Amazon DAS-C01 Exam Questions Instant Access

Question 1

A financial company uses Apache Hive on Amazon EMR for ad-hoc queries. Users are complaining of sluggish performance.

A data analyst notes the following:

Approximately 90% of queries are submitted 1 hour after the market opens.

Hadoop Distributed File System (HDFS) utilization never exceeds 10%.

Which solution would help address the performance issues?

ACreate instance fleet configurations for core and task nodes. Create an automatic scaling policy to scale out the instance groups based on the Amazon CloudWatch CapacityRemainingGB metric. Create an automatic scaling policy to scale in the instance fleet based on the CloudWatch CapacityRemainingGB metric.

BCreate instance fleet configurations for core and task nodes. Create an automatic scaling policy to scale out the instance groups based on the Amazon CloudWatch YARNMemoryAvailablePercentage metric. Create an automatic scaling policy to scale in the instance fleet based on the CloudWatch YARNMemoryAvailablePercentage metric.

CCreate instance group configurations for core and task nodes. Create an automatic scaling policy to scale out the instance groups based on the Amazon CloudWatch CapacityRemainingGB metric. Create an
automatic scaling policy to scale in the instance groups based on the CloudWatch CapacityRemainingGB metric.

DCreate instance group configurations for core and task nodes. Create an automatic scaling policy to scale out the instance groups based on the Amazon CloudWatch YARNMemoryAvailablePercentage metric. Create an automatic scaling policy to scale in the instance groups based on the CloudWatch YARNMemoryAvailablePercentage metric.

Answer : D

https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-plan-instances-guidelines.html

Question 2

A company's data science team is designing a shared dataset repository on a Windows server. The data repository will store a large amount of training data that the data

science team commonly uses in its machine learning models. The data scientists create a random number of new datasets each day.

The company needs a solution that provides persistent, scalable file storage and high levels of throughput and IOPS. The solution also must be highly available and must

integrate with Active Directory for access control.

Which solution will meet these requirements with the LEAST development effort?

AStore datasets as files in an Amazon EMR cluster. Set the Active Directory domain for authentication.

BStore datasets as files in Amazon FSx for Windows File Server. Set the Active Directory domain for authentication.

CStore datasets as tables in a multi-node Amazon Redshift cluster. Set the Active Directory domain for authentication.

DStore datasets as global tables in Amazon DynamoDB. Build an application to integrate authentication with the Active Directory domain.

Answer : B

Question 3

Once a month, a company receives a 100 MB .csv file compressed with gzip. The file contains 50,000 property listing records and is stored in Amazon S3 Glacier. The company needs its data analyst to query a subset of the data for a specific vendor.

What is the most cost-effective solution?

ALoad the data into Amazon S3 and query it with Amazon S3 Select.

BQuery the data from Amazon S3 Glacier directly with Amazon Glacier Select.

CLoad the data to Amazon S3 and query it with Amazon Athena.

DLoad the data to Amazon S3 and query it with Amazon Redshift Spectrum.

Answer : A

Question 4

A media content company has a streaming playback application. The company wants to collect and analyze the data to provide near-real-time feedback on playback issues. The company needs to consume this data and return results within 30 seconds according to the service-level agreement (SLA). The company needs the consumer to identify playback issues, such as quality during a specified timeframe. The data will be emitted as JSON and may change schemas over time.

Which solution will allow the company to collect data for processing while meeting these requirements?

ASend the data to Amazon Kinesis Data Firehose with delivery to Amazon S3. Configure an S3 event trigger an AWS Lambda function to process the data. The Lambda function will consume the data and process it to identify potential playback issues. Persist the raw data to Amazon S3.

BSend the data to Amazon Managed Streaming for Kafka and configure an Amazon Kinesis Analytics for Java application as the consumer. The application will consume the data and process it to identify potential playback issues. Persist the raw data to Amazon DynamoDB.

CSend the data to Amazon Kinesis Data Firehose with delivery to Amazon S3. Configure Amazon S3 to trigger an event for AWS Lambda to process. The Lambda function will consume the data and process it to identify potential playback issues. Persist the raw data to Amazon DynamoDB.

DSend the data to Amazon Kinesis Data Streams and configure an Amazon Kinesis Analytics for Java application as the consumer. The application will consume the data and process it to identify potential playback issues. Persist the raw data to Amazon S3.

Answer : D

https://aws.amazon.com/blogs/aws/new-amazon-kinesis-data-analytics-for-java/

Question 5

A company is sending historical datasets to Amazon S3 for storage. A data engineer at the company wants to make these datasets available for analysis using Amazon Athen

a. The engineer also wants to encrypt the Athena query results in an S3 results location by using AWS solutions for encryption. The requirements for encrypting the query results are as follows:

Use custom keys for encryption of the primary dataset query results.

Use generic encryption for all other query results.

Provide an audit trail for the primary dataset queries that shows when the keys were used and by whom.

Which solution meets these requirements?

AUse server-side encryption with S3 managed encryption keys (SSE-S3) for the primary dataset. Use SSE-S3 for the other datasets.

BUse server-side encryption with customer-provided encryption keys (SSE-C) for the primary dataset. Use server-side encryption with S3 managed encryption keys (SSE-S3) for the other datasets.

CUse server-side encryption with AWS KMS managed customer master keys (SSE-KMS CMKs) for the primary dataset. Use server-side encryption with S3 managed encryption keys (SSE-S3) for the other datasets.

DUse client-side encryption with AWS Key Management Service (AWS KMS) customer managed keys for the primary dataset. Use S3 client-side encryption with client-side keys for the other datasets.

Answer : A

Question 6

An analytics team uses Amazon OpenSearch Service for an analytics API to be used by data analysts. The OpenSearch Service cluster is configured with three master nodes. The analytics team uses Amazon Managed Streaming for Apache Kafka (Amazon MSK) and a customized data pipeline to ingest and store 2 months of data in an OpenSearch Service cluster. The cluster stopped responding, which is regularly causing timeout requests. The analytics team discovers the cluster is handling too many bulk indexing requests.

Which actions would improve the performance of the OpenSearch Service cluster? (Select TWO.)

AReduce the number of API bulk requests on the OpenSearch Service cluster and reduce the size of each bulk request.

BScale out the OpenSearch Service cluster by increasing the number of nodes.

CReduce the number of API bulk requests on the OpenSearch Service cluster, but increase the size of each bulk request.

DIncrease the number of master nodes for the OpenSearch Service cluster.
Scale down the pipeline component that is used to ingest the data into the OpenSearch Service cluster.

Answer : A, B

Question 7

A company uses Amazon Redshift as its data warehouse. The Redshift cluster is not encrypted. A data analytics specialist needs to use hardware security module (HSM) managed encryption keys to encrypt the data that is stored in the Redshift cluster.

Which combination of steps will meet these requirements? (Select THREE.)

AStop all write operations on the source cluster. Unload data from the source cluster.

BCopy the data to a new target cluster that is encrypted with AWS Key Management Service (AWS KMS).

CModify the source cluster by activating AWS CloudHSM encryption. Configure Amazon Redshift to automatically migrate data to a new encrypted cluster.

DModify the source cluster by activating encryption from an external HSM. Configure Amazon Redshift to automatically migrate data to a new encrypted cluster.

ECopy the data to a new target cluster that is encrypted with an HSM from AWS CloudHSM.

FRename the source cluster and the target cluster after the migration so that the target cluster is using the original endpoint.

Answer : A, E, F

Amazon AWS Certified Data Analytics - Specialty DAS-C01 Exam Questions