Free DAS-C01 Exam Braindumps

A company operates toll services for highways across the country and collects data that is used to understand usage patterns. Analysts have requested the ability to run traffic reports in near-real time. The company is interested in building an ingestion pipeline that loads all the data into an Amazon Redshift cluster and alerts operations personnel when toll traffic for a particular toll station does not meet a specified threshold. Station data and the corresponding threshold values are stored in Amazon S3.
Which approach is the MOST efficient way to meet these requirements?

1. A. Use Amazon Kinesis Data Firehose to collect data and deliver it to Amazon Redshift and Amazon Kinesis Data Analytics simultaneousl
2. B. Create a reference data source in Kinesis Data Analytics to temporarily store the threshold values from Amazon S3 and compare the count of vehicles for a particular toll station against its corresponding threshold valu
3. C. Use AWS Lambda to publish an Amazon Simple Notification Service (Amazon SNS) notification if the threshold is not met.
4. D. Use Amazon Kinesis Data Streams to collect all the data from toll station
5. E. Create a stream in Kinesis Data Streams to temporarily store the threshold values from Amazon S3. Send both streams to Amazon Kinesis Data Analytics to compare the count of vehicles for a particular toll station against its corresponding threshold valu
6. F. Use AWS Lambda to publish an Amazon Simple Notification Service (Amazon SNS) notification if the threshold is not me
7. G. Connect Amazon Kinesis Data Firehose to Kinesis Data Streams to deliver the data to Amazon Redshift.
8. H. Use Amazon Kinesis Data Firehose to collect data and deliver it to Amazon Redshif
9. I. Then, automatically trigger an AWS Lambda function that queries the data in Amazon Redshift, compares the count of vehicles for a particular toll station against its corresponding threshold values read from Amazon S3, and publishes an Amazon Simple Notification Service (Amazon SNS) notification if the threshold is not met.
10. J. Use Amazon Kinesis Data Firehose to collect data and deliver it to Amazon Redshift and Amazon Kinesis Data Analytics simultaneousl
11. K. Use Kinesis Data Analytics to compare the count of vehicles against the threshold value for the station stored in a table as an in-application stream based on information stored in Amazon S3. Configure an AWS Lambda function as an output for the application that will publish an Amazon Simple Queue Service (Amazon SQS) notification to alert operations personnel if the threshold is not met.

Correct Answer: D

A data analyst is using AWS Glue to organize, cleanse, validate, and format a 200 GB dataset. The data analyst triggered the job to run with the Standard worker type. After 3 hours, the AWS Glue job status is still RUNNING. Logs from the job run show no error codes. The data analyst wants to improve the job execution time without overprovisioning.
Which actions should the data analyst take?

1. A. Enable job bookmarks in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the executor-cores job parameter.
2. B. Enable job metrics in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the maximum capacity job parameter.
3. C. Enable job metrics in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the spark.yarn.executor.memoryOverhead job parameter.
4. D. Enable job bookmarks in AWS Glue to estimate the number of data processing units (DPUs). Based on the profiled metrics, increase the value of the num-executors job parameter.

Correct Answer: B

A company needs to store objects containing log data in JSON format. The objects are generated by eight applications running in AWS. Six of the applications generate a total of 500 KiB of data per second, and two of the applications can generate up to 2 MiB of data per second.
A data engineer wants to implement a scalable solution to capture and store usage data in an Amazon S3
bucket. The usage data objects need to be reformatted, converted to .csv format, and then compressed before they are stored in Amazon S3. The company requires the solution to include the least custom code possible and has authorized the data engineer to request a service quota increase if needed.
Which solution meets these requirements?

1. A. Configure an Amazon Kinesis Data Firehose delivery stream for each applicatio
2. B. Write AWS Lambda functions to read log data objects from the stream for each applicatio
3. C. Have the function perform reformatting and .csv conversio
4. D. Enable compression on all the delivery streams.
5. E. Configure an Amazon Kinesis data stream with one shard per applicatio
6. F. Write an AWS Lambda function to read usage data objects from the shard
7. G. Have the function perform .csv conversion, reformatting, and compression of the dat
8. H. Have the function store the output in Amazon S3.
9. I. Configure an Amazon Kinesis data stream for each applicatio
10. J. Write an AWS Lambda function to read usage data objects from the stream for each applicatio
11. K. Have the function perform .csv conversion, reformatting, and compression of the dat
12. L. Have the function store the output in Amazon S3.
13. M. Store usage data objects in an Amazon DynamoDB tabl
14. N. Configure a DynamoDB stream to copy the objects to an S3 bucke
15. O. Configure an AWS Lambda function to be triggered when objects are written to the S3 bucke
16. P. Have the function convert the objects into .csv format.

Correct Answer: A

A large retailer has successfully migrated to an Amazon S3 data lake architecture. The company’s marketing team is using Amazon Redshift and Amazon QuickSight to analyze data, and derive and visualize insights. To ensure the marketing team has the most up-to-date actionable information, a data analyst implements nightly refreshes of Amazon Redshift using terabytes of updates from the previous day.
After the first nightly refresh, users report that half of the most popular dashboards that had been running correctly before the refresh are now running much slower. Amazon CloudWatch does not show any alerts.
What is the MOST likely cause for the performance degradation?

1. A. The dashboards are suffering from inefficient SQL queries.
2. B. The cluster is undersized for the queries being run by the dashboards.
3. C. The nightly data refreshes are causing a lingering transaction that cannot be automatically closed by Amazon Redshift due to ongoing user workloads.
4. D. The nightly data refreshes left the dashboard tables in need of a vacuum operation that could not be automatically performed by Amazon Redshift due to ongoing user workloads.

Correct Answer: D
https://github.com/awsdocs/amazon-redshift-developer-guide/issues/21

A company uses Amazon kinesis Data Streams to ingest and process customer behavior information from application users each day. A data analytics specialist notices that its data stream is throttling. The specialist has turned on enhanced monitoring for the Kinesis data stream and has verified that the data stream did not exceed the data limits. The specialist discovers that there are hot shards
Which solution will resolve this issue?

1. A. Use a random partition key to ingest the records.
2. B. Increase the number of shards Split the size of the log records.
3. C. Limit the number of records that are sent each second by the producer to match the capacity of the stream.
4. D. Decrease the size of the records that are sent from the producer to match the capacity of the stream.

Correct Answer: A