DATA-ENGINEER-ASSOCIATE VALID TEST COST - VALID BRAINDUMPS DATA-ENGINEER-ASSOCIATE PDF

Data-Engineer-Associate Valid Test Cost - Valid Braindumps Data-Engineer-Associate Pdf

Data-Engineer-Associate Valid Test Cost - Valid Braindumps Data-Engineer-Associate Pdf

Blog Article

Tags: Data-Engineer-Associate Valid Test Cost, Valid Braindumps Data-Engineer-Associate Pdf, Data-Engineer-Associate Practice Test Engine, Braindump Data-Engineer-Associate Free, Data-Engineer-Associate Download Pdf

BTW, DOWNLOAD part of PDFBraindumps Data-Engineer-Associate dumps from Cloud Storage: https://drive.google.com/open?id=1blU0B6DCar-ljXt9yx_OaeSd4JXZbRmQ

Based on a return visit to students who purchased our Data-Engineer-Associate actual exam, we found that over 99% of the customers who purchased our Data-Engineer-Associate learning materials successfully passed the exam. Advertisements can be faked, but the scores of the students cannot be falsified. Data-Engineer-Associate Study Guide’s good results are derived from the intensive research and efforts of our experts. And we have become a popular brand in this field.

Many customers may be doubtful about our price. The truth is our price is relatively cheap among our peer. The inevitable trend is that knowledge is becoming worthy, and it explains why good Data-Engineer-Associate resources, services and data worth a good price. We always put our customers in the first place. Thus we offer discounts from time to time, and you can get 50% discount at the second time you buy our Data-Engineer-Associate question dumps after a year. Lower price with higher quality, that’s the reason why you should choose our Data-Engineer-Associate prep guide.

>> Data-Engineer-Associate Valid Test Cost <<

Valid Braindumps Amazon Data-Engineer-Associate Pdf, Data-Engineer-Associate Practice Test Engine

Our Data-Engineer-Associate study materials do not have the trouble that users can't read or learn because we try our best to present those complex and difficult test sites in a simple way. As long as you learn according to the plan of our Data-Engineer-Associate training materials, normal learning can make you grasp the knowledge points better. Whether you are an experienced top student or a student with poor grades, our Data-Engineer-Associate learning guide can help you get started quickly.

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q147-Q152):

NEW QUESTION # 147
A company created an extract, transform, and load (ETL) data pipeline in AWS Glue. A data engineer must crawl a table that is in Microsoft SQL Server. The data engineer needs to extract, transform, and load the output of the crawl to an Amazon S3 bucket. The data engineer also must orchestrate the data pipeline.
Which AWS service or feature will meet these requirements MOST cost-effectively?

  • A. AWS Glue workflows
  • B. Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
  • C. AWS Glue Studio
  • D. AWS Step Functions

Answer: A

Explanation:
AWS Glue workflows are a cost-effective way to orchestrate complex ETL jobs that involve multiple crawlers, jobs, and triggers. AWS Glue workflows allow you to visually monitor the progress and dependencies of your ETL tasks, and automatically handle errors and retries. AWS Glue workflows also integrate with other AWS services, such as Amazon S3, Amazon Redshift, and AWS Lambda, among others, enabling you to leverage these services for your data processing workflows. AWS Glue workflows are serverless, meaning you only pay for the resources you use, and you don't have to manage any infrastructure.
AWS Step Functions, AWS Glue Studio, and Amazon MWAA are also possible options for orchestrating ETL pipelines, but they have some drawbacks compared to AWS Glue workflows. AWS Step Functions is a serverless function orchestrator that can handle different types of data processing, such as real-time, batch, and stream processing. However, AWS Step Functions requires you to write code to define your state machines, which can be complex and error-prone. AWS Step Functions also charges you for every state transition, which can add up quickly for large-scale ETL pipelines.
AWS Glue Studio is a graphical interface that allows you to create and run AWS Glue ETL jobs without writing code. AWS Glue Studio simplifies the process of building, debugging, and monitoring your ETL jobs, and provides a range of pre-built transformations and connectors. However, AWS Glue Studio does not support workflows, meaning you cannot orchestrate multiple ETL jobs or crawlers with dependencies and triggers. AWS Glue Studio also does not support streaming data sources or targets, which limits its use cases for real-time data processing.
Amazon MWAA is a fully managed service that makes it easy to run open-source versions of Apache Airflow on AWS and build workflows to run your ETL jobs and data pipelines. Amazon MWAA provides a familiar and flexible environment for data engineers who are familiar with Apache Airflow, and integrates with a range of AWS services such as Amazon EMR, AWS Glue, and AWS Step Functions. However, Amazon MWAA is not serverless, meaning you have to provision and pay for the resources you need, regardless of your usage. Amazon MWAA also requires you to write code to define your DAGs, which can be challenging and time-consuming for complex ETL pipelines. References:
* AWS Glue Workflows
* AWS Step Functions
* AWS Glue Studio
* Amazon MWAA
* AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide


NEW QUESTION # 148
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 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.
  • B. 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.
  • C. 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.
  • D. 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.

Answer: A

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. Reference:
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 # 149
A company currently stores all of its data in Amazon S3 by using the S3 Standard storage class.
A data engineer examined data access patterns to identify trends. During the first 6 months, most data files are accessed several times each day. Between 6 months and 2 years, most data files are accessed once or twice each month. After 2 years, data files are accessed only once or twice each year.
The data engineer needs to use an S3 Lifecycle policy to develop new data storage rules. The new storage solution must continue to provide high availability.
Which solution will meet these requirements in the MOST cost-effective way?

  • A. Transition objects to S3 One Zone-Infrequent Access (S3 One Zone-IA) after 6 months. Transfer objects to S3 Glacier Deep Archive after 2 years.
  • B. Transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 6 months. Transfer objects to S3 Glacier Flexible Retrieval after 2 years.
  • C. Transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 6 months. Transfer objects to S3 Glacier Deep Archive after 2 years.
  • D. Transition objects to S3 One Zone-Infrequent Access (S3 One Zone-IA) after 6 months. Transfer objects to S3 Glacier Flexible Retrieval after 2 years.

Answer: C

Explanation:
To achieve the most cost-effective storage solution, the data engineer needs to use an S3 Lifecycle policy that transitions objects to lower-cost storage classes based on their access patterns, and deletes them when they are no longer needed. The storage classes should also provide high availability, which means they should be resilient to the loss of data in a single Availability Zone1. Therefore, the solution must include the following steps:
Transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 6 months. S3 Standard-IA is designed for data that is accessed less frequently, but requires rapid access when needed. It offers the same high durability, throughput, and low latency as S3 Standard, but with a lower storage cost and a retrieval fee2. Therefore, it is suitablefor data files that are accessed once or twice each month. S3 Standard-IA also provides high availability, as it stores data redundantly across multiple Availability Zones1.
Transfer objects to S3 Glacier Deep Archive after 2 years. S3 Glacier Deep Archive is the lowest-cost storage class that offers secure and durable storage for data that is rarely accessed and can tolerate a
12-hour retrieval time. It is ideal for long-term archiving and digital preservation3. Therefore, it is suitable for data files that are accessed only once or twice each year. S3 Glacier Deep Archive also provides high availability, as it stores data across at least three geographically dispersed Availability Zones1.
Delete objects when they are no longer needed. The data engineer can specify an expiration action in the S3 Lifecycle policy to delete objects after a certain period of time. This will reduce the storage cost and comply with any data retention policies.
Option C is the only solution that includes all these steps. Therefore, option C is the correct answer.
Option A is incorrect because it transitions objects to S3 One Zone-Infrequent Access (S3 One Zone-IA) after
6 months. S3 One Zone-IA is similar to S3 Standard-IA, but it stores data in a single Availability Zone. This means it has a lower availability and durability than S3 Standard-IA, and it is not resilient to the loss of data in a single Availability Zone1. Therefore, it does not provide high availability as required.
Option B is incorrect because it transfers objects to S3 Glacier Flexible Retrieval after 2 years. S3 Glacier Flexible Retrieval is a storage class that offers secure and durable storage for data that is accessed infrequently and can tolerate a retrieval time of minutes to hours. It is more expensive than S3 Glacier Deep Archive, and it is not suitable for data that is accessed only once or twice each year3. Therefore, it is not the most cost-effective option.
Option D is incorrect because it combines the errors of option A and B. It transitions objects to S3 One Zone-IA after 6 months, which does not provide high availability, and it transfers objects to S3 Glacier Flexible Retrieval after 2 years, which is not the most cost-effective option.
References:
1: Amazon S3 storage classes - Amazon Simple Storage Service
2: Amazon S3 Standard-Infrequent Access (S3 Standard-IA) - Amazon Simple Storage Service
3: Amazon S3 Glacier and S3 Glacier Deep Archive - Amazon Simple Storage Service
[4]: Expiring objects - Amazon Simple Storage Service
[5]: Managing your storage lifecycle - Amazon Simple Storage Service
[6]: Examples of S3 Lifecycle configuration - Amazon Simple Storage Service
[7]: Amazon S3 Lifecycle further optimizes storage cost savings with new features - What's New with AWS


NEW QUESTION # 150
A company is building a data stream processing application. The application runs in an Amazon Elastic Kubernetes Service (Amazon EKS) cluster. The application stores processed data in an Amazon DynamoDB table.
The company needs the application containers in the EKS cluster to have secure access to the DynamoDB table. The company does not want to embed AWS credentials in the containers.
Which solution will meet these requirements?

  • A. Create an IAM user that has an access key to access the DynamoDB table. Use environment variables in the EKS containers to store the IAM user access key data.
  • B. Store the AWS credentials in an Amazon S3 bucket. Grant the EKS containers access to the S3 bucket to retrieve the credentials.
  • C. Attach an IAM role to the EKS worker nodes. Grant the IAM role access to DynamoDB. Use the IAM role to set up IAM roles service accounts (IRSA) functionality.
  • D. Create an IAM user that has an access key to access the DynamoDB table. Use Kubernetes secrets that are mounted in a volume of the EKS cluster nodes to store the user access key data.

Answer: C

Explanation:
In this scenario, the company is using Amazon Elastic Kubernetes Service (EKS) and wants secure access to DynamoDB without embedding credentials inside the application containers. The best practice is to use IAM roles for service accounts (IRSA), which allows assigning IAM roles to Kubernetes service accounts. This lets the EKS pods assume specific IAM roles securely, without the need to store credentials in containers.
IAM Roles for Service Accounts (IRSA):
With IRSA, each pod in the EKS cluster can assume an IAM role that grants access to DynamoDB without needing to manage long-term credentials. The IAM role can be attached to the service account associated with the pod.
This ensures least privilege access, improving security by preventing credentials from being embedded in the containers.
Reference:
Alternatives Considered:
A (Storing AWS credentials in S3): Storing AWS credentials in S3 and retrieving them introduces security risks and violates the principle of not embedding credentials.
C (IAM user access keys in environment variables): This also embeds credentials, which is not recommended.
D (Kubernetes secrets): Storing user access keys as secrets is an option, but it still involves handling long-term credentials manually, which is less secure than using IRSA.
IAM Best Practices for Amazon EKS
Secure Access to DynamoDB from EKS


NEW QUESTION # 151
A company receives test results from testing facilities that are located around the world. The company stores the test results in millions of 1 KB JSON files in an Amazon S3 bucket. A data engineer needs to process the files, convert them into Apache Parquet format, and load them into Amazon Redshift tables. The data engineer uses AWS Glue to process the files, AWS Step Functions to orchestrate the processes, and Amazon EventBridge to schedule jobs.
The company recently added more testing facilities. The time required to process files is increasing. The data engineer must reduce the data processing time.
Which solution will MOST reduce the data processing time?

  • A. Use the AWS Glue dynamic frame file-grouping option to ingest the raw input files. Process the files. Load the files into the Amazon Redshift tables.
  • B. Use the Amazon Redshift COPY command to move the raw input files from Amazon S3 directly into the Amazon Redshift tables. Process the files in Amazon Redshift.
  • C. Use Amazon EMR instead of AWS Glue to group the raw input files. Process the files in Amazon EMR. Load the files into the Amazon Redshift tables.
  • D. Use AWS Lambda to group the raw input files into larger files. Write the larger files back to Amazon S3. Use AWS Glue to process the files. Load the files into the Amazon Redshift tables.

Answer: A

Explanation:
Problem Analysis:
Millions of 1 KB JSON files in S3 are being processed and converted to Apache Parquet format using AWS Glue.
Processing time is increasing due to the additional testing facilities.
The goal is to reduce processing time while using the existing AWS Glue framework.
Key Considerations:
AWS Glue offers the dynamic frame file-grouping feature, which consolidates small files into larger, more efficient datasets during processing.
Grouping smaller files reduces overhead and speeds up processing.
Solution Analysis:
Option A: Lambda for File Grouping
Using Lambda to group files would add complexity and operational overhead. Glue already offers built-in grouping functionality.
Option B: AWS Glue Dynamic Frame File-Grouping
This option directly addresses the issue by grouping small files during Glue job execution.
Minimizes data processing time with no extra overhead.
Option C: Redshift COPY Command
COPY directly loads raw files but is not designed for pre-processing (conversion to Parquet).
Option D: Amazon EMR
While EMR is powerful, replacing Glue with EMR increases operational complexity.
Final Recommendation:
Use AWS Glue dynamic frame file-grouping for optimized data ingestion and processing.
Reference:
AWS Glue Dynamic Frames
Optimizing Glue Performance


NEW QUESTION # 152
......

With the increasing marketization, the product experience marketing has been praised by the consumer market and the industry. Attract users interested in product marketing to know just the first step, the most important is to be designed to allow the user to try before buying the AWS Certified Data Engineer - Associate (DEA-C01) study training dumps, so we provide free pre-sale experience to help users to better understand our products. The user only needs to submit his E-mail address and apply for free trial online, and our system will soon send free demonstration research materials of Data-Engineer-Associate Latest Questions to download. If the user is still unsure which is best for him, consider applying for a free trial of several different types of test materials. It is believed that through comparative analysis, users will be able to choose the most satisfactory Data-Engineer-Associate test guide.

Valid Braindumps Data-Engineer-Associate Pdf: https://www.pdfbraindumps.com/Data-Engineer-Associate_valid-braindumps.html

Amazon with best AWS Certified Data Engineer - Associate (DEA-C01) study material help customers pass the AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate test, In order to provide the most effective Data-Engineer-Associate exam materials which cover all of the current events for our customers, a group of experts in our company always keep an close eye on the changes of the Data-Engineer-Associate exam even the smallest one, and then will compile all of the new key points as well as the latest types of exam questions into the new version of our Data-Engineer-Associate practice test, and you can get the latest version of our study materials for free during the whole year, Amazon Data-Engineer-Associate Valid Test Cost timing is everything.

Richard Adhikari, Development Process Is a Mixed-Bag Effort, Why would anyone want to turn off those cool thumbnail pictures, Amazon with best AWS Certified Data Engineer - Associate (DEA-C01) study material help customers pass the AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate test.

Data-Engineer-Associate Valid Test Cost Latest Questions Pool Only at PDFBraindumps

In order to provide the most effective Data-Engineer-Associate exam materials which cover all of the current events for our customers, a group of experts in our company always keep an close eye on the changes of the Data-Engineer-Associate exam even the smallest one, and then will compile all of the new key points as well as the latest types of exam questions into the new version of our Data-Engineer-Associate practice test, and you can get the latest version of our study materials for free during the whole year.

timing is everything, It is really tired, It's time to expand your knowledge and skills if you're committed to pass the Amazon Data-Engineer-Associate exam and get the certification badge to advance your profession.

What's more, part of that PDFBraindumps Data-Engineer-Associate dumps now are free: https://drive.google.com/open?id=1blU0B6DCar-ljXt9yx_OaeSd4JXZbRmQ

Report this page