Abstract: A system, method, and computer-readable medium are disclosed that may generate staging data independently from the execution of control scripts, which process the staging data, improving the quality, efficiency, and speed of data processing systems. The staging data can be independently loaded, validated, and utilized across multiple control scripts, reducing redundancy in the loading of data and the overhead of executing separate data processing for each control script. The control scripts can be automatically validated, such as by verifying expected output data ranges. Additionally, the complexity of the control scripts can be reduced as the loading of data is not performed by the control scripts. The controls scripts can generate a variety of output data, such as an indication of impacted accounts, and provide notifications based on the output data. A variety of machine learning classifiers may automatically generate the staging data and validate the staging data and/or output data.

Abstract: Aspects described herein generally improve the quality, efficiency, and speed of data processing systems by generating staging data independently from the execution of control scripts which process the staging data. The staging data can be independently loaded, validated, and utilized across multiple control scripts, reducing redundancy in the loading of data and the overhead of executing separate data processing for each control script. The control scripts can be automatically validated, such as by verifying expected output data ranges. Additionally, the complexity of the control scripts can be reduced as the loading of data is not performed by the control scripts. The controls scripts can generate a variety of output data, such as an indication of impacted accounts, and provide notifications based on the output data. A variety of machine learning classifiers can be used to automatically generate the staging data and validate the staging data and/or output data.

Abstract: A system, method, and computer-readable medium are disclosed that generate staging data independently from the execution of control scripts, which process the staging data, improving the quality, efficiency, and speed of data processing systems. The staging data can be independently loaded, validated, and utilized across multiple control scripts, reducing redundancy in the loading of data and the overhead of executing separate data processing for each control script. The control scripts can be automatically validated, such as by verifying expected output data ranges. Additionally, the complexity of the control scripts can be reduced as the loading of data is not performed by the control scripts. The controls scripts can generate a variety of output data, such as an indication of impacted accounts, and provide notifications based on the output data. A variety of machine learning classifiers may automatically generate the staging data and validate the staging data and/or output data.

Abstract: Aspects described herein generally improve the quality, efficiency, and speed of data processing systems by generating staging data independently from the execution of control scripts which process the staging data. The staging data can be independently loaded, validated, and utilized across multiple control scripts, reducing redundancy in the loading of data and the overhead of executing separate data processing for each control script. The control scripts can be automatically validated, such as by verifying expected output data ranges. Additionally, the complexity of the control scripts can be reduced as the loading of data is not performed by the control scripts. The controls scripts can generate a variety of output data, such as an indication of impacted accounts, and provide notifications based on the output data. A variety of machine learning classifiers can be used to automatically generate the staging data and validate the staging data and/or output data.

Abstract: Aspects described herein generally improve the quality, efficiency, and speed of data processing systems by generating staging data independently from the execution of control scripts which process the staging data. The staging data can be independently loaded, validated, and utilized across multiple control scripts, reducing redundancy in the loading of data and the overhead of executing separate data processing for each control script. The control scripts can be automatically validated, such as by verifying expected output data ranges. Additionally, the complexity of the control scripts can be reduced as the loading of data is not performed by the control scripts. The controls scripts can generate a variety of output data, such as an indication of impacted accounts, and provide notifications based on the output data. A variety of machine learning classifiers can be used to automatically generate the staging data and validate the staging data and/or output data.

Abstract: Aspects described herein generally improve the quality, efficiency, and speed of data processing systems by generating staging data independently from the execution of control scripts which process the staging data. The staging data can be independently loaded, validated, and utilized across multiple control scripts, reducing redundancy in the loading of data and the overhead of executing separate data processing for each control script. The control scripts can be automatically validated, such as by verifying expected output data ranges. Additionally, the complexity of the control scripts can be reduced as the loading of data is not performed by the control scripts. The controls scripts can generate a variety of output data, such as an indication of impacted accounts, and provide notifications based on the output data. A variety of machine learning classifiers can be used to automatically generate the staging data and validate the staging data and/or output data.

Abstract: Aspects described herein generally improve the quality, efficiency, and speed of data processing systems by generating staging data independently from the execution of control scripts which process the staging data. The staging data can be independently loaded, validated, and utilized across multiple control scripts, reducing redundancy in the loading of data and the overhead of executing separate data processing for each control script. The control scripts can be automatically validated, such as by verifying expected output data ranges. Additionally, the complexity of the control scripts can be reduced as the loading of data is not performed by the control scripts. The controls scripts can generate a variety of output data, such as an indication of impacted accounts, and provide notifications based on the output data. A variety of machine learning classifiers can be used to automatically generate the staging data and validate the staging data and/or output data.

Abstract: A low profile tactical illumination device includes a lightweight low profile main body having a bottom surface that includes a centrally located concave portion and a pair of Picatinny rail connectors, a plurality of forward projecting light emitting devices are disposed within the main body and a controller for operating the plurality of light emitting devices.