AWS Certified Solutions Architect – ProfessionalDesign for New SolutionsHard
A financial institution is building a new data platform to ingest, process, and analyze vast amounts of financial transaction data for regulatory compliance and fraud detection. The data arrives continuously and must be processed in real-time, with results available for query within seconds. The solution needs to handle petabytes of data, support complex SQL queries, and integrate with existing business intelligence (BI) tools. Which AWS services should be used to design this platform?
- AAmazon Kinesis Data Streams, Amazon Kinesis Data Analytics, Amazon S3, Amazon Redshift
- BAWS Glue, Amazon SQS, Amazon EMR, Amazon QuickSight
- CAmazon Kinesis Data Streams, AWS Lambda, Amazon S3, Amazon Redshift
- DAmazon Kinesis Data Firehose, Amazon Kinesis Data Analytics, Amazon S3, Amazon Athena
Show answer & explanationAnswer & explanation
Correct answer: A. Amazon Kinesis Data Streams, Amazon Kinesis Data Analytics, Amazon S3, Amazon Redshift
Kinesis Data Streams ingests data in real-time. Kinesis Data Analytics processes it in real-time. S3 provides scalable, durable storage for raw and processed data. Redshift is a petabyte-scale data warehouse that supports complex SQL queries and BI tool integration, suitable for the analytical requirements.
Why the other options are wrong
- B. AWS Glue is for ETL, SQS for messaging, and EMR for big data processing, which are not optimized for the 'real-time' processing and 'results available for query within seconds' for complex SQL queries on petabytes of data as efficiently as the Kinesis-Redshift combination.
- C. While SQS and Lambda can process data, Kinesis Data Analytics is better suited for continuous real-time stream processing before landing data in S3 and Redshift for complex analytics.
- D. Athena is excellent for ad-hoc queries on S3 but might not offer the performance for 'complex SQL queries' on 'petabytes of data' with 'results available for query within seconds' as a dedicated data warehouse like Redshift.
Real-time Analytics Data Platform
An AWS architecture designed to ingest, process, and analyze high-volume, continuous data streams in real-time, enabling rapid querying and insights for business intelligence and compliance.
- Real-time data ingestion and processing.
- Petabyte-scale storage and analytics.
- Support for complex SQL queries and BI tools.
- Low-latency query results.
Memory trick: Kinesis streams into Redshift, like a river flowing into a vast, queryable ocean.