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Latest DAS-C01 Exam Questions


Question # 1



A company has developed an Apache Hive script to batch process data stared in Amazon S3. The script needs to run once every day and store the output in Amazon S3. The company tested the script, and it completes within 30 minutes on a small local three-node cluster.
Which solution is the MOST cost-effective for scheduling and executing the script?

A.

Create an AWS Lambda function to spin up an Amazon EMR cluster with a Hive execution step. Set
KeepJobFlowAliveWhenNoSteps to false and disable the termination protection flag. Use Amazon
CloudWatch Events to schedule the Lambda function to run daily.

B.

Use the AWS Management Console to spin up an Amazon EMR cluster with Python Hue. Hive, and
Apache Oozie. Set the termination protection flag to true and use Spot Instances for the core nodes of
the cluster. Configure an Oozie workflow in the cluster to invoke the Hive script daily

C.

Create an AWS Glue job with the Hive script to perform the batch operation. Configure the job to run
once a day using a time-based schedule

D.

Use AWS Lambda layers and load the Hive runtime to AWS Lambda and copy the Hive script.
Schedule the Lambda function to run daily by creating a workflow using AWS Step Functions.




C.
  

Create an AWS Glue job with the Hive script to perform the batch operation. Configure the job to run
once a day using a time-based schedule







Question # 2



A financial company uses Amazon S3 as its data lake and has set up a data warehouse using a multi-node Amazon Redshift cluster. The data files in the data lake are organized in folders based on the data source of each data file. All the data files are loaded to one table in the Amazon Redshift cluster using a separate COPY command for each data file location. With this approach, loading all the data files into Amazon Redshift takes
a long time to complete. Users want a faster solution with little or no increase in cost while maintaining the segregation of the data files in the S3 data lake.
Which solution meets these requirements?

A.

Use Amazon EMR to copy all the data files into one folder and issue a COPY command to load the data into Amazon Redshift.

B.

Load all the data files in parallel to Amazon Aurora, and run an AWS Glue job to load the data into
Amazon Redshift

C.

Use an AWS Glue job to copy all the data files into one folder and issue a COPY command to load the
data into Amazon Redshift.

D.

Create a manifest file that contains the data file locations and issue a COPY command to load the data
into Amazon Redshift.




A.
  

Use Amazon EMR to copy all the data files into one folder and issue a COPY command to load the data into Amazon Redshift.







Question # 3



A company uses Amazon Elasticsearch Service (Amazon ES) to store and analyze its website clickstream
data. The company ingests 1 TB of data daily using Amazon Kinesis Data Firehose and stores one day’s worth
of data in an Amazon ES cluster.
The company has very slow query performance on the Amazon ES index and occasionally sees errors from
Kinesis Data Firehose when attempting to write to the index. The Amazon ES cluster has 10 nodes running a
single index and 3 dedicated master nodes. Each data node has 1.5 TB of Amazon EBS storage attached and
the cluster is configured with 1,000 shards. Occasionally, JVMMemoryPressure errors are found in the cluster
logs.
Which solution will improve the performance of Amazon ES?

A.

Increase the memory of the Amazon ES master nodes.

B.

Decrease the number of Amazon ES data nodes.

C.

Decrease the number of Amazon ES shards for the index.

D.

Increase the number of Amazon ES shards for the index.




C.
  

Decrease the number of Amazon ES shards for the index.







Question # 4



A media analytics company consumes a stream of social media posts. The posts are sent to an Amazon Kinesis data stream partitioned on user_id. An AWS Lambda function retrieves the records and validates the content  before loading the posts into an Amazon Elasticsearch cluster. The validation process needs to receive the posts for a given user in the order they were received. A data analyst has noticed that, during peak hours, the social media platform posts take more than an hour to appear in the Elasticsearch cluster. What should the data analyst do reduce this latency?

A.

Migrate the validation process to Amazon Kinesis Data Firehose.

B.

Migrate the Lambda consumers from standard data stream iterators to an HTTP/2 stream consumer.

C.

Increase the number of shards in the stream.

D.

Configure multiple Lambda functions to process the stream.




C.
  

Increase the number of shards in the stream.







Question # 5



A mobile gaming company wants to capture data from its gaming app and make the data available for analysis
immediately. The data record size will be approximately 20 KB. The company is concerned about achieving
optimal throughput from each device. Additionally, the company wants to develop a data stream processing
application with dedicated throughput for each consumer.
Which solution would achieve this goal?

A.

Have the app call the PutRecords API to send data to Amazon Kinesis Data Streams. Use the enhanced fan-out feature while consuming the data.

B.

Have the app call the PutRecordBatch API to send data to Amazon Kinesis Data Firehose. Submit a
support case to enable dedicated throughput on the account.

C.

Have the app use Amazon Kinesis Producer Library (KPL) to send data to Kinesis Data Firehose. Use
the enhanced fan-out feature while consuming the data.

D.

Have the app call the PutRecords API to send data to Amazon Kinesis Data Streams. Host the streamprocessing application on Amazon EC2 with Auto Scaling.




D.
  

Have the app call the PutRecords API to send data to Amazon Kinesis Data Streams. Host the streamprocessing application on Amazon EC2 with Auto Scaling.







Question # 6



A streaming application is reading data from Amazon Kinesis Data Streams and immediately writing the data
to an Amazon S3 bucket every 10 seconds. The application is reading data from hundreds of shards. The batch
interval cannot be changed due to a separate requirement. The data is being accessed by Amazon Athena.
Users are seeing degradation in query performance as time progresses.
Which action can help improve query performance?

A.

Merge the files in Amazon S3 to form larger files.

B.

Increase the number of shards in Kinesis Data Streams.

C.

Add more memory and CPU capacity to the streaming application.

D.

Write the files to multiple S3 buckets.




C.
  

Add more memory and CPU capacity to the streaming application.







Question # 7



A company that produces network devices has millions of users. Data is collected from the devices on an
hourly basis and stored in an Amazon S3 data lake.
The company runs analyses on the last 24 hours of data flow logs for abnormality detection and to
troubleshoot and resolve user issues. The company also analyzes historical logs dating back 2 years to discover
patterns and look for improvement opportunities.
The data flow logs contain many metrics, such as date, timestamp, source IP, and target IP. There are about 10
billion events every day.
How should this data be stored for optimal performance?

A.

In Apache ORC partitioned by date and sorted by source IP

B.

In compressed .csv partitioned by date and sorted by source IP

C.

In Apache Parquet partitioned by source IP and sorted by date

D.

In compressed nested JSON partitioned by source IP and sorted by date




D.
  

In compressed nested JSON partitioned by source IP and sorted by date







Question # 8



A company wants to improve user satisfaction for its smart home system by adding more features to its
recommendation engine. Each sensor asynchronously pushes its nested JSON data into Amazon Kinesis Data
Streams using the Kinesis Producer Library (KPL) in Java. Statistics from a set of failed sensors showed that,
when a sensor is malfunctioning, its recorded data is not always sent to the cloud.
The company needs a solution that offers near-real-time analytics on the data from the most updated sensors.
Which solution enables the company to meet these requirements?

A.

Set the RecordMaxBufferedTime property of the KPL to "-1" to disable the buffering on the sensor side. Use Kinesis Data Analytics to enrich the data based on a company-developed anomaly detection SQL script. Push the enriched data to a fleet of Kinesis data streams and enable the data transformation feature to flatten the JSON file. Instantiate a dense storage Amazon Redshift cluster and use it as the destination for the Kinesis Data Firehose delivery stream.

B.

Update the sensors code to use the PutRecord/PutRecords call from the Kinesis Data Streams API with
the AWS SDK for Java. Use Kinesis Data Analytics to enrich the data based on a company-developed
anomaly detection SQL script. Direct the output of KDA application to a Kinesis Data Firehose delivery
stream, enable the data transformation feature to flatten the JSON file, and set the Kinesis Data Firehose destination to an Amazon Elasticsearch Service cluster.

C.

Set the RecordMaxBufferedTime property of the KPL to "0" to disable the buffering on the sensor side.

D.

Connect for each stream a dedicated Kinesis Data Firehose delivery stream and enable the data
transformation feature to flatten the JSON file before sending it to an Amazon S3 bucket. Load the S3
data into an Amazon Redshift cluster.

E.

Update the sensors code to use the PutRecord/PutRecords call from the Kinesis Data Streams API with the AWS SDK for Java. Use AWS Glue to fetch and process data from the stream using the Kinesis Client Library (KCL). Instantiate an Amazon Elasticsearch Service cluster and use AWS Lambda to directly push data into it.




A.
  

Set the RecordMaxBufferedTime property of the KPL to "-1" to disable the buffering on the sensor side. Use Kinesis Data Analytics to enrich the data based on a company-developed anomaly detection SQL script. Push the enriched data to a fleet of Kinesis data streams and enable the data transformation feature to flatten the JSON file. Instantiate a dense storage Amazon Redshift cluster and use it as the destination for the Kinesis Data Firehose delivery stream.







Question # 9



A media company wants to perform machine learning and analytics on the data residing in its Amazon S3 data lake. There are two data transformation requirements that will enable the consumers within the company to create reports:
Daily transformations of 300 GB of data with different file formats landing in Amazon S3 at a scheduled
time.
One-time transformations of terabytes of archived data residing in the S3 data lake.
Which combination of solutions cost-effectively meets the company’s requirements for transforming the data? (Choose three.)

A.

For daily incoming data, use AWS Glue crawlers to scan and identify the schema.

B.

For daily incoming data, use Amazon Athena to scan and identify the schema.

C.

For daily incoming data, use Amazon Redshift to perform transformations.

D.

For daily incoming data, use AWS Glue workflows with AWS Glue jobs to perform transformations.

E.

For archived data, use Amazon EMR to perform data transformations.




B.
  

For daily incoming data, use Amazon Athena to scan and identify the schema.




C.
  

For daily incoming data, use Amazon Redshift to perform transformations.




D.
  

For daily incoming data, use AWS Glue workflows with AWS Glue jobs to perform transformations.







Question # 10



An Amazon Redshift database contains sensitive user data. Logging is necessary to meet compliance
requirements. The logs must contain database authentication attempts, connections, and disconnections. The logs must also contain each query run against the database and record which database user ran each query. Which steps will create the required logs?

 

A.

Enable Amazon Redshift Enhanced VPC Routing. Enable VPC Flow Logs to monitor traffic.

B.

Allow access to the Amazon Redshift database using AWS IAM only. Log access using AWS
CloudTrail.

C.

Enable audit logging for Amazon Redshift using the AWS Management Console or the AWS CLI.

D.

Enable and download audit reports from AWS Artifact.




C.
  

Enable audit logging for Amazon Redshift using the AWS Management Console or the AWS CLI.






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Amazon Web Services DAS-C01 Dumps - Latest Questions


Exam Code: DAS-C01
Exam Name: AWS Certified Data Analytics - Specialty

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