A system, comprising: a processor; a computer-readable storage device; a report database; and a reporting service, wherein the reporting service comprises processor-executable instructions stored on the computer-readable storage device, wherein the instructions, when executed by the processor, configure the reporting service to: receive time-series data, wherein the time-series data is associated with a process control system, and wherein the time-series data represents one or more values of a process control tag of the process control system over an interval of time; apportion the retrieved time-series data into a plurality of sub-intervals, wherein the plurality of sub-intervals comprise the interval of time, and wherein each sub-interval includes a predetermined number of individual data values sampled from the time-series data; determine a minimum data value of the individual data values of each sub-interval; determine a maximum data value of the individual data values of each sub-interval; execute an entropy calculation of the individual data values of each sub-interval; scale the entropy of each sub-interval based on the determined minimum and maximum data values thereof; detect that one or more sub-intervals are anomalous relative to an expected value by performing a statistical analysis on the scaled entropy value for each sub-interval; and publish at least one report indicative of the detected anomalous sub-intervals into the report database. a processor; a computer-readable storage device; a report database; and a reporting service, wherein the reporting service comprises processor-executable instructions stored on the computer-readable storage device, wherein the instructions, when executed by the processor, configure the reporting service to: receive time-series data, wherein the time-series data is associated with a process control system, and wherein the time-series data represents one or more values of a process control tag of the process control system over an interval of time; apportion the retrieved time-series data into a plurality of sub-intervals, wherein the plurality of sub-intervals comprise the interval of time, and wherein each sub-interval includes a predetermined number of individual data values sampled from the time-series data; determine a minimum data value of the individual data values of each sub-interval; determine a maximum data value of the individual data values of each sub-interval; execute an entropy calculation of the individual data values of each sub-interval; scale the entropy of each sub-interval based on the determined minimum and maximum data values thereof; detect that one or more sub-intervals are anomalous relative to an expected value by performing a statistical analysis on the scaled entropy value for each sub-interval; and publish at least one report indicative of the detected anomalous sub-intervals into the report database. receive time-series data, wherein the time-series data is associated with a process control system, and wherein the time-series data represents one or more values of a process control tag of the process control system over an interval of time; apportion the retrieved time-series data into a plurality of sub-intervals, wherein the plurality of sub-intervals comprise the interval of time, and wherein each sub-interval includes a predetermined number of individual data values sampled from the time-series data; determine a minimum data value of the individual data values of each sub-interval; determine a maximum data value of the individual data values of each sub-interval; execute an entropy calculation of the individual data values of each sub-interval; scale the entropy of each sub-interval based on the determined minimum and maximum data values thereof; detect that one or more sub-intervals are anomalous relative to an expected value by performing a statistical analysis on the scaled entropy value for each sub-interval; and publish at least one report indicative of the detected anomalous sub-intervals into the report database.