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Amazon Web Services DAS-C01 Dumps

Exam Code:
DAS-C01
Exam Name:
AWS Certified Data Analytics - Specialty
Last Update: Feb 29, 2024
207 Questions with Explanation
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AWS Certified Data Analytics (DAS-C01) is designed for individuals performing data analytics roles, as its name exam shows. It examines the candidate's ability to understand designing, building, securing, and maintaining data analytics solutions on AWS and the data lifecycle of collection, storage, processing, and visualization. Certification from AWS is an enterprise accreditation that verifies candidates' knowledge of AWS data lakes and analytics software.

Candidates for the AWS Certified Data Analytics – Specialty test must have the following qualifications: at least five years of expertise with data analytics techniques and two years of the practical learning experience with AWS. Second, expertise with AWS services to design, create, secure, and maintain analytics systems.

The AWS Certified Data Analytics exam is a 65-question Specialized level exam. The time limit is of 180 minutes to complete the exam. The exam is also available in two formats: a testing center and an online written exam. The exam fee for AWS Certified Data Analytics - Specialty is $300.

DAS-C01 Exam Details

Format: Multiple choice, Multiple Answer
Exam Type: Specialty
Exam Method: Testing center or online proctored exam
Time: 180 Min
Exam Price: $300 USD
Language: Available in English, Japanese, Korean, and Simplified Chinese

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AWS Certified Data Analytics - Specialty Questions and Answers

Questions 1

A marketing company is using Amazon EMR clusters for its workloads. The company manually installs third- party libraries on the clusters by logging in to the master nodes. A data analyst needs to create an automated solution to replace the manual process.

Which options can fulfill these requirements? (Choose two.)

Options:

A.

Place the required installation scripts in Amazon S3 and execute them using custom bootstrap actions.

B.

Place the required installation scripts in Amazon S3 and execute them through Apache Spark in Amazon EMR.

C.

Install the required third-party libraries in the existing EMR master node. Create an AMI out of that master node and use that custom AMI to re-create the EMR cluster.

D.

Use an Amazon DynamoDB table to store the list of required applications. Trigger an AWS Lambda function with DynamoDB Streams to install the software.

E.

Launch an Amazon EC2 instance with Amazon Linux and install the required third-party libraries on the instance. Create an AMI and use that AMI to create the EMR cluster.

Questions 2

An IOT company is collecting data from multiple sensors and is streaming the data to Amazon Managed Streaming for Apache Kafka (Amazon MSK). Each sensor type has

its own topic, and each topic has the same number of partitions.

The company is planning to turn on more sensors. However, the company wants to evaluate which sensor types are producing the most data sothat the company can scale

accordingly. The company needs to know which sensor types have the largest values for the following metrics: ByteslnPerSec and MessageslnPerSec.

Which level of monitoring for Amazon MSK will meet these requirements?

Options:

A.

DEFAULT level

B.

PER TOPIC PER BROKER level

C.

PER BROKER level

D.

PER TOPIC level

Questions 3

A company has a fitness tracker application that generates data from subscribers. The company needs real-time reporting on this data. The data is sent immediately, and the processing latency must be less than 1 second. The company wants to perform anomaly detection on the data as the data is collected. The company also requires a solution that minimizes operational overhead.

Which solution meets these requirements?

Options:

A.

Amazon EMR cluster with Apache Spark streaming, Spark SQL, and Spark's machine learning library (MLIib)

B.

Amazon Kinesis Data Firehose with Amazon S3 and Amazon Athena

C.

Amazon Kinesis Data Firehose with Amazon QuickSight

D.

Amazon Kinesis Data Streams with Amazon Kinesis Data Analytics

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