System and method for aggregating data from a plurality of data sources

Abstract

According to certain aspects, a computer system may be configured to aggregate and analyze data from a plurality of data sources. The system may obtain data from a plurality of data sources, each of which can include various types of data, including email data, system logon data, system logoff data, badge swipe data, employee data, job processing data, etc. associated with a plurality of individuals. The system may also transform data from each of the plurality of data sources into a format that is compatible for combining the data from the plurality of data sources. The system can resolve the data from each of the plurality of data sources to unique individuals of the plurality of individuals. The system can also determine an efficiency indicator based at least in part on a comparison of individuals of the unique individuals that have at least one common characteristic.

What is claimed is: 
     
         1 . A computer system comprising:
 a hardware computer processor configured to execute code to cause the computer system to:   access, from a first data source, first data items each associated with one of a plurality of individuals, the first data items indicating one or more of a badge-in time indicating entrance to a physical facility or a badge-out time indicating exit from the physical facility;   generate, for each individual, a first summary of first data items associated with the individual;   access, from a second data source, second data items each associated with one of the plurality of individuals, the second data items indicating one or more of system login time, system logout time, VPN login time, or VPN logout time;   generate, for each individual, a second summary of second data items associated with the individual, wherein at least the first summary and the second summary are each accessible by the computer system;   determine, a first group of unique individuals each sharing a first correlation between the first summary and the second summary;   determine a second group of unique individuals each sharing a second correlation between the first summary and the second summary;   generate a first output based at least on first data items and second data items of individuals in the first group;   generate a second output based at least on first data items and second data items of individuals in the second group;   determine a first security indicator for the first group relative to the second group based at least in part on comparison of the first output and the second output; and   generate user interface data configured to cause display of a user interface on a user computing device, the user interface including an indication of the first group, the second group, and the determined first security indicator.   
     
     
         2 . The computing system of  claim 1 , wherein the first output indicates one or more of an average badge-in time or an average badge-out time. 
     
     
         3 . The computing system of  claim 1 , wherein the code is further configured to cause the computer system to:
 receive, via input from the user interface, selection of a comparison characteristic;   determine, a third group of unique individuals each sharing the comparison characteristic;   generate a third output based at least on first data items of individuals in the third group;   determine a second security indicator for the first group based at least in part on comparison of the first output and the third output; and   update the user interface data to indicate the first group, the third group and the determined second security indicator.   
     
     
         4 . The computer system of  claim 1 , wherein the first common characteristic comprises badge-in time within a timespan or badge-out time within the timespan. 
     
     
         5 . The computing system of  claim 1 , wherein the code is further configured to cause the computer system to:
 generate a mapping of unique individuals within each of the first group and the second group.   
     
     
         6 . The computing system of  claim 1 , wherein the code is further configured to cause the computer system to:
 access expected format information indicating an expected format of data from the first data source providing the first data items or the second data source providing the second data items; and   detect inconsistencies in a first format of the data from the first data source or a second format from the second data source as compared to the expected format.   
     
     
         7 . The computing system of  claim 6 , wherein the code is further configured to cause the computer system to:
 in response to detection of an inconsistency, obtain the first or second data from the respective first or second data source such that the first or second data no longer has the inconsistency.   
     
     
         8 . The computing system of  claim 7 , wherein the code is further configured to cause the computer system to:
 update the user interface data to include an indicator of the inconsistency.   
     
     
         9 . The computing system of  claim 1 , wherein the code is further configured to cause the computer system to:
 determine a first file size for the first data items or second data items;   access a previous file size for a previous version of the first data items or second data items;   detect a discrepancy in size between the previous file size and the first file size; and   in response to detection of the discrepancy, obtain the first data items or second data items from respective first or second data sources such that the first or second data no longer has the discrepancy.   
     
     
         10 . A computerized method, performed by a computing system having one or more hardware computer processors and one or more non-transitory computer readable storage device storing software instructions executable by the computing system to perform the computerized method comprising:
 accessing, from a first data source, first data items each associated with one of a plurality of individuals, the first data items indicating one or more of a badge-in time indicating entrance to a physical facility or a badge-out time indicating exit from the physical facility;   generating, for each individual, a first summary of first data items associated with the individual;   accessing, from a second data source, second data items each associated with one of the plurality of individuals, the second data items indicating one or more of system login time, system logout time, VPN login time, or VPN logout time;   generating, for each individual, a second summary of second data items associated with the individual, wherein at least the first summary and the second summary are each accessible by the computer system;   determining, a first group of unique individuals each sharing a first correlation between the first summary and the second summary;   determining a second group of unique individuals each sharing a second correlation between the first summary and the second summary;   generating a first output based at least on first data items and second data items of individuals in the first group;   generating a second output based at least on first data items and second data items of individuals in the second group;   determining a first security indicator for the first group relative to the second group based at least in part on comparison of the first output and the second output; and   generating user interface data configured to cause display of a user interface on a user computing device, the user interface including an indication of the first group, the second group, and the determined first security indicator.   
     
     
         11 . The computerized method of  claim 10 , wherein the first output indicates one or more of an average badge-in time or an average badge-out time. 
     
     
         12 . The computerized method of  claim 10 , further comprising:
 receiving, via input from the user interface, selection of a comparison characteristic;   determining, a third group of unique individuals each sharing the comparison characteristic;   generating a third output based at least on first data items of individuals in the third group;   determining a second security indicator for the first group based at least in part on comparison of the first output and the third output; and   updating the user interface data to indicate the first group, the third group and the determined second security indicator.   
     
     
         13 . The computerized method of  claim 10 , wherein the first common characteristic comprises badge-in time within a timespan or badge-out time within the timespan. 
     
     
         14 . The computerized method of  claim 10 , further comprising:
 generating a mapping of unique individuals within each of the first group and the second group.   
     
     
         15 . The computerized method of  claim 10 , further comprising:
 accessing expected format information indicating an expected format of data from the first data source providing the first data items or the second data source providing the second data items; and   detecting inconsistencies in a first format of the data from the first data source or a second format from the second data source as compared to the expected format.   
     
     
         16 . The computerized method of  claim 10 , further comprising:
 in response to detection of an inconsistency, obtaining the first or second data from the respective first or second data source such that the first or second data no longer has the inconsistency.   
     
     
         17 . The computerized method of  claim 10 , further comprising:
 updating the user interface data to include an indicator of the inconsistency.   
     
     
         18 . The computerized method of  claim 10 , further comprising:
 determining a first file size for the first data items or second data items;   accessing a previous file size for a previous version of the first data items or second data items;   detecting a discrepancy in size between the previous file size and the first file size; and   in response to detection of the discrepancy, obtaining the first data items or second data items from respective first or second data sources such that the first or second data no longer has the discrepancy.