Most Recent Amazon DAS-C01 Exam Dumps

Prepare for the Amazon AWS Certified Data Analytics - Specialty exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.

QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Amazon DAS-C01 exam and achieve success.

The questions for DAS-C01 were last updated on Feb 22, 2025.

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Question No. 1

A company has an application that uses the Amazon Kinesis Client Library (KCL) to read records from a Kinesis data stream.

After a successful marketing campaign, the application experienced a significant increase in usage. As a result, a data analyst had to split some shards in the data stream. When the shards were split, the application started throwing an ExpiredIteratorExceptions error sporadically.

What should the data analyst do to resolve this?

AIncrease the number of threads that process the stream records.

BIncrease the provisioned read capacity units assigned to the stream's Amazon DynamoDB table.

CIncrease the provisioned write capacity units assigned to the stream's Amazon DynamoDB table.

DDecrease the provisioned write capacity units assigned to the stream's Amazon DynamoDB table.

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Correct Answer: C

Question No. 2

A central government organization is collecting events from various internal applications using Amazon Managed Streaming for Apache Kafka (Amazon MSK). The organization has configured a separate Kafka topic for each application to separate the dat

a. For security reasons, the Kafka cluster has been configured to only allow TLS encrypted data and it encrypts the data at rest.

A recent application update showed that one of the applications was configured incorrectly, resulting in writing data to a Kafka topic that belongs to another application. This resulted in multiple errors in the analytics pipeline as data from different applications appeared on the same topic. After this incident, the organization wants to prevent applications from writing to a topic different than the one they should write to.

Which solution meets these requirements with the least amount of effort?

ACreate a different Amazon EC2 security group for each application. Configure each security group to have access to a specific topic in the Amazon MSK cluster. Attach the security group to each application based on the topic that the applications should read and write to.

BInstall Kafka Connect on each application instance and configure each Kafka Connect instance to write to a specific topic only.

CUse Kafka ACLs and configure read and write permissions for each topic. Use the distinguished name of the clients' TLS certificates as the principal of the ACL.

DCreate a different Amazon EC2 security group for each application. Create an Amazon MSK cluster and Kafka topic for each application. Configure each security group to have access to the specific cluster.

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Correct Answer: B

Question No. 3

A company has multiple data workflows to ingest data from its operational databases into its data lake on Amazon S3. The workflows use AWS Glue and Amazon EMR for data processing and ETL. The company wants to enhance its architecture to provide automated orchestration and minimize manual intervention Which solution should the company use to manage the data workflows to meet these requirements?

AAWS Glue workflows

BAWS Step Functions

CAWS Lambda

DAWS Batch

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Correct Answer: B

This solution meets the requirements because:

AWS Step Functions is a fully managed service that allows you to create and orchestrate workflows that connect various AWS services, such as AWS Glue, Amazon EMR, Amazon S3, and others1.You can use Step Functions to automate your data workflows and handle complex logic, such as branching, parallel processing, error handling, retries, and timeouts1.

AWS Step Functions provides a graphical interface that lets you design and visualize your workflows as state machines, which are composed of a series of steps or tasks1.You can use the AWS Step Functions console, the AWS CLI, or the AWS SDKs to create and manage your state machines1.

AWS Step Functions integrates with AWS Glue and Amazon EMR to enable you to run data processing and ETL jobs as part of your workflows23.You can use the built-in connectors for these services to invoke them from your state machines23.You can also use Step Functions to monitor the status of your jobs and trigger actions based on the job outcomes23.

AWS Step Functions can help you minimize manual intervention by providing features such as automatic retries, catch blocks, and fallback states, which allow you to handle errors and failures gracefully in your workflows1.You can also use Step Functions to trigger your workflows based on events, such as a new file in S3 or a CloudWatch alarm1.

Question No. 4

A company hosts an Apache Flink application on premises. The application processes data from several Apache Kafka clusters. The data originates from a variety of sources, such as web applications mobile apps and operational databases The company has migrated some of these sources to AWS and now wants to migrate the Flink application. The company must ensure that data that resides in databases within the VPC does not traverse the internet The application must be able to process all the data that comes from the company's AWS solution, on-premises resources and the public internet

Which solution will meet these requirements with the LEAST operational overhead?

AImplement Flink on Amazon EC2 within the company's VPC Create Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in the VPC to collect data that comes from applications and databases within the VPC Use Amazon Kinesis Data Streams to collect data that comes from the public internet Configure Flink to have sources from Kinesis Data Streams Amazon MSK and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect

BImplement Flink on Amazon EC2 within the company's VPC Use Amazon Kinesis Data Streams to collect data that comes from applications and databases within the VPC and the public internet Configure Flink to have sources from Kinesis Data Streams and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect

CCreate an Amazon Kinesis Data Analytics application by uploading the compiled Flink jar file Use Amazon Kinesis Data Streams to collect data that comes from applications and databases within the VPC and the public internet Configure the Kinesis Data Analytics application to have sources from Kinesis Data Streams and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect

DCreate an Amazon Kinesis Data Analytics application by uploading the compiled Flink jar file Create Amazon Managed Streaming for Apache Kafka (Amazon MSK) clusters in the company's VPC to collect data that comes from applications and databases within the VPC Use Amazon Kinesis Data Streams to collect data that comes from the public internet Configure the Kinesis Data Analytics application to have sources from Kinesis Data Streams. Amazon MSK and any on-premises Kafka clusters by using AWS Client VPN or AWS Direct Connect

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Correct Answer: D

Question No. 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.

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Correct Answer: A

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