Abstract: The subject of the invention is a device for non-invasive blood glucose concentration measurement, comprising a central control system (4), a scattering module (1) and an electronic control system (2) of the scattering module (1) connected to it. The electronic control system (2) of the scattering module (1) is connected to the central control system (4). The scattering module (1) comprises a detection element (28) and a coherent radiation source (14) connected to the control system of the coherent radiation source (13). The device is characterized in that it further comprises a transmission module (7) and an electronic control system (8) of the transmission module (7) connected to it, connected to the central control system (4). The device further comprises a proximity sensor (12), connected to the central control system (4). The device comprises an optical fiber probe (11) comprising an emitting optical fiber (15) and a measuring optical fiber (18).

Abstract: In an example embodiment, a machine-learned model is trained to predict a region and industry for an organization. This region and industry information can then be used as part of a data enrichment process where data regarding the organization is “tagged” with the predicted industry and region information, allowing for a benchmarking tool to readily group organizational data by region and/or industry for meaningful comparison. This allows or the benchmarking tool to scale, as without the machine-learned model it would be necessary for a human to assign a region and industry to each organization missing that information, which may work for small numbers of organizations but would be impractical for large numbers of organizations.