Abstract: Aspects of the invention include receiving, using a processor, a plurality of values of a performance indicator. A statistical analysis of the plurality of values of the performance indicator is performed, using the processor, to detect an anomaly pattern in the plurality of values of the performance indicator. A warning message about the detected anomaly pattern is sent to an alert recipient that is selected by a machine learning model trained to identify alert recipients based at least in part on detected anomaly patterns. Feedback about the warning message is received from the alert recipient. The feedback includes an interest of the alert recipient in receiving warning messages about the detected anomaly pattern. The machine learning model is updated based at least in part on the feedback.

Abstract: A method comprises obtaining, from a service management database, one or more change tickets and one or more incident tickets relating to an information technology infrastructure, extracting, from the change tickets and the incident tickets, one or more dimensions indicating potential causality between one or more changes and one or more incidents, identifying configuration items of the information technology infrastructure associated with the one or more changes and the one or more incidents, defining one or more linkages between the one or more changes and the one or more incidents, storing, in the service management database, the defined linkages, building a risk assessment model using the defined linkages, and monitoring subsequent changes to the information technology infrastructure using the risk assessment model.

Abstract: Various embodiments collect unproductive resources in a network infrastructure. In one embodiment, data relating to resources of a network infrastructure is collected. An analytics model is selected based on a type of the collected data. The selected analytics model is executed to classify a resource unproductive or productive, and to assign a corresponding confidence level. An action plan for each confidence level is determined and the action plan is executed for the resource. The collected data may include resource utilization information, hypervisor information, cloud related meta-data, user knowledge and system knowledge. When data is only resource data, a resource mining model is selected. When the data includes reference data, a reference mining model is selected. When the data comprises reference data and resource data, a combined mining model is selected.

Abstract: Providing real-time awareness of an audience to a presenter during the presentation. In response to presenting a presentation to an audience, information is automatically collected about the audience from sensors positioned amongst the audience. The collected information about the audience is analyzed and, during the presentation, recommendations are made to the presenter for improving the presentation based on the collected information.

Abstract: A system includes a memory that stores computer executable components and neural network data, and a processor executes computer executable components stored in the memory. An assessment component assesses a computer network, and classifies the computer network relative to M network classifications stored in a repository, wherein M is an integer greater than one. A risk component determines risk of vulnerability subject to change impact regarding protection against a computer virus or cyber-attack based on historical information regarding vulnerability exposure and vulnerability remediation changes relative to the classification of the computer network. A recommendation component that generates recommendations and best action to mitigate risk and impact, and remediate the vulnerabilities based on the risk assessment and business priorities.

Abstract: Providing real-time awareness of an audience to a presenter during the presentation. In response to presenting a presentation to an audience, information is automatically collected about the audience from sensors positioned amongst the audience. The collected information about the audience is analyzed and, during the presentation, recommendations are made to the presenter for improving the presentation based on the collected information.

Abstract: In an approach to achieving consistent reporting, one or more processors receive a request to include a set of data analysis and visualization parameters in a distributed ledger, such as the blockchain fabric distributed ledger. One or more processors may determine whether the set of data analysis and visualization parameters is consistent with a set of pre-determined rules recorded in the distributed ledger. One or more processors may additionally store the set of data analysis and visualization parameters in the distributed ledger responsive to determining that the set of data analysis and visualization parameters is consistent with the set of pre-determined rules recorded in the distributed ledger. One or more processors may further generate a report of a first dataset based on the set of data analysis and visualization parameters.

Abstract: Aspects of the invention include receiving, using a processor, a plurality of values of a performance indicator. A statistical analysis of the plurality of values of the performance indicator is performed, using the processor, to detect an anomaly pattern in the plurality of values of the performance indicator. A warning message about the detected anomaly pattern is sent to an alert recipient that is selected by a machine learning model trained to identify alert recipients based at least in part on detected anomaly patterns. Feedback about the warning message is received from the alert recipient. The feedback includes an interest of the alert recipient in receiving warning messages about the detected anomaly pattern. The machine learning model is updated based at least in part on the feedback.

Abstract: A method includes obtaining, from a service management database, one or more change tickets and one or more incident tickets relating to an information technology infrastructure, defining one or more change-incident pairs based on linkages between the incident tickets and the change tickets, identifying, from the change-incident pairs, one or more dimensions affecting outcomes of implementation of one or more change types, generating at least one recommendation for altering implementation of subsequent changes of a given change type to the information technology infrastructure based on the identified dimensions, applying the at least one recommendation to the implementation of one or more subsequent changes of the given change type to configuration items in the information technology infrastructure, monitoring the information technology infrastructure to determine outcomes of the subsequent changes of the given change type, and modifying the at least one recommendation responsive to the monitoring.

Abstract: A data collection method including collecting, by a configuration collector manager, configuration data, including configuration properties, from a plurality of data sources, creating, by a model discovery component, a business application model using the configuration data collected by the configuration collector manager, a collecting, from a business application model analysis user interface, edits and confirmations associated with the business application model, and a analyzing, by a feedback analyzer component, the edits and confirmations associated with the business application model and prioritizing the configuration properties based on the data sources and the edits and confirmations associated with the business application model.

Abstract: A system includes a memory that stores computer executable components and neural network data, and a processor executes computer executable components stored in the memory. An assessment component assesses a computer network, and classifies the computer network relative to M network classifications stored in a repository, wherein M is an integer greater than one. A risk component determines risk of vulnerability subject to change impact regarding protection against a computer virus or cyber-attack based on historical information regarding vulnerability exposure and vulnerability remediation changes relative to the classification of the computer network. A recommendation component that generates recommendations and best action to mitigate risk and impact, and remediate the vulnerabilities based on the risk assessment and business priorities.

Abstract: In an approach to achieving consistent reporting, one or more processors receive a request to include a set of data analysis and visualization parameters in a distributed ledger, such as the blockchain fabric distributed ledger. One or more processors may determine whether the set of data analysis and visualization parameters is consistent with a set of pre-determined rules recorded in the distributed ledger. One or more processors may additionally store the set of data analysis and visualization parameters in the distributed ledger responsive to determining that the set of data analysis and visualization parameters is consistent with the set of pre-determined rules recorded in the distributed ledger. One or more processors may further generate a report of a first dataset based on the set of data analysis and visualization parameters.

Abstract: In an approach to achieving consistent reporting, one or more processors receive a request to include a set of data analysis and visualization parameters in a distributed ledger, such as the blockchain fabric distributed ledger. One or more processors may determine whether the set of data analysis and visualization parameters is consistent with a set of pre-determined rules recorded in the distributed ledger. One or more processors may additionally perform a corrective action for the set of data analysis and visualization parameters responsive to determining that the set of data analysis and visualization parameters is not consistent with the set of pre-determined rules recorded in the distributed ledger. One or more processors may further store the set of data analysis and visualization parameters in the distributed ledger and generate a report of a first dataset based on the set of data analysis and visualization parameters.

Abstract: In an approach to achieving consistent reporting, one or more processors receive a request to include a set of data analysis and visualization parameters in a distributed ledger, such as the blockchain fabric distributed ledger. One or more processors may determine whether the set of data analysis and visualization parameters is consistent with a set of pre-determined rules recorded in the distributed ledger. One or more processors may additionally perform a corrective action for the set of data analysis and visualization parameters responsive to determining that the set of data analysis and visualization parameters is not consistent with the set of pre-determined rules recorded in the distributed ledger. One or more processors may further store the set of data analysis and visualization parameters in the distributed ledger and generate a report of a first dataset based on the set of data analysis and visualization parameters.

Abstract: A method includes obtaining, from a service management database, one or more change tickets and one or more incident tickets relating to an information technology infrastructure, defining one or more change-incident pairs based on linkages between the incident tickets and the change tickets, identifying, from the change-incident pairs, one or more dimensions affecting outcomes of implementation of one or more change types, generating at least one recommendation for altering implementation of subsequent changes of a given change type to the information technology infrastructure based on the identified dimensions, applying the at least one recommendation to the implementation of one or more subsequent changes of the given change type to configuration items in the information technology infrastructure, monitoring the information technology infrastructure to determine outcomes of the subsequent changes of the given change type, and modifying the at least one recommendation responsive to the monitoring.

Abstract: A method includes obtaining, from a service management database, one or more change tickets and one or more incident tickets relating to an information technology infrastructure, defining one or more change-incident pairs based on linkages between the incident tickets and the change tickets, identifying, from the change-incident pairs, one or more dimensions affecting outcomes of implementation of one or more change types, generating at least one recommendation for altering implementation of subsequent changes of a given change type to the information technology infrastructure based on the identified dimensions, applying the at least one recommendation to the implementation of one or more subsequent changes of the given change type to configuration items in the information technology infrastructure, monitoring the information technology infrastructure to determine outcomes of the subsequent changes of the given change type, and modifying the at least one recommendation responsive to the monitoring.

Abstract: Methods and arrangements for discovering entity types for a set of records. A set of records is input, with each record comprising attributes with associated attribute values. The records are grouped into candidate entity types in view of at least one of: the attribute values of the records, at least one domain ontology and at least one dimension hierarchy. An interestingness measure of each candidate entity type is calculated, via estimating interestingness based on at least one factor selected from the group consisting of: a correlation between attribute values of records, a number of attributes, a log of queries issued to a server, and an average group size for candidate entity types. At least one candidate entity type is validated based on the calculated interestingness measures. Other variants and embodiments are broadly contemplated herein.

Abstract: A cognitive based service request dispatching system quantifies cognitive dependency of a service request and assigns the service request to maximize a value of cognitive match. A set of metrics comprising service quality index, cognitive capability score, cognitive dependency weight, and cognitive matching score are determined to quantify cognitive dependency of a service request and cognitive based assignment and dispatching of the service request.

Abstract: A method for supplementing structured information within a data system for entities based on unstructured data analyzes a document with unstructured data and extracts attribute values from the unstructured data for one or more entities of the data system. Entity records with structured information are retrieved from the data system based on the extracted attribute values. Entity references for corresponding entities of the data system are constructed based on a comparison of the retrieved entity records and the extracted attribute values. The entity references are linked to the corresponding entities within the data system, with the entity references including extracted attributes from the unstructured data for corresponding linked entities.

Abstract: Various embodiments collect unproductive resources in a network infrastructure. In one embodiment, data relating to resources of a network infrastructure is collected. An analytics model is selected based on a type of the collected data. The selected analytics model is executed to classify a resource unproductive or productive, and to assign a corresponding confidence level. An action plan for each confidence level is determined and the action plan is executed for the resource. The collected data may include resource utilization information, hypervisor information, cloud related meta-data, user knowledge and system knowledge. When data is only resource data, a resource mining model is selected. When the data includes reference data, a reference mining model is selected. When the data comprises reference data and resource data, a reference mining model is selected.