The NLP Engine is responsible for identifying and classifying sensitive data in different sources, applying NLP algorithms for both discovering these data and also for finding relationships between the discovered data. It consists of 3 modules: the Extraction and Classification module, the Co-Reference Resolution module, and the Human Evaluation and Feedback module.
The interface is a visual component of Data Sense that allows for the users to interact with the underlying platform. Through it, users can, for example, execute runs for discovering sensitive data in a set documents and visualize the obtained results.
The Service Layer consists of APIs that are responsible for the communication between the various components, namely the NLP Engine, the Data Layer and the User Interface.
The Configurations and User Database is responsible for storing the user accounts and the different configuration parameters.
The Results Database is responsible for storing the results produced by the NLP Engine modules, i.e., information about the identification and classification of sensitive data, which are the relevant entities within the data, and the location (indexes) of these sensitive data in the data sources where the discovery queries were performed. None of the actual discovered sensitive data is stored at any point during this process.