Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A system for troubleshooting network problems is disclosed. A model can use demographic information, network usage information, and network membership information to determine an importance of a problem. The importance of the problem for the user who reported the problem, a number of other users affected by the problem, and the importance of the problem to the other users can be used to determine a priority for resolving the problem. Before and after a work order is executed to resolve the problem, network metrics can be gathered, including aggregate network metrics, and automatically presented in various user interfaces. The analysis of the metrics can be used to update a database of which work orders are assigned in response to which problems.

Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A system for troubleshooting network problems is disclosed. A model can use demographic information, network usage information, and network membership information to determine an importance of a problem. The importance of the problem for the user who reported the problem, a number of other users affected by the problem, and the importance of the problem to the other users can be used to determine a priority for resolving the problem. Before and after a work order is executed to resolve the problem, network metrics can be gathered, including aggregate network metrics, and automatically presented in various user interfaces. The analysis of the metrics can be used to update a database of which work orders are assigned in response to which problems.

Abstract: A system for troubleshooting network problems is disclosed. A model can use demographic information, network usage information, and network membership information to determine an importance of a problem. The importance of the problem for the user who reported the problem, a number of other users affected by the problem, and the importance of the problem to the other users can be used to determine a priority for resolving the problem. Before and after a work order is executed to resolve the problem, network metrics can be gathered, including aggregate network metrics, and automatically presented in various user interfaces. The analysis of the metrics can be used to update a database of which work orders are assigned in response to which problems.

Abstract: A system for troubleshooting network problems is disclosed. A model can use demographic information, network usage information, and network membership information to determine an importance of a problem. The importance of the problem for the user who reported the problem, a number of other users affected by the problem, and the importance of the problem to the other users can be used to determine a priority for resolving the problem. Before and after a work order is executed to resolve the problem, network metrics can be gathered, including aggregate network metrics, and automatically presented in various user interfaces. The analysis of the metrics can be used to update a database of which work orders are assigned in response to which problems.

Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A system for troubleshooting network problems is disclosed. A model can use demographic information, network usage information, and network membership information to determine an importance of a problem. The importance of the problem for the user who reported the problem, a number of other users affected by the problem, and the importance of the problem to the other users can be used to determine a priority for resolving the problem. Before and after a work order is executed to resolve the problem, network metrics can be gathered, including aggregate network metrics, and automatically presented in various user interfaces. The analysis of the metrics can be used to update a database of which work orders are assigned in response to which problems.

Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A system and method for processing data wherein one or more user selections of source data and an input defining one or more operations to be performed on the selected source data are received to generate processed data for display as a chart; the source data is retrieved from at least one data source, the source data is processed according to the defined one or more operations to generate processed data for output for display as a chart, the chart is stored as data defining the one or more operations and data identifying the source data operated on, a further user selection is received to redisplay the chart; retrieving the source data from the at least one data source; and the source data is processed according to the defined one or more operations to generate the processed data for output for redisplay as the chart.

Abstract: A canonical decomposition (CD) method that includes building a multi-variate linear autoregressive (“MLAR”) model from an original data set or from a reduced set derived by data reduction methods from the original data set. The MLAR analysis is followed by seeking a coordinate transformation of the MLAR model to obtain the best possible match with one or more canonical forms representing relationships among components. For multi-variate data with a truly hierarchical structure, CD accurately extracts the underlying sources of the system.

Abstract: A canonical decomposition (CD) method that includes building a multi-variate linear autoregressive (“MLAR”) model from an original data set or from a reduced set derived by data reduction methods from the original data set. The MLAR analysis is followed by seeking a coordinate transformation of the MLAR model to obtain the best possible match with one or more canonical forms representing relationships among components. For multi-variate data with a truly hierarchical structure, CD accurately extracts the underlying sources of the system.

Abstract: A canonical decomposition (CD) method that includes building a multi-variate linear autoregressive (“MLAR”) model from an original data set or from a reduced set derived by data reduction methods from the original data set. The MLAR analysis is followed by seeking a coordinate transformation of the MLAR model to obtain the best possible match with one or more canonical forms representing relationships among components. For multi-variate data with a truly hierarchical structure, CD accurately extracts the underlying sources of the system.

Abstract: A canonical decomposition (CD) method that includes building a multi-variate linear autoregressive (“MLAR”) model from an original data set or from a reduced set derived by data reduction methods from the original data set. The MLAR analysis is followed by seeking a coordinate transformation of the MLAR model to obtain the best possible match with one or more canonical forms representing relationships among components. For multi-variate data with a truly hierarchical structure, CD accurately extracts the underlying sources of the system.