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| Section | Weight | Objectives |
|---|---|---|
| Data Security and Governance | 18% | - Apply governance and compliance best practices - Implement data security controls |
| Data Store Management | 26% | - Select appropriate data storage solutions - Optimize storage performance and cost |
| Data Ingestion and Transformation | 34% | - Ingest and transform data using AWS services - Build and manage data pipelines |
| Data Operations and Support | 22% | - Troubleshoot data workflow issues - Monitor and maintain data pipelines |
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NEW QUESTION # 10
A company needs to build an extract, transform, and load (ETL) pipeline that has separate stages for batch data ingestion, transformation, and storage. The pipeline must store the transformed data in an Amazon S3 bucket. Each stage must automatically retry failures. The pipeline must provide visibility into the success or failure of individual stages.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: B
Explanation:
Comprehensive and Detailed Explanation (150-250 words)
AWS Step Functions is a fully managed, serverless orchestration service designed to coordinate multiple AWS services into reliable workflows. Step Functions natively provide automatic retries, error handling, state-level visibility, and execution history, which directly satisfy the requirements for retry logic and monitoring individual pipeline stages.
In this solution, AWS Lambda functions are used for batch data ingestion, AWS Glue jobs handle transformation, and Amazon S3 is used for storage. Step Functions orchestrate these stages while maintaining clear separation of responsibilities. Each step can be configured with retry and catch policies, allowing the workflow to automatically recover from transient failures without manual intervention.
Chaining AWS Glue jobs alone does not provide detailed stage-level visibility or flexible retry control, and setting MaxRetries to 0 contradicts the retry requirement. EventBridge-based pipelines lack native workflow state tracking. Amazon MWAA introduces unnecessary operational overhead, including environment management and Airflow maintenance.
Therefore, using AWS Step Functions to orchestrate Lambda and Glue provides the most scalable, observable, and low-maintenance solution.
NEW QUESTION # 11
A marketing company uses Amazon S3 to store marketing dat
a. The company uses versioning in some buckets. The company runs several jobs to read and load data into the buckets.
To help cost-optimize its storage, the company wants to gather information about incomplete multipart uploads and outdated versions that are present in the S3 buckets.
Which solution will meet these requirements with the LEAST operational effort?
Answer: D
Explanation:
The company wants to gather information about incomplete multipart uploads and outdated versions in its Amazon S3 buckets to optimize storage costs.
Option B: Use Amazon S3 Inventory configurations reports to gather the information.
S3 Inventory provides reports that can list incomplete multipart uploads and versions of objects stored in S3. It offers an easy, automated way to track object metadata across buckets, including data necessary for cost optimization, without manual effort.
Options A (AWS CLI), C (S3 Storage Lens), and D (usage reports) either do not specifically gather the required information about incomplete uploads and outdated versions or require more manual intervention.
Reference:
Amazon S3 Inventory Documentation
NEW QUESTION # 12
A company runs a data pipeline that uses AWS Step Functions to orchestrate AWS Lambda functions and AWS Glue jobs. The Lambda functions and AWS Glue jobs require access to multiple Amazon RDS databases. The Lambda functions and AWS Glue jobs already have access to the VPC that hosts the RDS databases.
Which solution will meet these requirements in the MOST secure way?
Answer: C
Explanation:
AWS security best practices require avoiding long-term credentials and enforcing the principle of least privilege. Using IAM roles with role assumption is the most secure approach for granting temporary, scoped access to AWS resources.
In this solution, an IAM role is created with permissions to access the Amazon RDS databases. A second IAM role is assigned to the AWS Lambda functions and AWS Glue jobs with permission to assume the RDS- access role. This approach eliminates hard-coded credentials, enables automatic credential rotation through AWS Security Token Service (AWS STS), and provides clear separation of duties.
Using the root user or long-term access keys is explicitly discouraged by AWS. Creating IAM users for services violates best practices, as AWS services should use IAM roles, not users. Embedding credentials in JDBC connection strings exposes sensitive information and increases the risk of credential leakage.
Therefore, using IAM role assumption provides the strongest security posture, auditability, and compliance with AWS Well-Architected Framework guidance.
NEW QUESTION # 13
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?
Answer: D
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 # 14
A company receives call logs as Amazon S3 objects that contain sensitive customer information. The company must protect the S3 objects by using encryption. The company must also use encryption keys that only specific employees can access.
Which solution will meet these requirements with the LEAST effort?
Answer: C
Explanation:
Option C is the best solution to meet the requirements with the least effort because server-side encryption with AWS KMS keys (SSE-KMS) is a feature that allows you to encrypt data at rest in Amazon S3 using keys managed by AWS Key Management Service (AWS KMS). AWS KMS is a fully managed service that enables you to create and manage encryption keys for your AWS services and applications. AWS KMS also allows you to define granular access policies for your keys, such as who can use them to encrypt and decrypt data, and under what conditions. By using SSE-KMS, you canprotect your S3 objects by using encryption keys that only specific employees can access, without having to manage the encryption and decryption process yourself.
Option A is not a good solution because it involves using AWS CloudHSM, which is a service that provides hardware security modules (HSMs) in the AWS Cloud. AWS CloudHSM allows you to generate and use your own encryption keys on dedicated hardware that is compliant with various standards and regulations.
However, AWS CloudHSM is not a fully managed service and requires more effort to set up and maintain than AWS KMS. Moreover, AWS CloudHSM does not integrate with Amazon S3, so you have to configure the process that writes to S3 to make calls to CloudHSM to encrypt and decrypt the objects, which adds complexity and latency to the data protection process.
Option B is not a good solution because it involves using server-side encryption with customer-provided keys (SSE-C), which is a feature that allows you to encrypt data at rest in Amazon S3 using keys that you provide and manage yourself. SSE-C requires you to send your encryption key along with each request to upload or retrieve an object. However, SSE-C does not provide any mechanism to restrict access to the keys that encrypt the objects, so you have to implement your own key management and access control system, which adds more effort and risk to the data protection process.
Option D is not a good solution because it involves using server-side encryption with Amazon S3 managed keys (SSE-S3), which is a feature that allows you to encrypt data at rest in Amazon S3 using keys that are managed by Amazon S3. SSE-S3 automatically encrypts and decrypts your objects as they are uploaded and downloaded from S3. However, SSE-S3 does not allow you to control who can access the encryption keys or under what conditions. SSE-S3 uses a single encryption key for each S3 bucket, which is shared by all users who have access to the bucket. This means that you cannot restrict access to the keys that encrypt the objects by specific employees, which does not meet the requirements.
References:
AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide
Protecting Data Using Server-Side Encryption with AWS KMS-Managed Encryption Keys (SSE-KMS)
- Amazon Simple Storage Service
What is AWS Key Management Service? - AWS Key Management Service
What is AWS CloudHSM? - AWS CloudHSM
Protecting Data Using Server-Side Encryption with Customer-Provided Encryption Keys (SSE-C) - Amazon Simple Storage Service Protecting Data Using Server-Side Encryption with Amazon S3-Managed Encryption Keys (SSE-S3) - Amazon Simple Storage Service
NEW QUESTION # 15
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