Amazon DAS-C01 Exam Practice Test Instant Access

Question 1

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.)

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

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

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

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

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

FFor archived data, use Amazon SageMaker to perform data transformations.

Answer : A, D, E

Question 2

A global pharmaceutical company receives test results for new drugs from various testing facilities worldwide. The results are sent in millions of 1 KB-sized JSON objects to an Amazon S3 bucket owned by the company. The data engineering team needs to process those files, convert them into Apache Parquet format, and load them into Amazon Redshift for data analysts to perform dashboard reporting. The engineering team uses AWS Glue to process the objects, AWS Step Functions for process orchestration, and Amazon CloudWatch for job scheduling.

More testing facilities were recently added, and the time to process files is increasing.

What will MOST efficiently decrease the data processing time?

AUse AWS Lambda to group the small files into larger files. Write the files back to Amazon S3. Process the files using AWS Glue and load them into Amazon Redshift tables.

BUse the AWS Glue dynamic frame file grouping option while ingesting the raw input files. Process the files and load them into Amazon Redshift tables.

CUse the Amazon Redshift COPY command to move the files from Amazon S3 into Amazon Redshift tables directly. Process the files in Amazon Redshift.

DUse Amazon EMR instead of AWS Glue to group the small input files. Process the files in Amazon EMR and load them into Amazon Redshift tables.

Answer : A

Question 3

A regional energy company collects voltage data from sensors attached to buildings. To address any known dangerous conditions, the company wants to be alerted when a sequence of two voltage drops is detected within 10 minutes of a voltage spike at the same building. It is important to ensure that all messages are delivered as quickly as possible. The system must be fully managed and highly available. The company also needs a solution that will automatically scale up as it covers additional cites with this monitoring feature. The alerting system is subscribed to an Amazon SNS topic for remediation.

Which solution meets these requirements?

ACreate an Amazon Managed Streaming for Kafka cluster to ingest the data, and use an Apache Spark Streaming with Apache Kafka consumer API in an automatically scaled Amazon EMR cluster to process the incoming data. Use the Spark Streaming application to detect the known event sequence and send the SNS message.

BCreate a REST-based web service using Amazon API Gateway in front of an AWS Lambda function. Create an Amazon RDS for PostgreSQL database with sufficient Provisioned IOPS (PIOPS). In the Lambda function, store incoming events in the RDS database and query the latest data to detect the known event sequence and send the SNS message.

CCreate an Amazon Kinesis Data Firehose delivery stream to capture the incoming sensor data. Use an AWS Lambda transformation function to detect the known event sequence and send the SNS message.

DCreate an Amazon Kinesis data stream to capture the incoming sensor data and create another stream for alert messages. Set up AWS Application Auto Scaling on both. Create a Kinesis Data Analytics for Java application to detect the known event sequence, and add a message to the message stream. Configure an AWS Lambda function to poll the message stream and publish to the SNS topic.

Answer : D

Question 4

A company stores Apache Parquet-formatted files in Amazon S3 The company uses an AWS Glue Data Catalog to store the table metadata and Amazon Athena to query and analyze the data The tables have a large number of partitions The queries are only run on small subsets of data in the table A data analyst adds new time partitions into the table as new data arrives The data analyst has been asked to reduce the query runtime

Which solution will provide the MOST reduction in the query runtime?

AConvert the Parquet files to the csv file format..Then attempt to query the data again

BConvert the Parquet files to the Apache ORC file format. Then attempt to query the data again

CUse partition projection to speed up the processing of the partitioned table

DAdd more partitions to be used over the table. Then filter over two partitions and put all columns in the WHERE clause

Answer : C

Question 5

A company uses Amazon Elasticsearch Service (Amazon ES) to store and analyze its website clickstream dat

a. 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?

AIncrease the memory of the Amazon ES master nodes.

BDecrease the number of Amazon ES data nodes.

CDecrease the number of Amazon ES shards for the index.

DIncrease the number of Amazon ES shards for the index.

Answer : C

https://aws.amazon.com/premiumsupport/knowledge-center/high-jvm-memory-pressure-elasticsearch/

Question 6

A human resources company maintains a 10-node Amazon Redshift cluster to run analytics queries on the company's dat

a. The Amazon Redshift cluster contains a product table and a transactions table, and both tables have a product_sku column. The tables are over 100 GB in size. The majority of queries run on both tables.

Which distribution style should the company use for the two tables to achieve optimal query performance?

AAn EVEN distribution style for both tables

BA KEY distribution style for both tables

CAn ALL distribution style for the product table and an EVEN distribution style for the transactions table

DAn EVEN distribution style for the product table and an KEY distribution style for the transactions table

Answer : B

Question 7

A company has a marketing department and a finance department. The departments are storing data in Amazon S3 in their own AWS accounts in AWS Organizations. Both departments use AWS Lake Formation to catalog and secure their dat

a. The departments have some databases and tables that share common names.

The marketing department needs to securely access some tables from the finance department.

Which two steps are required for this process? (Choose two.)

AThe finance department grants Lake Formation permissions for the tables to the external account for the marketing department.

BThe finance department creates cross-account IAM permissions to the table for the marketing department role.

CThe marketing department creates an IAM role that has permissions to the Lake Formation tables.

Answer : A, B

Granting Lake Formation Permissions

Creating an IAM role (AWS CLI)

https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create_for-user.html

Amazon AWS Certified Data Analytics - Specialty DAS-C01 Exam Practice Test