A specialist needs to move and transform data for training. Some data must be processed near-real time and other data hourly. Existing Amazon EMR MapReduce jobs perform cleaning and feature engineering. Which two services can feed data into those MapReduce jobs? (Choose two.)

Amazon Kinesis is correct because it's designed for real-time streaming data ingestion, which aligns with the requirement for near-real-time processing. Kinesis can capture, process, and store large streams of data records, making it suitable for feeding real-time data into EMR MapReduce jobs. AWS Data Pipeline is correct because it's a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premise data sources, on a scheduled basis. This directly addresses the need for hourly data processing and can orchestrate the feeding of data into EMR MapReduce jobs. AWS Database Migration Service (DMS) is incorrect because it's primarily used for migrating databases to AWS, not for general-purpose, ongoing data ingestion for analytics. Amazon Athena is incorrect because it's an interactive query service for analyzing data in Amazon S3 using standard SQL, not a service for ingesting or moving data into EMR. Amazon Elasticsearch Service (Amazon ES) is incorrect because it's a managed service for deploying, operating, and scaling Elasticsearch clusters, typically used for search and analytics, not for data ingestion into EMR MapReduce jobs.