AIP-C01 · Question #95
AIP-C01 Question #95: Real Exam Question with Answer & Explanation
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Question
A GenAI developer is building a Retrieval Augmented Generation (RAG)-based customer support application that uses Amazon Bedrock foundation models (FMs). The application needs to process 50 GB of historical customer conversations that are stored in an Amazon S3 bucket as JSON files. The application must use the processed data as its retrieval corpus. The application's data processing workflow must extract relevant data from customer support documents, remove customer personally identifiable information (PII), and generate embeddings for vector storage. The processing workflow must be cost-effective and must finish within 4 hours. Which solution will meet these requirements with the LEAST operational overhead?
Options
- AUse AWS Lambda and Amazon Comprehend to process files in parallel, remove PII, and call
- BCreate an AWS Glue ETL job to run PII detection scripts on the data. Use Amazon SageMaker
- CDeploy an Amazon EMR cluster that runs Apache Spark with user-defined functions (UDFs) that
- DImplement a data processing pipeline that uses AWS Step Functions to orchestrate a workload
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