Amazon DAS-C01 Exam Questions & Answers

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?

A. Use AWS Glue to convert all the files from .csv to a single large Apache Parquet file. COPY the file into Amazon Redshift and query the file with Athena from Amazon S3.

B. Use Amazon EMR to convert each .csv file to Apache Avro. COPY the files into Amazon Redshift and query the file with Athena from Amazon S3.

C. Use AWS Glue to convert the files from .csv to a single large Apache ORC file. COPY the file into Amazon Redshift and query the file with Athena from Amazon S3.

D. Use AWS Glue to convert the files from .csv to Apache Parquet to create 20 Parquet files. COPY the files into Amazon Redshift and query the files with Athena from Amazon S3.

A utility company wants to visualize data for energy usage on a daily basis in Amazon QuickSight A data analytics specialist at the company has built a data pipeline to collect and ingest the data into Amazon S3 Each day the data is stored in an individual csv file in an S3 bucket This is an example of the naming structure 20210707_datacsv 20210708_datacsv.

To allow for data querying in QuickSight through Amazon Athena the specialist used an AWS Glue crawler to create a table with the path "s3 //powertransformer/20210707_data csv" However when the data is queried, it returns zero rows.

How can this issue be resolved?

A. Modify the IAM policy for the AWS Glue crawler to access Amazon S3.

B. Ingest the files again.

C. Store the files in Apache Parquet format.

D. Update the table path to "s3://powertransformer/".

A company uses Amazon EC2 instances to receive files from external vendors throughout each day. At the end of each day, the EC2 instances combine the files into a single file, perform gzip compression, and upload the single file to an

Amazon S3 bucket. The total size of all the files is approximately 100 GB each day.

When the files are uploaded to Amazon S3, an AWS Batch job runs a COPY command to load the files into an Amazon Redshift cluster.

Which solution will MOST accelerate the COPY process?

A. Upload the individual files to Amazon S3. Run the COPY command as soon as the files become available.

B. Split the files so that the number of files is equal to a multiple of the number of slices in the Redshift cluster. Compress and upload the files to Amazon S3. Run the COPY command on the files.

C. Split the files so that each file uses 50% of the free storage on each compute node in the Redshift cluster. Compress and upload the files to Amazon S3. Run the COPY command on the files.

D. Apply sharding by breaking up the files so that the DISTKEY columns with the same values go to the same file. Compress and upload the sharded files to Amazon S3. Run the COPY command on the files.