As new data is imported into the data reservoir, the data ingestion processes ensure the data is transformed, logged, and copied into the appropriate data repositories. The ability to easily import data from a multitude of sources is one of the selling points of the data reservoir. You want to be able to capture anything easily, and to allow decisions about how that data can be used later in the process. That being said, information needs to be incorporated into the reservoir in a controlled manner. During the process, metadata must be captured. It is also important to ensure appropriate separation between other systems and the reservoir to ensure an issue in one does not impact both. The Information Ingestion component is responsible for managing this. A staging area will often be used as part of the process to support loose coupling and ensure that delays in processing will not affect the source system. The information ingestion component will apply appropriate policies to the incoming data, including masking, quality validation, deduplication, and will push appropriate metadata to the reservoir catalog. Data with a known structure can be stored in a more structured repository such as a relational database, whereas less structured or mixed data can end up in a file system such as HDFS.