Abstract: A method, apparatus, and computer program are disclosed. The method may be performed by one or more processors and may comprise receiving first data representing an infrastructure of a computer network, the first data comprising an indication of hosts which form at least part of the computer network and one or more software resources on respective hosts. The method may also comprise receiving second data from a vulnerability scanning software, the second data comprising an indication of one or more vulnerabilities detected in the one or more software resources provided on at least some of the hosts of the computer network. Using a combination of the first data and the second data, output data may be generated representing a risk profile of the computer network infrastructure, the output data indicating one or more subsets of hosts, determined as being at risk of being affected by the detected vulnerabilities by virtue of the software resources they provide for output on a user interface.

Abstract: A method, apparatus, and computer program are disclosed. The method may be performed by one or more processors and may comprise receiving first data representing an infrastructure of a computer network, the first data comprising an indication of hosts which form at least part of the computer network and one or more software resources on respective hosts. The method may also comprise receiving second data from a vulnerability scanning software, the second data comprising an indication of one or more vulnerabilities detected in the one or more software resources provided on at least some of the hosts of the computer network. Using a combination of the first data and the second data, output data may be generated representing a risk profile of the computer network infrastructure, the output data indicating one or more subsets of hosts, determined as being at risk of being affected by the detected vulnerabilities by virtue of the software resources they provide for output on a user interface.

Abstract: A computing system accesses one or more data sources to determine maintenance optimization data associated with an asset within a set of assets. The maintenance optimization data may include one or more of: upcoming maintenance events for the asset, such as may be predicted based on analysis of historical maintenance information of the asset, a time series of predicted value of the asset over a time period around the upcoming maintenance event, such as within a few days or hours of the maintenance event, and/or a recommended window of time to initiate and/or perform upcoming maintenance events, which may be based on a combination of the expected upcoming maintenance events, and the time series of predicted value of the particular asset, for example.

Abstract: A computing system accesses one or more data sources to determine maintenance optimization data associated with an asset within a set of assets. The maintenance optimization data may include one or more of: upcoming maintenance events for the asset, such as may be predicted based on analysis of historical maintenance information of the asset, a time series of predicted value of the asset over a time period around the upcoming maintenance event, such as within a few days or hours of the maintenance event, and/or a recommended window of time to initiate and/or perform upcoming maintenance events, which may be based on a combination of the expected upcoming maintenance events, and the time series of predicted value of the particular asset, for example.

Abstract: User interfaces are provided for improved data optimization. A model user interface can be used to generate models based on a historical data file based on modeling details and filters specified by a user. The user can save the models and apply the models to optimize a data file. The user can specify optimization details and see visualizations of the results.

Abstract: User interfaces are provided for improved data optimization. A model user interface can be used to generate models based on a historical data file based on modeling details and filters specified by a user. The user can save the models and apply the models to optimize a data file. The user can specify optimization details and see visualizations of the results.

Abstract: A method, apparatus, and computer program are disclosed. The method may be performed by one or more processors and may comprise receiving first data representing an infrastructure of a computer network, the first data comprising an indication of hosts which form at least part of the computer network and one or more software resources on respective hosts. The method may also comprise receiving second data from a vulnerability scanning software, the second data comprising an indication of one or more vulnerabilities detected in the one or more software resources provided on at least some of the hosts of the computer network. Using a combination of the first data and the second data, output data may be generated representing a risk profile of the computer network infrastructure, the output data indicating one or more subsets of hosts, determined as being at risk of being affected by the detected vulnerabilities by virtue of the software resources they provide for output on a user interface.

Abstract: A method, apparatus, and computer program are disclosed. The method may be performed by one or more processors and may comprise receiving first data representing an infrastructure of a computer network, the first data comprising an indication of hosts which form at least part of the computer network and one or more software resources on respective hosts. The method may also comprise receiving second data from a vulnerability scanning software, the second data comprising an indication of one or more vulnerabilities detected in the one or more software resources provided on at least some of the hosts of the computer network. Using a combination of the first data and the second data, output data may be generated representing a risk profile of the computer network infrastructure, the output data indicating one or more subsets of hosts, determined as being at risk of being affected by the detected vulnerabilities by virtue of the software resources they provide for output on a user interface.

Abstract: A computing system accesses one or more data sources to determine maintenance optimization data associated with an asset within a set of assets. The maintenance optimization data may include one or more of: upcoming maintenance events for the asset, such as may be predicted based on analysis of historical maintenance information of the asset, a time series of predicted value of the asset over a time period around the upcoming maintenance event, such as within a few days or hours of the maintenance event, and/or a recommended window of time to initiate and/or perform upcoming maintenance events, which may be based on a combination of the expected upcoming maintenance events, and the time series of predicted value of the particular asset, for example.

Abstract: A computing system accesses one or more data sources to determine maintenance optimization data associated with an asset within a set of assets. The maintenance optimization data may include one or more of: upcoming maintenance events for the asset, such as may be predicted based on analysis of historical maintenance information of the asset, a time series of predicted value of the asset over a time period around the upcoming maintenance event, such as within a few days or hours of the maintenance event, and/or a recommended window of time to initiate and/or perform upcoming maintenance events, which may be based on a combination of the expected upcoming maintenance events, and the time series of predicted value of the particular asset, for example.

Abstract: User interfaces are provided for improved data optimization. A model user interface can be used to generate models based on a historical data file based on modeling details and filters specified by a user. The user can save the models and apply the models to optimize a data file. The user can specify optimization details and see visualizations of the results.

Abstract: A computing system accesses one or more data sources to determine maintenance optimization data associated with an asset within a set of assets. The maintenance optimization data may include one or more of: upcoming maintenance events for the asset, such as may be predicted based on analysis of historical maintenance information of the asset, a time series of predicted value of the asset over a time period around the upcoming maintenance event, such as within a few days or hours of the maintenance event, and/or a recommended window of time to initiate and/or perform upcoming maintenance events, which may be based on a combination of the expected upcoming maintenance events, and the time series of predicted value of the particular asset, for example.

Abstract: User interfaces are provided for improved data optimization. A model user interface can be used to generate models based on a historical data file based on modeling details and filters specified by a user. The user can save the models and apply the models to optimize a data file. The user can specify optimization details and see visualizations of the results.

Abstract: A method, apparatus, and computer program are disclosed. The method may be performed by one or more processors and may comprise receiving first data representing an infrastructure of a computer network, the first data comprising an indication of hosts which form at least part of the computer network and one or more software resources on respective hosts. The method may also comprise receiving second data from a vulnerability scanning software, the second data comprising an indication of one or more vulnerabilities detected in the one or more software resources provided on at least some of the hosts of the computer network. Using a combination of the first data and the second data, output data may be generated representing a risk profile of the computer network infrastructure, the output data indicating one or more subsets of hosts, determined as being at risk of being affected by the detected vulnerabilities by virtue of the software resources they provide for output on a user interface.