DATA-ENGINEER-ASSOCIATE VALID EXAM TUTORIAL, DATA-ENGINEER-ASSOCIATE VISUAL CERT EXAM

Data-Engineer-Associate Valid Exam Tutorial, Data-Engineer-Associate Visual Cert Exam

Data-Engineer-Associate Valid Exam Tutorial, Data-Engineer-Associate Visual Cert Exam

Blog Article

Tags: Data-Engineer-Associate Valid Exam Tutorial, Data-Engineer-Associate Visual Cert Exam, Data-Engineer-Associate Exam Prep, Data-Engineer-Associate Free Dump Download, Data-Engineer-Associate Pass Leader Dumps

PrepAwayETE have the latest Amazon certification Data-Engineer-Associate exam training materials. The industrious PrepAwayETE's IT experts through their own expertise and experience continuously produce the latest Amazon Data-Engineer-Associate training materials to facilitate IT professionals to pass the Amazon Certification Data-Engineer-Associate Exam. The certification of Amazon Data-Engineer-Associate more and more valuable in the IT area and a lot people use the products of PrepAwayETE to pass Amazon certification Data-Engineer-Associate exam. Through so many feedbacks of these products, our PrepAwayETE products prove to be trusted.

PrepAwayETE offers updated and real Amazon Data-Engineer-Associate Exam Dumps for AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) test takers who want to prepare quickly for the Data-Engineer-Associate examination. These actual Data-Engineer-Associate exam questions have been compiled by a team of professionals after a thorough analysis of past papers and current content of the Data-Engineer-Associate test. If students prepare with these valid Data-Engineer-Associate questions, they will surely become capable of clearing the Data-Engineer-Associate examination within a few days.

>> Data-Engineer-Associate Valid Exam Tutorial <<

High Pass-Rate Data-Engineer-Associate Valid Exam Tutorial by PrepAwayETE

Cracking the AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) exam brings high-paying jobs, promotions, and validation of talent. Dozens of AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) exam applicants don't get passing scores in the real Data-Engineer-Associate exam because of using invalid Amazon Data-Engineer-Associate exam dumps. Failure in the Data-Engineer-Associate Exam leads to a loss of time, money, and confidence. If you are an applicant for the AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) exam, you can prevent these losses by using the latest real Data-Engineer-Associate exam questions of PrepAwayETE.

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q49-Q54):

NEW QUESTION # 49
A media company wants to improve a system that recommends media content to customer based on user behavior and preferences. To improve the recommendation system, the company needs to incorporate insights from third-party datasets into the company's existing analytics platform.
The company wants to minimize the effort and time required to incorporate third-party datasets.
Which solution will meet these requirements with the LEAST operational overhead?

  • A. Use API calls to access and integrate third-party datasets from AWS
  • B. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from AWS CodeCommit repositories.
  • C. Use API calls to access and integrate third-party datasets from AWS Data Exchange.
  • D. Use Amazon Kinesis Data Streams to access and integrate third-party datasets from Amazon Elastic Container Registry (Amazon ECR).

Answer: C

Explanation:
AWS Data Exchange is a service that makes it easy to find, subscribe to, and use third-party data in the cloud.
It provides a secure and reliable way to access and integrate data from various sources, such as data providers, public datasets, or AWS services. Using AWS Data Exchange, you can browse and subscribe to data products that suit your needs, and then use API calls or the AWS Management Console to export the data to Amazon S3, where you can use it with your existing analytics platform. This solution minimizes the effort and time required to incorporate third-party datasets, as you do not need to set up and manage data pipelines, storage, or access controls. You also benefit from the data quality and freshness provided by the data providers, who can update their data products as frequently as needed12.
The other options are not optimal for the following reasons:
B: Use API calls to access and integrate third-party datasets from AWS. This option is vague and does not specify which AWS service or feature is used to access and integrate third-party datasets. AWS offers a variety of services and features that can help with data ingestion, processing, and analysis, but not all of them are suitable for the given scenario. For example, AWS Glue is a serverless data integration service that can help you discover, prepare, and combine data from various sources, but it requires you to create and run data extraction, transformation, and loading (ETL) jobs, which can add operational overhead3.
C: Use Amazon Kinesis Data Streams to access and integrate third-party datasets from AWS CodeCommit repositories. This option is not feasible, as AWS CodeCommit is a source control service that hosts secure Git-based repositories, not a data source that can be accessed by Amazon Kinesis Data Streams. Amazon Kinesis Data Streams is a service that enables you to capture, process, and analyze data streams in real time, suchas clickstream data, application logs, or IoT telemetry. It does not support accessing and integrating data from AWS CodeCommit repositories, which are meant for storing and managing code, not data .
D: Use Amazon Kinesis Data Streams to access and integrate third-party datasets from Amazon Elastic Container Registry (Amazon ECR). This option is also not feasible, as Amazon ECR is a fully managed container registry service that stores, manages, and deploys container images, not a data source that can be accessed by Amazon Kinesis Data Streams. Amazon Kinesis Data Streams does not support accessing and integrating data from Amazon ECR, which is meant for storing and managing container images, not data .
References:
1: AWS Data Exchange User Guide
2: AWS Data Exchange FAQs
3: AWS Glue Developer Guide
4: AWS CodeCommit User Guide
5: Amazon Kinesis Data Streams Developer Guide
6: Amazon Elastic Container Registry User Guide
7: Build a Continuous Delivery Pipeline for Your Container Images with Amazon ECR as Source


NEW QUESTION # 50
A company has a production AWS account that runs company workloads. The company's security team created a security AWS account to store and analyze security logs from the production AWS account. The security logs in the production AWS account are stored in Amazon CloudWatch Logs.
The company needs to use Amazon Kinesis Data Streams to deliver the security logs to the security AWS account.
Which solution will meet these requirements?

  • A. Create a destination data stream in the production AWS account. In the production AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the security AWS account.
  • B. Create a destination data stream in the production AWS account. In the security AWS account, create an IAM role that has cross-account permissions to Kinesis Data Streams in the production AWS account.
  • C. Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the security AWS account.
  • D. Create a destination data stream in the security AWS account. Create an IAM role and a trust policy to grant CloudWatch Logs the permission to put data into the stream. Create a subscription filter in the production AWS account.

Answer: D

Explanation:
Amazon Kinesis Data Streams is a service that enables you to collect, process, and analyze real-time streaming data. You can use Kinesis Data Streams to ingest data from various sources, such as Amazon CloudWatch Logs, and deliver it to different destinations, such as Amazon S3 or Amazon Redshift. To use Kinesis Data Streams to deliver the security logs from the production AWS account to the security AWS account, you need to create a destination data stream in the security AWS account. This data stream will receive the log data from the CloudWatch Logs service in the production AWS account. To enable this cross-account data delivery, you need to create an IAM role and a trust policy in the security AWS account. The IAM role defines the permissions that the CloudWatch Logs service needs to put data into the destination data stream. The trust policy allows the production AWS account to assume the IAM role. Finally, you need to create a subscription filter in the production AWS account. A subscription filter defines the pattern to match log events and the destination to send the matching events. In this case, the destination is the destination data stream in the security AWS account. This solution meets the requirements of using Kinesis Data Streams to deliver the security logs to the security AWS account. The other options are either not possible or not optimal. You cannot create a destination data stream in the production AWS account, as this would not deliver the data to the security AWS account. You cannot create a subscription filter in the security AWS account, as this would not capture the log events from the production AWS account. Reference:
Using Amazon Kinesis Data Streams with Amazon CloudWatch Logs
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 3: Data Ingestion and Transformation, Section 3.3: Amazon Kinesis Data Streams


NEW QUESTION # 51
A company is developing an application that runs on Amazon EC2 instances. Currently, the data that the application generates is temporary. However, the company needs to persist the data, even if the EC2 instances are terminated.
A data engineer must launch new EC2 instances from an Amazon Machine Image (AMI) and configure the instances to preserve the data.
Which solution will meet this requirement?

  • A. Launch new EC2 instances by using an AMI that is backed by a root Amazon Elastic Block Store (Amazon EBS) volume that contains the application data. Apply the default settings to the EC2 instances.
  • B. Launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume. Attach an Amazon Elastic Block Store (Amazon EBS) volume to contain the application data. Apply the default settings to the EC2 instances.
  • C. Launch new EC2 instances by using an AMI that is backed by an Amazon Elastic Block Store (Amazon EBS) volume. Attach an additional EC2 instance store volume to contain the application data. Apply the default settings to the EC2 instances.
  • D. Launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume that contains the application data. Apply the default settings to the EC2 instances.

Answer: B

Explanation:
Amazon EC2 instances can use two types of storage volumes: instance store volumes and Amazon EBS volumes. Instance store volumes are ephemeral, meaning they are only attached to the instance for the duration of its life cycle. If the instance is stopped, terminated, or fails, the data on the instance store volume is lost. Amazon EBS volumes are persistent, meaning they can be detached from the instance and attached to another instance, and the data on the volume is preserved. To meet the requirement of persisting the data even if the EC2 instances are terminated, the data engineer must use Amazon EBS volumes to store the application data. The solution is to launch new EC2 instances by using an AMI that is backed by an EC2 instance store volume, which is the default option for most AMIs. Then, the data engineer must attach an Amazon EBS volume to each instance and configure the application to write the data to the EBS volume. This way, the data will be saved on the EBS volume and can be accessed by another instance if needed. The data engineer can apply the default settings to the EC2 instances, as there is no need to modify the instance type, security group, or IAM role for this solution. The other options are either not feasible or not optimal. Launching new EC2 instances by using an AMI that is backed by an EC2 instance store volume that contains the application data (option A) or by using an AMI that is backed by a root Amazon EBS volume that contains the application data (option B) would not work, as the data on the AMI would be outdated and overwritten by the new instances. Attaching an additional EC2 instance store volume to contain the application data (option D) would not work, as the data on the instance store volume would be lost if the instance is terminated. References:
* Amazon EC2 Instance Store
* Amazon EBS Volumes
* AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 2: Data Store Management, Section 2.1: Amazon EC2


NEW QUESTION # 52
A company is migrating its database servers from Amazon EC2 instances that run Microsoft SQL Server to Amazon RDS for Microsoft SQL Server DB instances. The company's analytics team must export large data elements every day until the migration is complete. The data elements are the result of SQL joins across multiple tables. The data must be in Apache Parquet format. The analytics team must store the data in Amazon S3.
Which solution will meet these requirements in the MOST operationally efficient way?

  • A. Create a view in the EC2 instance-based SQL Server databases that contains the required data elements.
    Create an AWS Glue job that selects the data directly from the view and transfers the data in Parquet format to an S3 bucket. Schedule the AWS Glue job to run every day.
  • B. Create an AWS Lambda function that queries the EC2 instance-based databases by using Java Database Connectivity (JDBC). Configure the Lambda function to retrieve the required data, transform the data into Parquet format, and transfer the data into an S3 bucket. Use Amazon EventBridge to schedule the Lambda function to run every day.
  • C. Schedule SQL Server Agent to run a daily SQL query that selects the desired data elements from the EC2 instance-based SQL Server databases. Configure the query to direct the output .csv objects to an S3 bucket. Create an S3 event that invokes an AWS Lambda function to transform the output format from .csv to Parquet.
  • D. Use a SQL query to create a view in the EC2 instance-based SQL Server databases that contains the required data elements. Create and run an AWS Glue crawler to read the view. Create an AWS Glue job that retrieves the data and transfers the data in Parquet format to an S3 bucket. Schedule the AWS Glue job to run every day.

Answer: A

Explanation:
Option A is the most operationally efficient way to meet the requirements because it minimizes the number of steps and services involved in the data export process. AWS Glue is a fully managed service that can extract, transform, and load (ETL) data from various sources to various destinations, including Amazon S3. AWS Glue can also convert data to different formats, such as Parquet, which is a columnar storage format that is optimized for analytics. By creating a view in the SQL Server databases that contains the required data elements, the AWS Glue job can select the data directly from the view without having to perform any joins or transformations on the source data. The AWS Glue job can then transfer the data in Parquet format to an S3 bucket and run on a daily schedule.
Option B is not operationally efficient because it involves multiple steps and services to export the data. SQL Server Agent is a tool that can run scheduled tasks on SQL Server databases, such as executing SQL queries.
However, SQL Server Agent cannot directlyexport data to S3, so the query output must be saved as .csv objects on the EC2 instance. Then, an S3 event must be configured to trigger an AWS Lambda function that can transform the .csv objects to Parquet format and upload them to S3. This option adds complexity and latency to the data export process and requires additional resources and configuration.
Option C is not operationally efficient because it introduces an unnecessary step of running an AWS Glue crawler to read the view. An AWS Glue crawler is a service that can scan data sources and create metadata tables in the AWS Glue Data Catalog. The Data Catalog is a central repository that stores information about the data sources, such as schema, format, and location. However, in this scenario, the schema and format of the data elements are already known and fixed, so there is no need to run a crawler to discover them. The AWS Glue job can directly select the data from the view without using the Data Catalog. Running a crawler adds extra time and cost to the data export process.
Option D is not operationally efficient because it requires custom code and configuration to query the databases and transform the data. An AWS Lambda function is a service that can run code in response to events or triggers, such as Amazon EventBridge. Amazon EventBridge is a service that can connect applications and services with event sources, such as schedules, and route them to targets, such as Lambda functions. However, in this scenario, using a Lambda function to query the databases and transform the data is not the best option because it requires writing and maintaining code that uses JDBC to connect to the SQL Server databases, retrieve the required data, convert the data to Parquet format, and transfer the data to S3.
This option also has limitations on the execution time, memory, and concurrency of the Lambda function, which may affect the performance and reliability of the data export process.
:
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide
AWS Glue Documentation
Working with Views in AWS Glue
Converting to Columnar Formats


NEW QUESTION # 53
A company saves customer data to an Amazon S3 bucket. The company uses server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the bucket. The dataset includes personally identifiable information (PII) such as social security numbers and account details.
Data that is tagged as PII must be masked before the company uses customer data for analysis. Some users must have secure access to the PII data during the preprocessing phase. The company needs a low-maintenance solution to mask and secure the PII data throughout the entire engineering pipeline.
Which combination of solutions will meet these requirements? (Select TWO.)

  • A. Use AWS Glue DataBrew to perform extract, transform, and load (ETL) tasks that mask the PII data before analysis.
  • B. Write custom scripts in an application to mask the PII data and to control access.
  • C. Use Amazon GuardDuty to monitor access patterns for the PII data that is used in the engineering pipeline.
  • D. Configure an Amazon Made discovery job for the S3 bucket.
  • E. Use AWS Identity and Access Management (IAM) to manage permissions and to control access to the PII data.

Answer: A,E

Explanation:
To address the requirement of masking PII data and ensuring secure access throughout the data pipeline, the combination of AWS Glue DataBrew and IAM provides a low-maintenance solution.
A . AWS Glue DataBrew for Masking:
AWS Glue DataBrew provides a visual tool to perform data transformations, including masking PII data. It allows for easy configuration of data transformation tasks without requiring manual coding, making it ideal for this use case.
Reference:
D . AWS Identity and Access Management (IAM):
Using IAM policies allows fine-grained control over access to PII data, ensuring that only authorized users can view or process sensitive data during the pipeline stages.
Alternatives Considered:
B (Amazon GuardDuty): GuardDuty is for threat detection and does not handle data masking or access control for PII.
C (Amazon Macie): Macie can help discover sensitive data but does not handle the masking of PII or access control.
E (Custom scripts): Custom scripting increases the operational burden compared to a built-in solution like DataBrew.
AWS Glue DataBrew for Data Masking
IAM Policies for PII Access Control


NEW QUESTION # 54
......

We provide Amazon Data-Engineer-Associate exam product in three different formats to accommodate diverse learning styles and help candidates prepare successfully for the Data-Engineer-Associate exam. These formats include Data-Engineer-Associate web-based practice test, desktop-based practice exam software, and AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) pdf file. Before purchasing, customers can try a free demo to assess the quality of the Amazon Data-Engineer-Associate practice exam material.

Data-Engineer-Associate Visual Cert Exam: https://www.prepawayete.com/Amazon/Data-Engineer-Associate-practice-exam-dumps.html

Amazon Data-Engineer-Associate Valid Exam Tutorial Three versions for your personal taste, We hope that more people can benefit from our Data-Engineer-Associate study guide, If you want to know more about Data-Engineer-Associate test dumps, please visit PrepAwayETE or consult our customer service, Dear, are you tired of the study preparation for Data-Engineer-Associate exam test, PrepAwayETE Data-Engineer-Associate Visual Cert Exam will provide you with a full refund or another exam of your choice absolutely free within 90 days from the date of purchase if for any reason you do not pass your exam.

As you read, you'll start to see what things you need to know to Data-Engineer-Associate pursue the area that interests you most, A library allows you to store elements, such as text frames, images, or empty frames.

Data-Engineer-Associate - Updated AWS Certified Data Engineer - Associate (DEA-C01) Valid Exam Tutorial

Three versions for your personal taste, We hope that more people can benefit from our Data-Engineer-Associate Study Guide, If you want to know more about Data-Engineer-Associate test dumps, please visit PrepAwayETE or consult our customer service.

Dear, are you tired of the study preparation for Data-Engineer-Associate exam test, PrepAwayETE will provide you with a full refund or another exam of your choice absolutely free within Data-Engineer-Associate Free Dump Download 90 days from the date of purchase if for any reason you do not pass your exam.

Report this page