Distributed multi-data source performance management
First Claim
1. One or more non-transitory computer-readable media storing computer-executable instructions that upon execution cause one or more processors to perform acts comprising:
- calculating one or more key performance indicators (KPIs) for an entity, the calculating the one or more KPIs including;
receiving operation data regarding operations of the entity via the data management platform,aggregating the operation data into a plurality of datasets according to one or more grouping parameters,selecting one or more predicted KPIs for the entity based on historical query request information, the one or more predicted KPIs being likely to be requested in an upcoming time period, andpre-calculating the one or more predicted KPIs for the entity according to the operation data in one or more datasets of the plurality of datasets,receiving one or more additional sources of data regarding the entity via a data management platform that interfaces with multiple data sources;
aggregating the one or more KPIs and the one or more additional sources of data into datasets according to one or more grouping parameters;
analyzing data in one or more datasets to generate one or more comprehensive performance indicators; and
providing at least one comprehensive performance indicator for display on a user device, wherein each KPI and each comprehensive performance indicator respectively indicates a performance of a device, a component, a node, or a service of the entity.
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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.
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Citations
20 Claims
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1. One or more non-transitory computer-readable media storing computer-executable instructions that upon execution cause one or more processors to perform acts comprising:
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calculating one or more key performance indicators (KPIs) for an entity, the calculating the one or more KPIs including; receiving operation data regarding operations of the entity via the data management platform, aggregating the operation data into a plurality of datasets according to one or more grouping parameters, selecting one or more predicted KPIs for the entity based on historical query request information, the one or more predicted KPIs being likely to be requested in an upcoming time period, and pre-calculating the one or more predicted KPIs for the entity according to the operation data in one or more datasets of the plurality of datasets, receiving one or more additional sources of data regarding the entity via a data management platform that interfaces with multiple data sources; aggregating the one or more KPIs and the one or more additional sources of data into datasets according to one or more grouping parameters; analyzing data in one or more datasets to generate one or more comprehensive performance indicators; and providing at least one comprehensive performance indicator for display on a user device, wherein each KPI and each comprehensive performance indicator respectively indicates a performance of a device, a component, a node, or a service of the entity. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A computer-implemented method, comprising:
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calculating one or more key performance indicators (KPIs) for an entity via a performance management engine that executes on one or more computing nodes, the calculating the one or more KPIs including; receiving operation data regarding operations of the entity via the data management platform; aggregating the operation data into a plurality of datasets according to one or more grouping parameters; selecting one or more predicted KPIs for the entity based on historical query request information, the one or more predicted KPIs being likely to be requested in an upcoming time period, and pre-calculating the one or more predicted KPIs for the entity according to the operation data in one or more datasets of the plurality of datasets; receiving one or more additional sources of data regarding the entity via a data management platform that interfaces with multiple data sources, the multiple data sources further including one or more of a social media data source, an alarm data source of the entity, a trouble ticket data source of the entity, or a tool data source of the entity; aggregating the one or more KPIs and the one or more additional sources of data into datasets according to one or more grouping parameters, the one or more grouping parameters include a specific time period, a specific entity component, a specific user device vendor, a specific user device model, or different levels of an entity hierarchy that includes a subscriber level, a device level, a service area level, and a geographical market level; analyzing data in one or more datasets to generate one or more comprehensive performance indicators via the performance management engine; and providing at least one comprehensive performance indicator for display on a user device, wherein each KPI and each comprehensive performance indicator respectively indicates a performance of a device, a component, a node, or a service of the entity. - View Dependent Claims (15, 16, 17, 18)
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14. The computer-implemented method of 13, wherein the calculating the one or more KPIs further includes:
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receiving operation data regarding operations of the entity via the data management platform, aggregating the operation data into a plurality of datasets according to one or more grouping parameters, pre-calculating the one or more KPIs for the entity according to the operation data in one or more datasets of the plurality of datasets, determining whether a specific KPI that is requested corresponds to a pre-calculated predicted KPI, the specific KPI being requested for fulfilling a performance data query that is initiated at a user device or generating a comprehensive performance indicator, retrieving the pre-calculated predicted KPI from a KPI cache for presentation on the user device or generation of the comprehensive performance indicator in response to a determination that the specific KPI corresponds to the pre-calculated predicted KPI, and calculating the specific KPI for the entity according to the operation data in a corresponding dataset of the plurality of datasets, and providing the specific KPI for presentation on the user device or the generation of the comprehensive performance indicator, in response to a determination that the one or more predicted KPIs as pre-calculated fail to correspond to the specific KPI.
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19. A system, comprising:
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one or more processors; and memory including a plurality of computer-executable components that are executable by the one or more processors to perform a plurality of actions, the plurality of actions comprising; receiving operation data regarding operations of an entity via a data management platform that interfaces with multiple data sources, the multiple data sources including an operation data source that stores the operation data; aggregating the operation data into a plurality of datasets according to one or more grouping parameters, the one or more grouping parameters include a specific time period, a specific entity component, a specific user device vendor, a specific user device model, or different levels of an entity hierarchy that includes a subscriber level, a device level, a service area level, and a geographical market level; and selecting one or more predicted Key Performance Indicators (KPIs) for the entity based on historical query request information, the one or more predicted KPIs being likely to be requested in an upcoming time period, pre-calculating the one or more predicated KIPIs for the entity according to the operation data in one or more datasets of the plurality of datasets; determining whether a specific KPI that is requested corresponds to a pre-calculated predicated KPI; retrieving the pre-calculated KPI from a KPI cache in response to a determination that the specific KPI corresponds to the pre-calculated predicated KPI; and calculating the specific KPI for the entity according to the operation data in a corresponding dataset of the plurality of datasets in response to a determination that the one or more predicated KPIs as pre-calculated fail to correspond to the specific KPI. - View Dependent Claims (20)
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Specification