SAP-C02 Design for New Solutions Practice Question
A healthcare company is designing a new system on AWS to store and analyze patient health records. The system must comply with HIPAA regulations. Data includes structured lab results and unstructured clinical notes. The company needs to run complex SQL queries on the structured data and perform natural language processing (NLP) on the unstructured data. The solution should be cost-effective and minimize administrative overhead. Which solution should a Solutions Architect recommend?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Store structured data in Amazon Redshift, store unstructured data in S3, and use Amazon Comprehend Medical for NLP.
Amazon Redshift is a fully managed, petabyte-scale data warehouse service that is ideal for running complex SQL queries on structured data, and it supports HIPAA compliance. Amazon Comprehend Medical is a HIPAA-eligible natural language processing (NLP) service specifically designed to extract medical information from unstructured clinical text. Storing unstructured data in Amazon S3 is cost-effective and scalable. This combination minimizes administrative overhead with managed services. Option A is incorrect because Amazon RDS for PostgreSQL is not optimized for complex analytics at scale and may require additional setup for performance. Option B is incorrect because Amazon Athena is best for ad-hoc queries and not ideal for frequent, complex SQL workloads; moreover, Amazon Textract is for document extraction (e.g., OCR), not NLP. Option C is incorrect because Amazon DynamoDB is a NoSQL database not suited for complex SQL queries, and Amazon SageMaker would require custom model building, increasing overhead compared to using a managed NLP service like Comprehend Medical.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Store structured data in Amazon RDS for PostgreSQL, store unstructured data in S3, and use AWS Glue to run NLP jobs.
Why it's wrong here
RDS is not optimized for large-scale analytics; Glue is for ETL, not NLP.
- ✗
Store all data in S3, use Amazon Athena for SQL queries and Amazon Textract for NLP.
Why it's wrong here
Athena is for ad-hoc queries, not frequent analytics; Textract is for document text extraction, not NLP.
- ✗
Store structured data in DynamoDB, store unstructured data in S3, use Amazon SageMaker to build custom NLP models.
Why it's wrong here
DynamoDB is not for complex queries; SageMaker requires ML expertise and overhead.
- ✓
Store structured data in Amazon Redshift, store unstructured data in S3, and use Amazon Comprehend Medical for NLP.
Why this is correct
Redshift is for analytics; Comprehend Medical is HIPAA-eligible and designed for medical NLP.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This SAP-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SAP-C02 exam.