DATA-ENGINEER-ASSOCIATE EXAM QUESTION, DATA-ENGINEER-ASSOCIATE HIGH PASSING SCORE

Data-Engineer-Associate Exam Question, Data-Engineer-Associate High Passing Score

Data-Engineer-Associate Exam Question, Data-Engineer-Associate High Passing Score

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Amazon AWS Certified Data Engineer - Associate (DEA-C01) Sample Questions (Q40-Q45):

NEW QUESTION # 40
A company uses Amazon RDS to store transactional data. The company runs an RDS DB instance in a private subnet. A developer wrote an AWS Lambda function with default settings to insert, update, or delete data in the DB instance.
The developer needs to give the Lambda function the ability to connect to the DB instance privately without using the public internet.
Which combination of steps will meet this requirement with the LEAST operational overhead? (Choose two.)

  • A. Update the security group of the DB instance to allow only Lambda function invocations on the database port.
  • B. Attach the same security group to the Lambda function and the DB instance. Include a self-referencing rule that allows access through the database port.
  • C. Configure the Lambda function to run in the same subnet that the DB instance uses.
  • D. Update the network ACL of the private subnet to include a self-referencing rule that allows access through the database port.
  • E. Turn on the public access setting for the DB instance.

Answer: B,C

Explanation:
To enable the Lambda function to connect to the RDS DB instance privately without using the public internet, the best combination of steps is to configure the Lambda function to run in the same subnet that the DB instance uses, and attach the same security group to the Lambda function and the DB instance. This way, the Lambda function and the DB instance can communicate within the same private network, and the security group can allow traffic between them on the database port. This solution has the least operational overhead, as it does not require any changes to the public access setting, the network ACL, or the security group of the DB instance.
The other options are not optimal for the following reasons:
A: Turn on the public access setting for the DB instance. This option is not recommended, as it would expose the DB instance to the public internet, which can compromise the security and privacy of the data. Moreover, this option would not enable the Lambda function to connect to the DB instance privately, as it would still require the Lambda function to use the public internet to access the DB instance.
B: Update the security group of the DB instance to allow only Lambda function invocations on the database port. This option is not sufficient, as it would only modify the inbound rules of the security group of the DB instance, but not the outbound rules of the security group of the Lambda function.
Moreover, this option would not enable the Lambda function to connect to the DB instance privately, as it would still require the Lambda function to use the public internet to access the DB instance.
E: Update the network ACL of the private subnet to include a self-referencing rule that allows access through the database port. This option is not necessary, as the network ACL of the private subnet already allows all traffic within the subnet by default. Moreover, this option would not enable the Lambda function to connect to the DB instance privately, as it would still require the Lambda function to use the public internet to access the DB instance.
References:
1: Connecting to an Amazon RDS DB instance
2: Configuring a Lambda function to access resources in a VPC
3: Working with security groups
4: Network ACLs


NEW QUESTION # 41
A company has a data processing pipeline that includes several dozen steps. The data processing pipeline needs to send alerts in real time when a step fails or succeeds. The data processing pipeline uses a combination of Amazon S3 buckets, AWS Lambda functions, and AWS Step Functions state machines.
A data engineer needs to create a solution to monitor the entire pipeline.
Which solution will meet these requirements?

  • A. Use AWS CloudTrail to send a message to an Amazon Simple Notification Service (Amazon SNS) topic that sends notifications when a state machine fails to run or succeeds to run.
  • B. Configure the AWS Lambda functions to store notifications in an Amazon S3 bucket when the state machines finish running. Enable S3 event notifications on the S3 bucket.
  • C. Configure an Amazon EventBridge rule to react when the execution status of a state machine changes.Configure the rule to send a message to an Amazon Simple Notification Service (Amazon SNS) topic that sends notifications.
  • D. Configure the Step Functions state machines to store notifications in an Amazon S3 bucket when the state machines finish running. Enable S3 event notifications on the S3 bucket.

Answer: C

Explanation:
AWS Step Functions natively emitsstate change eventstoAmazon EventBridge, which can trigger an Amazon SNS notification. This is the most direct and real-time way to alert on success/failure without relying on custom logging or polling.
"Step Functions automatically emits status changes that EventBridge can capture to trigger alerts or workflows. Use EventBridge to invoke an SNS topic for real-time alerts on job status."
-Ace the AWS Certified Data Engineer - Associate Certification - version 2 - apple.pdf This provides real-time alerting and the least operational overhead.


NEW QUESTION # 42
A company stores its processed data in an S3 bucket. The company has a strict data access policy. The company uses IAM roles to grant teams within the company different levels of access to the S3 bucket.
The company wants to receive notifications when a user violates the data access policy. Each notification must include the username of the user who violated the policy.
Which solution will meet these requirements?

  • A. Use Amazon S3 server access logs to monitor access to the bucket. Forward the access logs to an Amazon CloudWatch log group. Use metric filters on the log group to set up CloudWatch alarms.
  • B. Use AWS Config rules to detect violations of the data access policy. Set up compliance alarms.
  • C. Use Amazon CloudWatch metrics to gather object-level metrics. Set up CloudWatch alarms.
  • D. Use AWS CloudTrail to track object-level events for the S3 bucket. Forward events to Amazon CloudWatch to set up CloudWatch alarms.

Answer: D

Explanation:
The requirement is to detect violations of data access policies and receive notifications with the username of the violator. AWS CloudTrail can provideobject-level tracking for S3to capture detailed API actions on specific S3 objects, including the user who performed the action.
* AWS CloudTrail:
* CloudTrail can monitorAPI callsmade to an S3 bucket, including object-level API actions such as GetObject, PutObject, and DeleteObject. This will help detect access violations based on the API calls made by different users.
* CloudTrail logs include details such as theuser identity, which is essential for meeting the requirement of including the username in notifications.
* The CloudTrail logs can be forwarded toAmazon CloudWatchto trigger alarms based on certain access patterns (e.g., violations of specific policies).
Reference:Monitoring Amazon S3 Activity Using AWS CloudTrail
Amazon CloudWatch:
By forwarding CloudTrail logs to CloudWatch, you can set upalarmsthat are triggered when a specific condition is met, such as unauthorized access or policy violations. The alarm can include detailed information from the CloudTrail log, including the username.
Alternatives Considered:
A (AWS Config rules): While AWS Config can track resource configurations and compliance, it does not provide real-time, detailed tracking of object-level events like CloudTrail does.
B (CloudWatch metrics): CloudWatch does not gather object-level metrics for S3 directly. For this use case, CloudTrail provides better granularity.
D (S3 server access logs): S3 server access logs can monitor access, but they do not provide the real-time monitoring and alerting features that CloudTrail with CloudWatch alarms offer. They also do not include API- level granularity like CloudTrail.
References:
AWS CloudTrail Integration with S3
Amazon CloudWatch Alarms


NEW QUESTION # 43
A company has multiple applications that use datasets that are stored in an Amazon S3 bucket. The company has an ecommerce application that generates a dataset that contains personally identifiable information (PII).
The company has an internal analytics application that does not require access to the PII.
To comply with regulations, the company must not share PII unnecessarily. A data engineer needs to implement a solution that with redact PII dynamically, based on the needs of each application that accesses the dataset.
Which solution will meet the requirements with the LEAST operational overhead?

  • A. Create an S3 Object Lambda endpoint. Use the S3 Object Lambda endpoint to read data from the S3 bucket. Implement redaction logic within an S3 Object Lambda function to dynamically redact PII based on the needs of each application that accesses the data.
  • B. Create an API Gateway endpoint that has custom authorizers. Use the API Gateway endpoint to read data from the S3 bucket. Initiate a REST API call to dynamically redact PII based on the needs of each application that accesses the data.
  • C. Use AWS Glue to transform the data for each application. Create multiple copies of the dataset. Give each dataset copy the appropriate level of redaction for the needs of the application that accesses the copy.
  • D. Create an S3 bucket policy to limit the access each application has. Create multiple copies of the dataset. Give each dataset copy the appropriate level of redaction for the needs of the application that accesses the copy.

Answer: A

Explanation:
Option B is the best solution to meet the requirements with the least operational overhead because S3 Object Lambda is a feature that allows you to add your own code to process data retrieved from S3 before returning it to an application. S3 Object Lambda works with S3 GET requests and can modify both the object metadata and the object data. By using S3 Object Lambda, you can implement redaction logic within an S3 Object Lambda function to dynamically redact PII based on the needs of each application that accesses the data. This way, you can avoid creating and maintaining multiple copies of the dataset with different levels of redaction.
Option A is not a good solution because it involves creating and managing multiple copies of the dataset with different levels of redaction for each application. This option adds complexity and storage cost to the data protection process and requires additional resources and configuration. Moreover, S3 bucket policies cannot enforce fine-grained data access control at the row and column level, so they are not sufficient to redact PII.
Option C is not a good solution because it involves using AWS Glue to transform the data for each application. AWS Glue is a fully managed service that can extract, transform, and load (ETL) data from various sources to various destinations, including S3. AWS Glue can also convert data to different formats, such as Parquet, which is a columnar storage format that is optimized for analytics. However, in this scenario, using AWS Glue to redact PII is not the best option because it requires creating and maintaining multiple copies of the dataset with different levels of redaction for each application. This option also adds extra time and cost to the data protection process and requires additional resources and configuration.
Option D is not a good solution because it involves creating and configuring an API Gateway endpoint that has custom authorizers. API Gateway is a service that allows youto create, publish, maintain, monitor, and secure APIs at any scale. API Gateway can also integrate with other AWS services, such as Lambda, to provide custom logic for processing requests. However, in this scenario, using API Gateway to redact PII is not the best option because it requires writing and maintaining custom code and configuration for the API endpoint, the custom authorizers, and the REST API call. This option also adds complexity and latency to the data protection process and requires additional resources and configuration.
:
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide
Introducing Amazon S3 Object Lambda - Use Your Code to Process Data as It Is Being Retrieved from S3 Using Bucket Policies and User Policies - Amazon Simple Storage Service AWS Glue Documentation What is Amazon API Gateway? - Amazon API Gateway


NEW QUESTION # 44
A company wants to analyze sales records that the company stores in a MySQL database. The company wants to correlate the records with sales opportunities identified by Salesforce.
The company receives 2 GB erf sales records every day. The company has 100 GB of identified sales opportunities. A data engineer needs to develop a process that will analyze and correlate sales records and sales opportunities. The process must run once each night.
Which solution will meet these requirements with the LEAST operational overhead?

  • A. Use Amazon AppFlow to fetch sales opportunities from Salesforce. Use Amazon Kinesis Data Streams to fetch sales records from the MySQL database. Use Amazon Managed Service for Apache Flink to correlate the datasets. Use AWS Step Functions to orchestrate the process.
  • B. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to fetch both datasets. Use AWS Lambda functions to correlate the datasets. Use AWS Step Functions to orchestrate the process.
  • C. Use Amazon AppFlow to fetch sales opportunities from Salesforce. Use AWS Glue to fetch sales records from the MySQL database. Correlate the sales records with sales opportunities. Use AWS Step Functions to orchestrate the process.
  • D. Use Amazon AppFlow to fetch sales opportunities from Salesforce. Use AWS Glue to fetch sales records from the MySQL database. Correlate the sales records with the sales opportunities. Use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to orchestrate the process.

Answer: C

Explanation:
* Problem Analysis:
* The company processes2 GB of daily sales recordsand100 GB of Salesforce sales opportunities
.
* The goal is to analyze and correlate the two datasets withlow operational overhead.
* The process must runonce nightly.
* Key Considerations:
* Amazon AppFlowsimplifies data integration with Salesforce.
* AWS Gluecan extract data from MySQL and perform ETL operations.
* Step Functionscan orchestrate workflows with minimal manual intervention.
* Apache Airflow and Flink add complexity, which conflicts with the requirement for low operational overhead.
* Solution Analysis:
* Option A: MWAA + Lambda + Step Functions
* Requires custom Lambda code for dataset correlation, increasing development and operational complexity.
* Option B: AppFlow + Glue + MWAA
* MWAA adds orchestration overhead compared to the simpler Step Functions.
* Option C: AppFlow + Glue + Step Functions
* AppFlow fetches Salesforce data, Glue extracts MySQL data, and Step Functions orchestrate the entire process.
* Minimal setup and operational overhead, making it the best choice.
* Option D: AppFlow + Kinesis + Flink + Step Functions
* Using Kinesis and Flink for batch processing introduces unnecessary complexity.
* Final Recommendation:
* UseAmazon AppFlowto fetch Salesforce data,AWS Glueto process MySQL data, andStep Functionsfor orchestration.
:
Amazon AppFlow Overview
AWS Glue ETL Documentation
AWS Step Functions


NEW QUESTION # 45
......

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