AWS Certified Data Engineer - Associate
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You are designing a data pipeline for a healthcare organization that needs to process and analyze patient data from various sources, including electronic health records (EHR) and medical imaging. The pipeline should be able to handle both structured and unstructured data. Which AWS services would you use to create this pipeline, and how would you configure them to meet the requirements?
A
Use Amazon S3 for data storage, AWS Glue for ETL processing, and Amazon Redshift for data warehousing. Configure Glue to process both structured and unstructured data, and store the processed data in Redshift for analysis.
B
Use Amazon S3 for data storage, AWS Lambda for serverless computing, and Amazon Elasticsearch for data analysis. Configure Lambda to process the patient data, and store the processed data in Elasticsearch for analysis.
C
Use Amazon S3 for data storage, AWS Step Functions for workflow management, and AWS Glue for ETL processing. Configure Step Functions to manage the workflow, Glue to process both structured and unstructured data, and store the processed data in S3 for further analysis.
D
Use Amazon S3 for data storage, AWS Data Pipeline for scheduling and workflow management, and AWS Glue for ETL processing. Configure Data Pipeline to schedule Glue jobs based on dependencies, and Glue to process both structured and unstructured data.