Abstract: One example method is performed at a far edge device and includes collecting data with one or more IoT (Internet of Things) devices, feeding the data to a feedback loop that includes multiple stages, running the feedback loop, providing learning information, comprising output from one or more of the stages of the feedback loop, to a central manager by way of a learn interface, accessing learning information generated by one or more other far edge devices, and updating the feedback loop using the learning information generated by the one or more other far edge devices.

Abstract: One example method includes receiving a query that recites a particular question for which a user who originated the query needs an answer, parsing the query to identify the question, identifying information that is responsive to the question, presenting the information to the user in a user-selectable form, and receiving, from the user, a selection of the information. In some cases, the information presented to the user may include one or more datasets, or one or more pipelines.

Abstract: One example method includes receiving a data stream that comprises data in a form of multi-dimensional data structures. The data stream may be received in real time as it is generated. Metadata about the data may be generated and stored. Further, portions of the data may be selected and cached, and the cached data analyzed in real time. Based on the analyzing, various insights may be generated concerning the data that was analyzed.

Abstract: One example method includes receiving a data stream that comprises data in a form of multi-dimensional data structures. The data stream may be received in real time as it is generated. Metadata about the data may be generated and stored. Further, portions of the data may be selected and cached, and the cached data analyzed in real time. Based on the analyzing, various insights may be generated concerning the data that was analyzed.

Abstract: A graph is disclosed. A graph includes entities that are represented by N-dimensional matrices. Each of the entities is associated with one or more attributes and each attribute has its own dimension. The graph can represent time aware graph entity changes, time aware graph relationship changes, and supports time aware queries.

Abstract: One example method includes receiving, by a graph proxy, an event from an event generator, and the event includes information about an IO and information about data affected by the IO, comparing, by the graph proxy, the data to a schema, when the data is determined by the graph proxy to map to the schema, identifying, by the graph proxy, a rule that is associated with the event, and the rule specifies performance of an action when a condition is met, and when the condition is met, performing, by the graph proxy, the action, and the action is performed with respect to a graph.

Abstract: Hardware trust boundaries in a data confidence fabric are provided. Nodes in a data confidence fabric are provisioned with identifies and confidence scores. Hardware-based trust insertion technologies are applied to data in the data confidence fabric. Protocols allow nodes to join the data confidence fabric and be aware of other nodes. Paths of data can be graphed and audited.

Abstract: A method for managing data includes obtaining, by an indirection logic service, a data request for data, wherein the data request specifies a ledger entry, identifying an indirection logic entry stored in the indirection logic service based on the ledger entry, obtaining a selection of trust data from a client, wherein the ledger entry comprises metadata of the trust data, and initiating communication between the client and a local trust manager based on the selection of trust data, wherein the trust data was generated by the local trust manager.

Abstract: A method in one embodiment comprises receiving a plurality of requests for data records from a plurality of clients. The data is in a plurality of data systems of a global namespace, and the plurality of data systems are in a plurality of locations. The method also comprises determining whether a given client is allowed access to one or more of the data records based on one or more of a plurality of data access policies, retrieving the data records from at least one of the data systems based on a determination that the given client is allowed access to the data records, and providing the data records to the given client. Retrieving the data records comprises determining a location for the data records, and generating a channel to the location through which the data records are retrieved.

Abstract: One example method includes receiving a query that recites a particular question for which a user who originated the query needs an answer, parsing the query to identify the question, identifying information that is responsive to the question, presenting the information to the user in a user-selectable form, and receiving, from the user, a selection of the information. In some cases, the information presented to the user may include one or more datasets, or one or more pipelines.

Abstract: One example method includes receiving a query that recites a particular question for which a user who originated the query needs an answer, parsing the query to identify the question, identifying information that is responsive to the question, presenting the information to the user in a user-selectable form, and receiving, from the user, a selection of the information. In some cases, the information presented to the user may include one or more datasets, or one or more pipelines.

Abstract: One example method includes receiving a user request for a data set, and the user request includes information concerning user requirements for the data set, identifying data records that satisfy one or more of the user requirements, calculating a respective relative value for each of the data records, and the relative values are based in part on the user requirements, and providing access controls for each data record that enable tracing of accesses of the data record.

Abstract: Aspects of annotating data are disclosed. As data is ingested to a data confidence fabric, analytic values, which includes tags or annotations, are attached to or associated with the data by an analytic insertion mechanism. The analytic values allow the data to be used by applications including machine learning algorithms immediately. Feedback from the applications allow the analytic insertion mechanism to improve and generate more valuable analytic values and to generate higher confidence scores for the analytic values.

Abstract: A method in one embodiment comprises receiving a plurality of requests for data records from a plurality of clients. The data is in a plurality of data systems of a global namespace, and the plurality of data systems are in a plurality of locations. The method also comprises determining whether a given client is allowed access to one or more of the data records based on one or more of a plurality of data access policies, retrieving the data records from at least one of the data systems based on a determination that the given client is allowed access to the data records, and providing the data records to the given client. Retrieving the data records comprises determining a location for the data records, and generating a channel to the location through which the data records are retrieved.

Abstract: A method for managing data includes obtaining, by an indirection logic service, a data request for data, wherein the data request specifies a ledger entry, identifying an indirection logic entry stored in the indirection logic service based on the ledger entry, obtaining a selection of trust data from a client, wherein the ledger entry comprises metadata of the trust data, and initiating communication between the client and a local trust manager based on the selection of trust data, wherein the trust data was generated by the local trust manager.

Abstract: Hardware trust boundaries in a data confidence fabric are provided. Nodes in a data confidence fabric are provisioned with identifies and confidence scores. Hardware-based trust insertion technologies are applied to data in the data confidence fabric. Protocols allow nodes to join the data confidence fabric and be aware of other nodes. Paths of data can be graphed and audited.

Abstract: An information handling system server chassis manages plural server resources disposed on sleds in chassis slots with a power supply control board that allocates power from one or more power supplies to the slots. The power supply control board interfaces with an external network and includes one or more network interface cards that provide an Ethernet interface with power distribution boards disposed on sleds in the slots. The power distribution boards manage application of power to server resources and communication by the power supply control board through the Ethernet interface to manage functions at the server resources.

Abstract: An information handling system server chassis manages plural server resources disposed on sleds in chassis slots with a power supply control board that allocates power from one or more power supplies to the slots. The power supply control board interfaces with an external network and includes one or more network interface cards that provide an Ethernet interface with power distribution boards disposed on sleds in the slots. The power distribution boards manage application of power to server resources and communication by the power supply control board through the Ethernet interface to manage functions at the server resources.

Abstract: A system and method for a search engine is disclosed. A method for operating a search engine may include calculating a plurality of document vectors, receiving a search request, calculating a search request vector, calculating a distance between the search request vector and the plurality of document vectors, and returning a list of documents that are within a predetermined distance of the search request vector. An information handling system for a search engine may include a central processing unit that is coupled to a general purpose graphical processing unit. The central processing unit is able to calculate a plurality of document vectors, receive a search request, calculate a search vector, and return a list of documents that are within a predetermined distance of the search request vector. The general purpose graphical processing unit is able to calculate a distance between the search request vector and the plurality of document vectors.

Abstract: A system and method for authenticating the source, integrity, and associated execution controls, of a plurality of software, including but not limited to, installation packages, updates, patches, and other code components, distributed from a plurality of issuers for implementation on a plurality of predetermined recipient information handling systems operating within a network environment. Current file security is improved by automatically filtering software installation packages to ensure that each package component is signed by a trusted and verified issuer, and has not been tampered with, thereby replacing a weak, native trust model based on firewalls, static filters, reactive detection, and cleansing approaches.