Examcollection Data-Engineer-Associate Questions Answers, Exam Data-Engineer-Associate Online

P.S. Free & New Data-Engineer-Associate dumps are available on Google Drive shared by Itcerttest: https://drive.google.com/open?id=13iuihX-jj1ZEHbPGx1prr2SmKnX_E6XG

The language of our Data-Engineer-Associate study materials is simple. The learners may come from many social positions and their abilities to master our Data-Engineer-Associate study materials are varied. Based on this consideration we apply the most simple and easy-to-be-understood language to help the learners no matter he or she is the students or the in-service staff, the novice or the experienced employee which have worked for many years. Data-Engineer-Associate Study Material use the simple language to explain the answers and detailed knowledge points and the concise words to show the complicated information about the Data-Engineer-Associate study material.

Our passing rate is high so that you have little probability to fail in the exam because the Data-Engineer-Associate guide torrent is of high quality. But if you fail in exam unfortunately we will refund you in full immediately at one time and the procedures are simple and fast. If you have any questions about AWS Certified Data Engineer - Associate (DEA-C01) test torrent or there are any problems existing in the process of the refund you can contact us by mails or contact our online customer service personnel and we will reply and solve your doubts or questions promptly. We guarantee to you that we provide the best Data-Engineer-Associate study torrent to you and you can pass the exam with high possibility and also guarantee to you that if you fail in the exam unfortunately we will provide the fast and simple refund procedures.

>> Examcollection Data-Engineer-Associate Questions Answers <<

Exam Data-Engineer-Associate Online & Flexible Data-Engineer-Associate Testing Engine

Just like the old saying goes, motivation is what gets you started, and habit is what keeps you going. A good habit, especially a good study habit, will have an inestimable effect in help you gain the success. The Data-Engineer-Associate exam prep from our company will offer the help for you to develop your good study habits. If you buy and use our study materials, you will cultivate a good habit in study. More importantly, the good habits will help you find the scientific prop learning methods and promote you study efficiency, and then it will be conducive to helping you pass the Data-Engineer-Associate Exam in a short time. So hurry to buy the Data-Engineer-Associate test guide from our company, you will benefit a lot from it.

Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q112-Q117):

NEW QUESTION # 112
A company is planning to migrate on-premises Apache Hadoop clusters to Amazon EMR. The company also needs to migrate a data catalog into a persistent storage solution.
The company currently stores the data catalog in an on-premises Apache Hive metastore on the Hadoop clusters. The company requires a serverless solution to migrate the data catalog.
Which solution will meet these requirements MOST cost-effectively?

A. Use AWS Database Migration Service (AWS DMS) to migrate the Hive metastore into Amazon S3. Configure AWS Glue Data Catalog to scan Amazon S3 to produce the data catalog.
B. Configure a Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use AWS Glue Data Catalog to store the company's data catalog as an external data catalog.
C. Configure a new Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use the new metastore as the company's data catalog.
D. Configure an external Hive metastore in Amazon EMR. Migrate the existing on-premises Hive metastore into Amazon EMR. Use Amazon Aurora MySQL to store the company's data catalog.

Answer: A

Explanation:
AWS Database Migration Service (AWS DMS) is a service that helps you migrate databases to AWS quickly and securely. You can use AWS DMS to migrate the Hive metastore from the on-premises Hadoop clusters into Amazon S3, which is a highly scalable, durable, and cost-effective object storage service. AWS Glue Data Catalog is a serverless, managed service that acts as a central metadata repository for your data assets. You can use AWS Glue Data Catalog to scan the Amazon S3 bucket that contains the migrated Hive metastore and create a data catalog that is compatible with Apache Hive and other AWS services. This solution meets the requirements of migrating the data catalog into a persistent storage solution and using a serverless solution. This solution is also the most cost-effective, as it does not incur any additional charges for running Amazon EMR or Amazon Aurora MySQL clusters. The other options are either not feasible or not optimal. Configuring a Hive metastore in Amazon EMR (option B) or an external Hive metastore in Amazon EMR (option C) would require running and maintaining Amazon EMR clusters, which would incur additional costs and complexity. Using Amazon Aurora MySQL to store the company's data catalog (option C) would also incur additional costs and complexity, as well as introduce compatibility issues with Apache Hive. Configuring a new Hive metastore in Amazon EMR (option D) would not migrate the existing data catalog, but create a new one, which would result in data loss and inconsistency. Reference:
Using AWS Database Migration Service
Populating the AWS Glue Data Catalog
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 4: Data Analysis and Visualization, Section 4.2: AWS Glue Data Catalog

NEW QUESTION # 113
A company needs a solution to manage costs for an existing Amazon DynamoDB table. The company also needs to control the size of the table. The solution must not disrupt any ongoing read or write operations. The company wants to use a solution that automatically deletes data from the table after 1 month.
Which solution will meet these requirements with the LEAST ongoing maintenance?

A. Use an AWS Lambda function to periodically scan the DynamoDB table for data that is older than 1 month. Configure the Lambda function to delete old data.
B. Configure a scheduled Amazon EventBridge rule to invoke an AWS Lambda function to check for data that is older than 1 month. Configure the Lambda function to delete old data.
C. Configure a stream on the DynamoDB table to invoke an AWS Lambda function. Configure the Lambda function to delete data in the table that is older than 1 month.
D. Use the DynamoDB TTL feature to automatically expire data based on timestamps.

Answer: D

Explanation:
The requirement is to manage the size of an Amazon DynamoDB table by automatically deleting data older than 1 month without disrupting ongoing read or write operations. The simplest and most maintenance-free solution is to use DynamoDB Time-to-Live (TTL).
Option A: Use the DynamoDB TTL feature to automatically expire data based on timestamps.
DynamoDB TTL allows you to specify an attribute (e.g., a timestamp) that defines when items in the table should expire. After the expiration time, DynamoDB automatically deletes the items, freeing up storage space and keeping the table size under control without manual intervention or disruptions to ongoing operations.
Other options involve higher maintenance and manual scheduling or scanning operations, which increase complexity unnecessarily compared to the native TTL feature.
Reference:
DynamoDB Time-to-Live (TTL)

NEW QUESTION # 114
A data engineer runs Amazon Athena queries on data that is in an Amazon S3 bucket. The Athena queries use AWS Glue Data Catalog as a metadata table.
The data engineer notices that the Athena query plans are experiencing a performance bottleneck. The data engineer determines that the cause of the performance bottleneck is the large number of partitions that are in the S3 bucket. The data engineer must resolve the performance bottleneck and reduce Athena query planning time.
Which solutions will meet these requirements? (Choose two.)

A. Transform the data that is in the S3 bucket to Apache Parquet format.
B. Use Athena partition projection based on the S3 bucket prefix.
C. Create an AWS Glue partition index. Enable partition filtering.
D. Bucketthe data based on a column thatthe data have in common in a WHERE clause of the user query
E. Use the Amazon EMR S3DistCP utility to combine smaller objects in the S3 bucket into larger objects.

Answer: B,C

Explanation:
The best solutions to resolve the performance bottleneck and reduce Athena query planning time are to create an AWS Glue partition index and enable partition filtering, and to use Athena partition projection based on the S3 bucket prefix.
AWS Glue partition indexes are a feature that allows you to speed up query processing of highly partitioned tables cataloged in AWS Glue Data Catalog. Partition indexes are available for queries in Amazon EMR, Amazon Redshift Spectrum, and AWS Glue ETL jobs. Partition indexes are sublists of partition keys defined in the table. When you create a partition index, you specify a list of partition keys that already exist on a given table. AWS Glue then creates an index for the specified keys and stores it in the Data Catalog. When you run a query that filters on the partition keys, AWS Glue uses the partition index to quickly identify the relevant partitions without scanning the entiretable metadata. This reduces the query planning time and improves the query performance1.
Athena partition projection is a feature that allows you to speed up query processing of highly partitioned tables and automate partition management. In partition projection, Athena calculates partition values and locations using the table properties that you configure directly on your table in AWS Glue. The table properties allow Athena to 'project', or determine, the necessary partition information instead of having to do a more time-consuming metadata lookup in the AWS Glue Data Catalog. Because in-memory operations are often faster than remote operations, partition projection can reduce the runtime of queries against highly partitioned tables. Partition projection also automates partition management because it removes the need to manually create partitions in Athena, AWS Glue, or your external Hive metastore2.
Option B is not the best solution, as bucketing the data based on a column that the data have in common in a WHERE clause of the user query would not reduce the query planning time. Bucketing is a technique that divides data into buckets based on a hash function applied to a column. Bucketing can improve the performance of join queries by reducing the amount of data that needs to be shuffled between nodes. However, bucketing does not affect the partition metadata retrieval, which is the main cause of the performance bottleneck in this scenario3.
Option D is not the best solution, as transforming the data that is in the S3 bucket to Apache Parquet format would not reduce the query planning time. Apache Parquet is a columnar storage format that can improve the performance of analytical queries by reducing the amount of data that needs to be scanned and providing efficient compression and encoding schemes. However, Parquet does not affect the partition metadata retrieval, which is the main cause of the performance bottleneck in this scenario4.
Option E is not the best solution, as using the Amazon EMR S3DistCP utility to combine smaller objects in the S3 bucket into larger objects would not reduce the query planning time. S3DistCP is a tool that can copy large amounts of data between Amazon S3 buckets or from HDFS to Amazon S3. S3DistCP can also aggregate smaller files into larger files to improve the performance of sequential access. However, S3DistCP does not affect the partition metadata retrieval, which is the main cause of the performance bottleneck in this scenario5. References:
Improve query performance using AWS Glue partition indexes
Partition projection with Amazon Athena
Bucketing vs Partitioning
Columnar Storage Formats
S3DistCp
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide

NEW QUESTION # 115
A company extracts approximately 1 TB of data every day from data sources such as SAP HANA, Microsoft SQL Server, MongoDB, Apache Kafka, and Amazon DynamoDB. Some of the data sources have undefined data schemas or data schemas that change.
A data engineer must implement a solution that can detect the schema for these data sources. The solution must extract, transform, and load the data to an Amazon S3 bucket. The company has a service level agreement (SLA) to load the data into the S3 bucket within 15 minutes of data creation.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use Amazon EMR to detect the schema and to extract, transform, and load the data into the S3 bucket. Create a pipeline in Apache Spark.
B. Create a stored procedure in Amazon Redshift to detect the schema and to extract, transform, and load the data into a Redshift Spectrum table. Access the table from Amazon S3.
C. Create a PvSpark proqram in AWS Lambda to extract, transform, and load the data into the S3 bucket.
D. Use AWS Glue to detect the schema and to extract, transform, and load the data into the S3 bucket. Create a pipeline in Apache Spark.

Answer: D

Explanation:
AWS Glue is a fully managed service that provides a serverless data integration platform. It can automatically discover and categorize data from various sources, including SAP HANA, Microsoft SQL Server, MongoDB, Apache Kafka, and Amazon DynamoDB. It can also infer the schema of the data and store it in the AWS Glue Data Catalog, which is a central metadata repository. AWS Glue can then use the schema information to generate and run Apache Spark code to extract, transform, and load the data into an Amazon S3 bucket. AWS Glue can also monitor and optimize the performance and cost of the data pipeline, and handle any schema changes that may occur in the source data. AWS Glue can meet the SLA of loading the data into the S3 bucket within 15 minutes of data creation, as it can trigger the data pipeline based on events, schedules, or on-demand. AWS Glue has the least operational overhead among the options, as it does not require provisioning, configuring, or managing any servers or clusters. It also handles scaling, patching, and security automatically. Reference:
AWS Glue
[AWS Glue Data Catalog]
[AWS Glue Developer Guide]
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide

NEW QUESTION # 116
A data engineer needs to onboard a new data producer into AWS. The data producer needs to migrate data products to AWS.
The data producer maintains many data pipelines that support a business application. Each pipeline must have service accounts and their corresponding credentials. The data engineer must establish a secure connection from the data producer's on-premises data center to AWS. The data engineer must not use the public internet to transfer data from an on-premises data center to AWS.
Which solution will meet these requirements?

A. Create an AWS Direct Connect connection to the on-premises data center. Store the application keys in AWS Secrets Manager. Create Amazon S3 buckets that contain resigned URLS that have one-day expiration dates.
B. Create an AWS Direct Connect connection to the on-premises data center. Store the service account credentials in AWS Secrets manager.
C. Instruct the new data producer to create Amazon Machine Images (AMIs) on Amazon Elastic Container Service (Amazon ECS) to store the code base of the application. Create security groups in a public subnet that allow connections only to the on-premises data center.
D. Create a security group in a public subnet. Configure the security group to allow only connections from the CIDR blocks that correspond to the data producer. Create Amazon S3 buckets than contain presigned URLS that have one-day expiration dates.

Answer: B

Explanation:
For secure migration of data from an on-premises data center to AWS without using the public internet, AWS Direct Connect is the most secure and reliable method. Using Secrets Manager to store service account credentials ensures that the credentials are managed securely with automatic rotation.
AWS Direct Connect:
Direct Connect establishes a dedicated, private connection between the on-premises data center and AWS, avoiding the public internet. This is ideal for secure, high-speed data transfers.
Reference:
AWS Secrets Manager:
Secrets Manager securely stores and rotates service account credentials, reducing operational overhead while ensuring security.
Alternatives Considered:
A (ECS with security groups): This does not address the need for a secure, private connection from the on-premises data center.
C (Public subnet with presigned URLs): This involves using the public internet, which does not meet the requirement.
D (Direct Connect with presigned URLs): While Direct Connect is correct, presigned URLs with short expiration dates are unnecessary for this use case.
AWS Direct Connect Documentation
AWS Secrets Manager Documentation

NEW QUESTION # 117
......

Our company has occupied large market shares because of our consistent renovating. We have built a powerful research center and owned a strong team. Up to now, we have got a lot of patents about our Amazon study materials. On the one hand, our company has benefited a lot from renovation. Customers are more likely to choose our Data-Engineer-Associate Materials. On the other hand, the money we have invested is meaningful, which helps to renovate new learning style of the exam. So it will be very convenient for you to buy our product and it will do a lot of good to you.

Exam Data-Engineer-Associate Online: https://www.itcerttest.com/Data-Engineer-Associate_braindumps.html

Whereas, the web-based Amazon Data-Engineer-Associate practice test works without installation on all operating systems, Itcerttest is an excellent supplier and professional institution on Data-Engineer-Associate certification since 2005, The AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate exam questions are the real Data-Engineer-Associate Exam Questions that will surely repeat in the upcoming Data-Engineer-Associate exam and you can easily pass the challenging AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate certification exam, As we all know, it is difficult for you to prepare a Amazon Data-Engineer-Associate exam by yourself.

I always had a passion for photographing people, so I tried a model/portrait shoot and immediately felt in love with it, Data-Engineer-Associate latest practice material provides you the simplest way to clear exam with high efficiency.

Pass Guaranteed 2025 Amazon Unparalleled Data-Engineer-Associate: Examcollection AWS Certified Data Engineer - Associate (DEA-C01) Questions Answers

Whereas, the web-based Amazon Data-Engineer-Associate Practice Test works without installation on all operating systems, Itcerttest is an excellent supplier and professional institution on Data-Engineer-Associate certification since 2005.

The AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate exam questions are the real Data-Engineer-Associate Exam Questions that will surely repeat in the upcoming Data-Engineer-Associate exam and you can easily pass the challenging AWS Certified Data Engineer - Associate (DEA-C01) Data-Engineer-Associate certification exam.

As we all know, it is difficult for you to prepare a Amazon Data-Engineer-Associate exam by yourself, Our system is well designed and any person or any organization has no access to the information of the clients.

DOWNLOAD the newest Itcerttest Data-Engineer-Associate PDF dumps from Cloud Storage for free: https://drive.google.com/open?id=13iuihX-jj1ZEHbPGx1prr2SmKnX_E6XG