropriate individual IAM user
2. B. and apply the S3 bucket policy to the S3 bucket.
3. C. Create an Athena workgroup for each given use case, apply tags to the workgroup, and create an IAM policy using the tags to apply appropriate permissions to the workgroup.
4. D. Create an IAM role for each given use case, assign appropriate permissions to the role for the given usecase, and add the role to associate the role with Athena.
5. E. Create an AWS Glue Data Catalog resource policy for each given use case that grants permissions to appropriate individual IAM users, and apply the resource policy to the specific tables used by Athena.

Correct Answer: B
https://docs.aws.amazon.com/athena/latest/ug/user-created-workgroups.html
Amazon Athena Workgroups - A new resource type that can be used to separate query execution and query history between Users, Teams, or Applications running under the same AWS account https://aws.amazon.com/about-aws/whats-new/2019/02/athena_workgroups/