SAP-C02 Question 80
Select 2A company is modernizing its on-premises data analytics platform by migrating to AWS. The current setup processes large volumes of batch data daily, requiring high throughput for storage and compute. Security is a top priority, and the company must ensure data encryption at rest and in transit. Additionally, the solution must be highly scalable to accommodate future growth. Which combination of AWS services can best meet these requirements?
- A
Amazon S3 with server-side encryption (SSE) for data storage and Amazon EMR for scalable compute processing
- B
Amazon RDS with Multi-AZ deployment for data storage and Amazon Lambda for processing
- C
Amazon Redshift with encryption enabled for data warehousing and AWS Glue for ETL processing
- D
Amazon EFS for data storage and AWS Batch for processing
- E
Amazon DynamoDB for data storage and Amazon Kinesis Data Analytics for real-time processing
Show answer and explanation
Correct answers: A, C
Explanation
The correct combination of services must address the requirements for scalable storage, high-throughput computing, and security. Amazon S3 with SSE and Amazon EMR provide a robust solution for batch data processing with encryption in place. Alternatively, Amazon Redshift with encryption and AWS Glue provide a highly scalable and secure solution for large-scale data analytics. Other options either lack scalability, are not optimized for batch processing, or cater to different use cases like real-time analytics or low-latency workloads.
- A. Correct.
Amazon S3 with server-side encryption (SSE) ensures data encryption at rest, while Amazon EMR provides scalable, high-throughput compute power for batch processing. This combination meets the requirements for scalability, security, and performance.
- B. Incorrect.
Amazon RDS is not designed for high-throughput batch processing or large-scale data analytics. Additionally, Lambda is better suited for event-driven architectures rather than large-scale batch data processing.
- C. Correct.
Amazon Redshift is a fully managed data warehouse service that supports encryption and is ideal for large-scale analytics. AWS Glue complements it by providing ETL capabilities to prepare data, addressing both scalability and security requirements.
- D. Incorrect.
Amazon EFS is suitable for shared file storage but is not optimized for high-throughput batch analytics. AWS Batch is used for managing batch jobs but does not inherently provide the necessary scalability for large-scale analytics.
- E. Incorrect.
Amazon DynamoDB is a NoSQL database designed for low-latency workloads, not batch processing. Kinesis Data Analytics is better suited for real-time streaming analytics rather than large-scale batch data processing.