Abstract: A virtual marketplace may offer end users the ability to acquire articles (including tools and metadata objects) that are compatible with an enterprise operating system platform. The virtual marketplace may determine one or more articles that are implemented (or installed) on the enterprise operating system platform. The enterprise operating system platform may be provided to the end user by an operator of the marketplace. The articles including articles that may be used for evaluating a performance of an entity. The virtual marketplace may further ascertain data that are processed or generated by the articles that are implemented on the enterprise operating system platform. The virtual marketplace may additionally determine functionalities that are used or provided by the articles. Accordingly, the virtual marketplace may provide a recommendation of associated articles from the virtual marketplace that have at least one dependency relationship with the articles.

Abstract: A method and system of managing a utility system having a plurality of subsystems. A utility management server receives performance measurement data of a subsystem of a first utility system is received, from a first utility monitoring device (UMD). A type of the subsystem and a type of the first UMD is determined. Static rules are applied based on the type of subsystem and the type of UMD. Upon determining that the predetermined condition based on the static rules is not met, identifying a subsystem and its corresponding UMD responsible for a malfunction by retrieving contextual information from the measurements megastore server, analyzing the data from the first UMD and the contextual information, and sending a notification to the UMD having the subsystem that has been identified as being the source of the malfunction.

Abstract: An analytic application may automatically determine a root cause of an issue with a wireless carrier network and generate a solution for the root cause. Initially, a data management platform may receive performance data regarding user device and network components of a wireless carrier network from multiple data sources. Subsequently, the analytic application may receive an indication of an issue affecting one or more user devices that are using the wireless carrier network. The analytic application may analyze the performance data using a trained machine learning model to determine a root cause for the issue affecting the one or more user devices. The trained machine learning model may employ multiple types of machine learning algorithms to analyze the performance data. The analytic application may provide the root cause or the solution that resolves the root cause for presentation.

Abstract: A set of key performance indicators (KPIs) is calculated for a first set of user devices based on device performance data of the first set of more user devices or network performance data of a communication network that provides communication services to the first set of user devices. The device performance data has at least one of temporal or geographical commonality with the network performance data. A machine learning (ML) model is then trained based on training data, in which the training data includes the network performance data and the set of KPIs calculated for the first set of user devices. The ML model is applied to additional network performance data of the communication network to extrapolate one or more extrapolated KPIs for the first set of user devices or a second set of user devices.

Abstract: A distributed tool virtual marketplace may offer end users the ability to acquire tools that are compatible with an enterprise operating system platform. The virtual marketplace may determine one or more tools that are implemented on the enterprise operating system platform. The enterprise operating system platform may be provided to the end user by an operator of the marketplace. The tools including a tool that may be used for evaluating a performance of an entity. The virtual marketplace may further ascertain data that are processed or generated by the tools that are implemented on the enterprise operating system platform. The virtual marketplace may additionally determine functionalities that are used or provided by the tools. Accordingly, the distributed tool virtual marketplace may provide a recommendation of associated tools from the distributed tool virtual marketplace that have at least one dependency relationship with the tools.

Abstract: A method and system of managing fixed line network elements. Data from disparate sources is received by a processing layer of a monitoring server via a wireline communication network. The intelligence layer determines whether a first node from the disparate nodes is new or pre-existing. Based on a determination by the intelligence layer whether a node is new or pre-existing, different static rules are applied to the received data from the first node. Contextual information is retrieved from the measurements megastore related to the first node. A root cause of a malfunction of the first node is determined. A notification is generated based on the root cause of the malfunction.

Abstract: A network fix application may automatically determine a root cause of an issue with a wireless carrier network and generate a network fix prioritization to implement a solution for the root cause before receiving a customer or network trouble ticket. Initially, a data adaptor platform may receive performance data regarding user device and network components of a wireless carrier network from multiple data sources. The network fix application may analyze the performance data using a trained machine learning model to predict a root cause for the issue affecting the one or more user devices based on the symptoms indicated in the performance data. Additionally, the network fix application may analyze the performance data using another trained machine learning model to provide a network fix prioritization to implement a resolution for each predicted root cause in the most optimal order.

Abstract: An analytic application may automatically determine a root cause of an issue with a wireless carrier network and generate a solution for the root cause. Initially, a data management platform may receive performance data regarding user device and network components of a wireless carrier network from multiple data sources. Subsequently, the analytic application may receive an indication of an issue affecting one or more user devices that are using the wireless carrier network. The analytic application may analyze the performance data using a trained machine learning model to determine a root cause for the issue affecting the one or more user devices. The trained machine learning model may employ multiple types of machine learning algorithms to analyze the performance data. The analytic application may provide the root cause or the solution that resolves the root cause for presentation.

Abstract: A communication analytics engine that executes in conjunction with a data collection platform may provide a unified and scalable solution for call data aggregation and processing. A data collection platform may establish a communication connection with a wireless carrier network. The data collection platform may collect call data of multiple user devices via the communication connection, in which the multiple user devices may use the wireless carrier network to initiate and receive calls to one or more additional devices. The data collection platform may convert the call data into a format that is readable by the communication analytics engine. The communication analytics engine may analyze the call data to generate analytic results that includes one or more key performance indicators (KPIs).

Abstract: A performance management engine may be implemented to continuously detecting entity performance issues. The performance management engine may calculate one or more key performance indicators (KPIs) that measure performance of an entity. The performance management engine may further receive one or more additional sources of data regarding the entity via a data management platform that interfaces with multiple data sources. The performance management engine may aggregate the KPIs and the one or more additional sources of data into datasets according to one or more grouping parameters. The data in one or more datasets may be analyzed by the performance management engine to generate one or more comprehensive performance indicators. The comprehensive performance indicators are then provided for display on a user device. Each KPI or comprehensive performance indicator measures performance of a device, a component, a node, or a service of the entity.

Abstract: A method and system of creating an alert for a monitored network system. Key performance indicators (KPI's) of a plurality of components of a monitored network system are displayed on a user interface. A selection of one or more components of the plurality of components related to a malfunction is received. A present status and/or a pattern of performance of the one or more selected components is extracted. A preliminary alert is created based on the at least one of (i) the present status and (ii) the pattern of performance of the one or more selected components. Historical data related to the one or more selected components is retrieved. The preliminary alert is trained based on at least some of the retrieved historical scenarios. The preliminary alert is promoted to a primary alert upon training the preliminary to a confidence level that is above a predetermined threshold.

Abstract: Machine-learning based geolocation techniques may be used to provide the geolocations of user devices and determine the locations of hotspot areas. A coarse geolocation of a user device may be determined based on the wireless communication network usage information of the user device. Device data that includes the coarse geolocation of the use device may be inputted into a trained geolocation model of a machine learning algorithm. A refined geolocation of the user device that is more accurate than the coarse geolocation of the user device may be determined by using the machine learning algorithm to process the device data via the trained geolocation model. The refined geolocation of the user device may be further stored in a data store.

Abstract: A method and system of managing fixed line network elements. Data from disparate sources is received by a processing layer of a monitoring server via a wireline communication network. The intelligence layer determines whether a first node from the disparate nodes is new or pre-existing. Based on a determination by the intelligence layer whether a node is new or pre-existing, different static rules are applied to the received data from the first node. Contextual information is retrieved from the measurements megastore related to the first node. A root cause of a malfunction of the first node is determined. A notification is generated based on the root cause of the malfunction.

Abstract: An analytic application may provide analysis of performance data for a wireless carrier network to determine root causes of issues. Performance data for network components of the wireless carrier network and device components of user devices that use the network may be obtained. The performance data is processed by aggregating multiple datasets of the performance data into aggregated performance data according to one or more grouping parameters or converge a plurality of datasets of the performance data into converged performance data according to a unitary storage schema. Analysis may be performed on the aggregated performance data or the converged performance data to detect an issue affecting the wireless carrier network or to generate a solution to the issue. The aggregate performance data and the converged performance data may include non-real time data or real time data. Accordingly, the issue or the solution to the issue may be provided for presentation.

Abstract: Integrated application development and deployment may speed up application development. The continuous integration component of a software development engine may generate a completed version of a deployment project in a development environment by at least generating an updated version of a first project element concurrently with integrating an initial version of the first project element with an initial version of a second project element. The updated version of the first project element is then integrated with the initial version of the second project element to generate the completed version. An orchestration component may configure a production environment to execute a production image that is a copy of a development image that is created from the completed version, in which the production environment is mirrored by the development environment. The continuous integration tool may also include an automatic deployment component that deploys the production image into the production environment for execution.

Abstract: A performance management engine may be implemented to continuously detecting entity performance issues. The performance management engine may calculate one or more key performance indicators (KPIs) that measure performance of an entity. The performance management engine may further receive one or more additional sources of data regarding the entity via a data management platform that interfaces with multiple data sources. The performance management engine may aggregate the KPIs and the one or more additional sources of data into datasets according to one or more grouping parameters. The data in one or more datasets may be analyzed by the performance management engine to generate one or more comprehensive performance indicators. The comprehensive performance indicators are then provided for display on a user device. Each KPI or comprehensive performance indicator measures performance of a device, a component, a node, or a service of the entity.

Abstract: A communication analytics engine that executes in conjunction with a data collection platform may provide a unified and scalable solution for call data aggregation and processing. A data collection platform may establish a communication connection with a wireless carrier network. The data collection platform may collect call data of multiple user devices via the communication connection, in which the multiple user devices may use the wireless carrier network to initiate and receive calls to one or more additional devices. The data collection platform may convert the call data into a format that is readable by the communication analytics engine. The communication analytics engine may analyze the call data to generate analytic results that includes one or more key performance indicators (KPIs).

Abstract: An analytic application may automatically determine a root cause of an issue with a wireless carrier network and generate a solution for the root cause. Initially, a data management platform may receive performance data regarding user device and network components of a wireless carrier network from multiple data sources. Subsequently, the analytic application may receive an indication of an issue affecting one or more user devices that are using the wireless carrier network. The analytic application may analyze the performance data using a trained machine learning model to determine a root cause for the issue affecting the one or more user devices. The trained machine learning model may employ multiple types of machine learning algorithms to analyze the performance data. The analytic application may provide the root cause or the solution that resolves the root cause for presentation.

Abstract: A method and system of distributed parallel processing. There are a plurality of distributed parallel processing units (DPPUs). Each DPPU is configured to receive data related to a condition of the network. The type of data received by each DPPU is disparate for each DPPU. Each DPPU analyzes its data. Upon determining that a predetermined condition is met or a predetermined threshold is exceeded, the disparate data is transformed into a common format using an appropriate driver of the configuration module. The common format data is sent to a storage device of a first DPPU of the plurality of DPPUs.