A prediction service produces 100 TB of prediction data daily. You must create a visualization of the daily precision-recall curve and provide a read-only view to the Business team. Which option requires the least amount of coding?

The correct option leverages Amazon EMR for efficient processing of 100 TB of data, saving the results to S3, which is a cost-effective and scalable storage solution. Amazon QuickSight can then easily ingest this processed data from S3 to create visualizations, including precision-recall curves, and share them as read-only dashboards with the Business team. This minimizes custom coding for visualization compared to direct S3 access. Running EMR and saving to S3 without QuickSight (first option) would require the Business team to have technical skills to interpret raw data, which is not ideal for a read-only view. Computing directly in QuickSight (second option) is not feasible for 100 TB of data, as QuickSight is not designed for such large-scale data processing. Using Amazon Elasticsearch Service (fourth option) for computing precision-recall is not its primary use case and would be inefficient and complex for this specific task.