P.S. Free & New Data-Engineer-Associate dumps are available on Google Drive shared by Braindumpsqa: https://drive.google.com/open?id=1ZjNicHIfEnyhN8-plcx5etHr-NJa7GAE
We at Braindumpsqa give you the techniques and resources to make sure you get the most out of your exam study. We provide preparation material for the AWS Certified Data Engineer - Associate (DEA-C01) exam that will guide you when you sit to study for it. Data-Engineer-Associate updated questions give you enough confidence to sit for the Amazon exam.If you take enough practice tests on Data-Engineer-Associate Practice Exam software by Braindumpsqa, you’ll be more comfortable when you walk in on Amazon exam day. So, go with Data-Engineer-Associate exam questions that are prepared under the supervision of industry experts to expand your knowledge base and successfully pass the certification exam on the first attempt.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Ingestion and Transformation | 34% | - Ingest data from various sources
- Transform and enrich data
|
| Topic 2: Data Store Management | 26% | - Manage data lifecycle and storage tiers - Optimize storage performance and cost - Design and implement data storage solutions
|
| Topic 3: Data Security and Governance | 18% | - Encrypt data at rest and in transit - Protect sensitive data - Implement access control and authentication
|
| Topic 4: Data Operations and Support | 22% | - Backup, restore, and disaster recovery - Automate operational tasks - Ensure reliability and scalability - Monitor and troubleshoot data pipelines
|
>> Minimum Data-Engineer-Associate Pass Score <<
As a hot test of Amazon certification, Data-Engineer-Associate practice exam become a difficult task for most candidates. So choosing right study materials is a guarantee success. Our website will be first time to provide you the latest Data-Engineer-Associate Exam Braindumps and test answers to let you be fully prepared to pass Data-Engineer-Associate actual test with 100% guaranteed.
NEW QUESTION # 247
A company has five offices in different AWS Regions. Each office has its own human resources (HR) department that uses a unique IAM role. The company stores employee records in a data lake that is based on Amazon S3 storage.
A data engineering team needs to limit access to the records. Each HR department should be able to access records for only employees who are within the HR department's Region.
Which combination of steps should the data engineering team take to meet this requirement with the LEAST operational overhead? (Choose two.)
Answer: C,D
Explanation:
AWS Lake Formation is a service that helps you build, secure, and manage data lakes on Amazon S3. You can use AWS Lake Formation to register the S3 path as a data lake location, and enable fine-grained access control to limit access to the records based on the HR department's Region. You can use data filters to specify which S3 prefixes or partitions each HR department can access, and grant permissions to the IAM roles of the HR departments accordingly. This solution will meet the requirement with the least operational overhead, as it simplifies the data lake management and security, and leverages the existing IAM roles of the HR departments12.
The other options are not optimal for the following reasons:
A. Use data filters for each Region to register the S3 paths as data locations. This option is not possible, as data filters are not used to register S3 paths as data locations, but to grant permissions to access specific S3 prefixes or partitions within a data location. Moreover, this option does not specify how to limit access to the records based on the HR department's Region.
C. Modify the IAM roles of the HR departments to add a data filter for each department's Region. This option is not possible, as data filters are not added to IAM roles, but to permissions granted by AWS Lake Formation. Moreover, this option does not specify how to register the S3 path as a data lake location, or how to enable fine-grained access control in AWS Lake Formation.
E. Create a separate S3 bucket for each Region. Configure an IAM policy to allow S3 access. Restrict access based on Region. This option is not recommended, as it would require more operational overhead to create and manage multiple S3 buckets, and to configure and maintain IAM policies for each HR department.
Moreover, this option does not leverage the benefits of AWS Lake Formation, such as data cataloging, data transformation, and data governance.
1: AWS Lake Formation
2: AWS Lake Formation Permissions
AWS Identity and Access Management
Amazon S3
NEW QUESTION # 248
A company uses AWS Glue jobs to implement several data pipelines. The pipelines are critical to the company.
The company needs to implement a monitoring mechanism that will alert stakeholders if the pipelines fail.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: A
Explanation:
Creating an EventBridge rule that triggers a Lambda function on AWS Glue job failure events and then sends notifications via Amazon SNS is the most direct and operationally efficient method:
"Practice Quiz 10: A data engineer must monitor the data pipeline... Which solution will meet these requirements?
A). Inspect the job run monitoring section of the AWS Glue console.answer: A."
- Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf Although this reference directly supports using AWS Glue's monitoring features via EventBridge, it implies that solutions like A-which directly use EventBridge failure events for automation-are more optimal and less complex than constructing custom logs and metrics.
NEW QUESTION # 249
A company uses Amazon Redshift as a data warehouse solution. One of the datasets that the company stores in Amazon Redshift contains data for a vendor.
Recently, the vendor asked the company to transfer the vendor ' s data into the vendor ' s Amazon S3 bucket once each week.
Which solution will meet this requirement?
Answer: C
Explanation:
The Redshift UNLOAD command is specifically designed to export query results to Amazon S3, and AWS Glue can orchestrate this as part of a scheduled job. This is the cleanest and most appropriate approach for recurring weekly data transfers:
"Use the Redshift UNLOAD command with AWS Glue to export data to Amazon S3. This pattern enables routine exports of selected data to external locations."
- Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf This avoids complexities of Redshift Spectrum or unsupported use of COPY commands in Lambda.
NEW QUESTION # 250
A company has a data lake in Amazon 53. The company uses AWS Glue to catalog data and AWS Glue Studio to implement data extract, transform, and load (ETL) pipelines.
The company needs to ensure that data quality issues are checked every time the pipelines run. A data engineer must enhance the existing pipelines to evaluate data quality rules based on predefined thresholds.
Which solution will meet these requirements with the LEAST implementation effort?
Answer: B
Explanation:
Problem Analysis:
The company uses AWS Glue for ETL pipelines and must enforce data quality checks during pipeline execution.
The goal is to implement quality checks with minimal implementation effort.
Key Considerations:
AWS Glue provides an Evaluate Data Quality transform that allows for defining quality checks directly in the pipeline.
DQDL (Data Quality Definition Language) simplifies the process by allowing declarative rule definitions.
Solution Analysis:
Option A: SQL Transform
SQL queries can implement rules but require manual effort for each rule and do not integrate natively with Glue.
Option B: Evaluate Data Quality Transform + DQDL
AWS Glue's built-in Evaluate Data Quality transform is designed for this use case.
Allows defining thresholds and rules in DQDL with minimal coding effort.
Option C: Custom Transform with PyDeequ
PyDeequ is a powerful library but adds unnecessary complexity compared to Glue's native features.
Option D: Custom Transform with Great Expectations
Similar to PyDeequ, Great Expectations adds operational complexity and external dependencies.
Final Recommendation:
Use the Evaluate Data Quality transform with DQDL to implement data quality rules in AWS Glue pipelines.
Reference:
AWS Glue Data Quality
DQDL Syntax and Examples
AWS Glue Studio Documentation
NEW QUESTION # 251
A company is using an AWS Transfer Family server to migrate data from an on-premises environment to AWS. Company policy mandates the use of TLS 1.2 or above to encrypt the data in transit.
Which solution will meet these requirements?
Answer: A
Explanation:
The AWS Transfer Family server's security policy can be updated to enforce TLS 1.2 or higher, ensuring compliance with company policy for encrypted data transfers.
AWS Transfer Family Security Policy:
AWS Transfer Family supports setting a minimum TLS version through its security policy configuration. This ensures that only connections using TLS 1.2 or above are allowed.
Reference:
Alternatives Considered:
A (Generate new SSH keys): SSH keys are unrelated to TLS and do not enforce encryption protocols like TLS 1.2.
B (Update security group rules): Security groups control IP-level access, not TLS versions.
D (Install SSL certificate): SSL certificates ensure secure connections, but the TLS version is controlled via the security policy.
AWS Transfer Family Documentation
NEW QUESTION # 252
......
Do not hesitate to seek our extraordinary Amazon Data-Engineer-Associate practice material to make a name in the field of Technology. Braindumpsqa has designed the Amazon Data-Engineer-Associate product in three formats. You will find their specifications below to comprehend them better.
Data-Engineer-Associate Valid Test Objectives: https://www.braindumpsqa.com/Data-Engineer-Associate_braindumps.html
DOWNLOAD the newest Braindumpsqa Data-Engineer-Associate PDF dumps from Cloud Storage for free: https://drive.google.com/open?id=1ZjNicHIfEnyhN8-plcx5etHr-NJa7GAE