Abstract: Embodiments for locating, identifying and categorizing data-assets through advanced machine learning algorithms implemented by profiler components across Hadoop and Hadoop Compatible File Systems, databases and in-memory objects automatically and periodically to provide a visual representation of the category of data infrastructure distributed across data-centers and multiple clusters, for the purposes of enriching data quality, enabling data discovery and improving outcomes from downstream systems.

Abstract: Embodiments for managing data in a large-scale computer network coupling one or more client computer to a server and having multiple clusters having respective applications, by: encoding web-based data of services to a web browser of a client computer; forwarding requests from the web browser to a cluster access subsystem that wraps the requests in a security protocol interaction that preserves an identity of a user of the client computer; deploying to deploy the applications using an application descriptor for each application of the deployed applications; and storing data about how each application can be accessed through service endpoints including a network address and port identifier for access by queries by any other component, application, or service in the network.