Latest Real Data-Engineer-Associate Exam, Exam Data-Engineer-Associate Introduction

Tags: Latest Real Data-Engineer-Associate Exam, Exam Data-Engineer-Associate Introduction, Data-Engineer-Associate Exam Study Guide, Data-Engineer-Associate Exam Quizzes, Latest Data-Engineer-Associate Exam Fee

Due to busy routines, applicants of the AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) exam need real AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) exam questions. When they don't study with updated Amazon Data-Engineer-Associate practice test questions, they fail and lose money. If you want to save your resources, choose updated and actual AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate) exam questions of 2Pass4sure.

You may be get refused by so many Data-Engineer-Associate study dumps in thehe present market, facing so many similar Data-Engineer-Associate study guide , so how can you distinguish the best one among them? We will give you some suggestions, first of all, you need to see the pass rate, for all the efforts we do to the Data-Engineer-Associate Study Dumps is to pass . Our company guarantees the high pass rate. Second, you need to see the feedback of the customers, since the customers have used it, and they have the evaluation of the Data-Engineer-Associate study guide.

>> Latest Real Data-Engineer-Associate Exam <<

Exam Data-Engineer-Associate Introduction - Data-Engineer-Associate Exam Study Guide

In order to serve you better, we have a complete system to you if you buy Data-Engineer-Associate study materials from us. We offer you free demo for you to have a try before buying. If you are satisfied with the exam, you can just add them to cart, and pay for it. You will obtain the downloading link and password for Data-Engineer-Associate Study Materials within ten minutes, if you don’t, just contact us, we will solve the problem for you. After you buy, if you have some questions about the Data-Engineer-Associate exam braindumps after buying you can contact our service stuff, they have the professional knowledge and will give you reply.

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q33-Q38):

NEW QUESTION # 33
A company needs to partition the Amazon S3 storage that the company uses for a data lake. The partitioning will use a path of the S3 object keys in the following format: s3://bucket/prefix/year=2023/month=01/day=01.
A data engineer must ensure that the AWS Glue Data Catalog synchronizes with the S3 storage when the company adds new partitions to the bucket.
Which solution will meet these requirements with the LEAST latency?

A. Use code that writes data to Amazon S3 to invoke the Boto3 AWS Glue create partition API call.
B. Manually run the AWS Glue CreatePartition API twice each day.
C. Run the MSCK REPAIR TABLE command from the AWS Glue console.
D. Schedule an AWS Glue crawler to run every morning.

Answer: A

Explanation:
The best solution to ensure that the AWS Glue Data Catalog synchronizes with the S3 storage when the company adds new partitions to the bucket with the least latency is to use code that writes data to Amazon S3 to invoke the Boto3 AWS Glue create partition API call. This way, the Data Catalog is updated as soon as new data is written to S3, and the partition information is immediately available for querying by other services. The Boto3 AWS Glue create partition API call allows you to create a new partition in the Data Catalog by specifying the table name, the database name, and the partition values1. You can use this API call in your code that writes data to S3, such as a Python script or an AWS Glue ETL job, to create a partition for each new S3 object key that matches the partitioning scheme.
Option A is not the best solution, as scheduling an AWS Glue crawler to run every morning would introduce a significant latency between the time new data is written to S3 and the time the Data Catalog is updated. AWS Glue crawlers are processes that connect to a data store, progress through a prioritized list of classifiers to determine the schema for your data, and then create metadata tables in the Data Catalog2. Crawlers can be scheduled to run periodically, such as daily or hourly, but they cannot runcontinuously or in real-time.
Therefore, using a crawler to synchronize the Data Catalog with the S3 storage would not meet the requirement of the least latency.
Option B is not the best solution, as manually running the AWS Glue CreatePartition API twice each day would also introduce a significant latency between the time new data is written to S3 and the time the Data Catalog is updated. Moreover, manually running the API would require more operational overhead and human intervention than using code that writes data to S3 to invoke the API automatically.
Option D is not the best solution, as running the MSCK REPAIR TABLE command from the AWS Glue console would also introduce a significant latency between the time new data is written to S3 and the time the Data Catalog is updated. The MSCK REPAIR TABLE command is a SQL command that you can run in the AWS Glue console to add partitions to the Data Catalog based on the S3 object keys that match the partitioning scheme3. However, this command is not meant to be run frequently or in real-time, as it can take a long time to scan the entire S3 bucket and add the partitions. Therefore, using this command to synchronize the Data Catalog with the S3 storage would not meet the requirement of the least latency. References:
AWS Glue CreatePartition API
Populating the AWS Glue Data Catalog
MSCK REPAIR TABLE Command
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide

NEW QUESTION # 34
A data engineer must orchestrate a series of Amazon Athena queries that will run every day. Each query can run for more than 15 minutes.
Which combination of steps will meet these requirements MOST cost-effectively? (Choose two.)

A. Use an AWS Lambda function and the Athena Boto3 client start_query_execution API call to invoke the Athena queries programmatically.
B. Use an AWS Glue Python shell job and the Athena Boto3 client start_query_execution API call to invoke the Athena queries programmatically.
C. Use an AWS Glue Python shell script to run a sleep timer that checks every 5 minutes to determine whether the current Athena query has finished running successfully. Configure the Python shell script to invoke the next query when the current query has finished running.
D. Create an AWS Step Functions workflow and add two states. Add the first state before the Lambda function. Configure the second state as a Wait state to periodically check whether the Athena query has finished using the Athena Boto3 get_query_execution API call. Configure the workflow to invoke the next query when the current query has finished running.
E. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate the Athena queries in AWS Batch.

Answer: A,D

Explanation:
Option A and B are the correct answers because they meet the requirements most cost-effectively. Using an AWS Lambda function and the Athena Boto3 client start_query_execution API call to invoke the Athena queries programmatically is a simple and scalable way to orchestrate the queries. Creating an AWS Step Functions workflow and adding two states to check the query status and invoke the next query is a reliable and efficient way to handle the long-running queries.
Option C is incorrect because using an AWS Glue Python shell job to invoke the Athena queries programmatically is more expensive than using a Lambda function, as it requires provisioning and running a Glue job for each query.
Option D is incorrect because using an AWS Glue Python shell script to run a sleep timer that checks every 5 minutes to determine whether the current Athena query has finished running successfully is not a cost-effective or reliable way to orchestrate the queries, as it wastes resources and time.
Option E is incorrect because using Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate the Athena queries in AWS Batch is an overkill solution that introduces unnecessary complexity and cost, as it requires setting up and managing an Airflow environment and an AWS Batch compute environment.
References:
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 5: Data Orchestration, Section 5.2: AWS Lambda, Section 5.3: AWS Step Functions, Pages 125-135 Building Batch Data Analytics Solutions on AWS, Module 5: Data Orchestration, Lesson 5.1: AWS Lambda, Lesson 5.2: AWS Step Functions, Pages 1-15 AWS Documentation Overview, AWS Lambda Developer Guide, Working with AWS Lambda Functions, Configuring Function Triggers, Using AWS Lambda with Amazon Athena, Pages 1-4 AWS Documentation Overview, AWS Step Functions Developer Guide, Getting Started, Tutorial:
Create a Hello World Workflow, Pages 1-8

NEW QUESTION # 35
A company stores daily records of the financial performance of investment portfolios in .csv format in an Amazon S3 bucket. A data engineer uses AWS Glue crawlers to crawl the S3 data.
The data engineer must make the S3 data accessible daily in the AWS Glue Data Catalog.
Which solution will meet these requirements?

A. Create an IAM role that includes the AWSGlueServiceRole policy. Associate the role with the crawler.Specify the S3 bucket path of the source data as the crawler's data store. Allocate data processing units (DPUs) to run the crawler every day. Configure the output destination to a new path in the existing S3 bucket.
B. Create an IAM role that includes the AmazonS3FullAccess policy. Associate the role with the crawler.
Specify the S3 bucket path of the source data as the crawler's data store. Create a daily schedule to run the crawler. Configure the output destination to a new path in the existing S3 bucket.
C. Create an IAM role that includes the AWSGlueServiceRole policy. Associate the role with the crawler.
Specify the S3 bucket path of the source data as the crawler's data store. Create a daily schedule to run the crawler. Specify a database name for the output.
D. Create an IAM role that includes the AmazonS3FullAccess policy. Associate the role with the crawler.
Specify the S3 bucket path of the source data as the crawler's data store. Allocate data processing units (DPUs) to run the crawler every day. Specify a database name for the output.

Answer: C

Explanation:
To make the S3 data accessible daily in the AWS Glue Data Catalog, the data engineer needs to create a crawler that can crawl the S3 data and write the metadata to the Data Catalog. The crawler also needs to run on a daily schedule to keep the Data Catalog updated with the latest data. Therefore, the solution must include the following steps:
Create an IAM role that has the necessary permissions to access the S3 data and the Data Catalog. The AWSGlueServiceRole policy is a managed policy that grants these permissions1.
Associate the role with the crawler.
Specify the S3 bucket path of the source data as the crawler's data store. The crawler will scan the data and infer the schema and format2.
Create a daily schedule to run the crawler. The crawler will run at the specified time every day and update the Data Catalog with any changes in the data3.
Specify a database name for the output. The crawler will create or update a table in the Data Catalog under the specified database. The table will contain the metadata about the data in the S3 bucket, such as the location, schema, and classification.
Option B is the only solution that includes all these steps. Therefore, option B is the correct answer.
Option A is incorrect because it configures the output destination to a new path in the existing S3 bucket. This is unnecessary and may cause confusion, as the crawler does not write any data to the S3 bucket, only metadata to the Data Catalog.
Option C is incorrect because it allocates data processing units (DPUs) to run the crawler every day. This is also unnecessary, as DPUs are only used for AWS Glue ETL jobs, not crawlers.
Option D is incorrect because it combines the errors of option A and C. It configures the output destination to a new path in the existing S3 bucket and allocates DPUs to run the crawler every day, both of which are irrelevant for the crawler.
References:
1: AWS managed (predefined) policies for AWS Glue - AWS Glue
2: Data Catalog and crawlers in AWS Glue - AWS Glue
3: Scheduling an AWS Glue crawler - AWS Glue
[4]: Parameters set on Data Catalog tables by crawler - AWS Glue
[5]: AWS Glue pricing - Amazon Web Services (AWS)

NEW QUESTION # 36
A data engineer maintains custom Python scripts that perform a data formatting process that many AWS Lambda functions use. When the data engineer needs to modify the Python scripts, the data engineer must manually update all the Lambda functions.
The data engineer requires a less manual way to update the Lambda functions.
Which solution will meet this requirement?

A. Store a pointer to the custom Python scripts in environment variables in a shared Amazon S3 bucket.
B. Assign the same alias to each Lambda function. Call reach Lambda function by specifying the function's alias.
C. Store a pointer to the custom Python scripts in the execution context object in a shared Amazon S3 bucket.
D. Package the custom Python scripts into Lambda layers. Apply the Lambda layers to the Lambda functions.

Answer: D

Explanation:
Lambda layers are a way to share code and dependencies across multiple Lambda functions. By packaging the custom Python scripts into Lambda layers, the data engineer can update the scripts in one place and have them automatically applied to all the Lambda functions that use the layer. This reduces the manual effort and ensures consistency across the Lambda functions. The other options are either not feasible or not efficient.
Storing a pointer to the custom Python scripts in the execution context object or in environment variables would require the Lambda functions to download the scripts from Amazon S3 every time they are invoked, which would increase latency and cost. Assigning the same alias to each Lambda function would not help with updating the Python scripts, as the alias only points to a specific version of the Lambda function code.
References:
AWS Lambda layers
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 3: Data Ingestion and Transformation, Section 3.4: AWS Lambda

NEW QUESTION # 37
A company uses an on-premises Microsoft SQL Server database to store financial transaction data. The company migrates the transaction data from the on-premises database to AWS at the end of each month. The company has noticed that the cost to migrate data from the on-premises database to an Amazon RDS for SQL Server database has increased recently.
The company requires a cost-effective solution to migrate the data to AWS. The solution must cause minimal downtown for the applications that access the database.
Which AWS service should the company use to meet these requirements?

A. AWS Lambda
B. AWS Direct Connect
C. AWS DataSync
D. AWS Database Migration Service (AWS DMS)

Answer: D

Explanation:
AWS Database Migration Service (AWS DMS) is a cloud service that makes it possible to migrate relational databases, data warehouses, NoSQL databases, and other types of data stores to AWS quickly, securely, and with minimal downtime and zero data loss1. AWS DMS supports migration between 20-plus database and analytics engines, such as Microsoft SQL Server to Amazon RDS for SQL Server2. AWS DMS takes overmany of the difficult or tedious tasks involved in a migration project, such as capacity analysis, hardware and software procurement, installation and administration, testing and debugging, and ongoing replication and monitoring1. AWS DMS is a cost-effective solution, as you only pay for the compute resources and additional log storage used during the migration process2. AWS DMS is the best solution for the company to migrate the financial transaction data from the on-premises Microsoft SQL Server database to AWS, as it meets the requirements of minimal downtime, zero data loss, and low cost.
Option A is not the best solution, as AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers, but it does not provide any built-in features for database migration.
You would have to write your own code to extract, transform, and load the data from the source to the target, which would increase the operational overhead and complexity.
Option C is not the best solution, as AWS Direct Connect is a service that establishes a dedicated network connection from your premises to AWS, but it does not provide any built-in features for database migration.
You would still need to use another service or tool to perform the actual data transfer, which would increase the cost and complexity.
Option D is not the best solution, as AWS DataSync is a service that makes it easy to transfer data between on-premises storage systems and AWS storage services, such as Amazon S3, Amazon EFS, and Amazon FSx for Windows File Server, but it does not support Amazon RDS for SQL Server as a target. You would have to use another service or tool to migrate the data from Amazon S3 to Amazon RDS for SQL Server, which would increase the latency and complexity. References:
Database Migration - AWS Database Migration Service - AWS
What is AWS Database Migration Service?
AWS Database Migration Service Documentation
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide

NEW QUESTION # 38
......

Our experts update the Data-Engineer-Associate training materials every day and provide the latest update timely to you. If you have the doubts or the questions about our product and the purchase procedures you can contact our online customer service personnel at any time. We provide the discounts to the old client and you can have a free download and tryout of our Data-Engineer-Associate Test Question before your purchase. So there are many merits of our product. Read the introduction of the characteristics and the functions of our Data-Engineer-Associate practice test as follow carefully before you purchase our product.

Exam Data-Engineer-Associate Introduction: https://www.2pass4sure.com/AWS-Certified-Data-Engineer/Data-Engineer-Associate-actual-exam-braindumps.html

Amazon Latest Real Data-Engineer-Associate Exam So we can definitely say that cooperating with us is your best choice, Amazon Latest Real Data-Engineer-Associate Exam This passing rate is not what we say out of thin air, Choose the Data-Engineer-Associate test guide absolutely excellent quality and reasonable price, because the more times the user buys the Data-Engineer-Associate test guide, the more discounts he gets, Data-Engineer-Associate - AWS Certified Data Engineer - Associate (DEA-C01) is an essential exam for Amazon AWS Certified Data Engineer certification, sometimes it will become a lion in the way to obtain the certification.

So why dont firms offer traditional employees (https://www.2pass4sure.com/AWS-Certified-Data-Engineer/Data-Engineer-Associate-actual-exam-braindumps.html) the same level of flexibility they can offer contractor workers, The questions are designed to get you thinking and in the print edition) Data-Engineer-Associate Exam Study Guide drawing and writing with room on each spread to fill in the blanks and jot down ideas.

100% Pass 2024 Fantastic Amazon Latest Real Data-Engineer-Associate Exam

So we can definitely say that cooperating with us is your best choice, This passing rate is not what we say out of thin air, Choose the Data-Engineer-Associate test guide absolutely excellent quality and reasonable price, because the more times the user buys the Data-Engineer-Associate test guide, the more discounts he gets.

Data-Engineer-Associate - AWS Certified Data Engineer - Associate (DEA-C01) is an essential exam for Amazon AWS Certified Data Engineer certification, sometimes it will become a lion in the way to obtain the certification, I will show you the advantages of our AWS Certified Data Engineer - Associate (DEA-C01) pdf torrent.