Abstract: A device may receive time series data from one or more data sources. The device may pre-process the time series data to generate a respective time series chart for multiple classifications included in the time series data. The device may randomly select a pair of respective time series charts and a correlation detection technique after pre-processing the time series data. The device may determine a correlation for the pair of respective time series charts based on using the correlation detection technique. The device may determine a score for the pair of respective time series charts based on the correlation of the pair of respective time series charts. The score may indicate an extent to which the pair of respective time series charts is correlated with each other. The device may perform one or more actions after determining the score for the pair of respective time series charts.

Abstract: A device may process configuration data to identify category data that identifies possible categories of data included in the configuration data. The device may process the category data, after identifying the category data, using a natural language processing technique to generate a set of terms to be processed using an artificial intelligence module. The device may utilize the artificial intelligence module to process the set of terms to predict a set of configuration actions to be performed with respect to the configuration data and to determine an order in which to perform the set of configuration actions. The artificial intelligence module may be associated with translating the configuration data into a computer-readable form. The device may generate an execution script based on the set of configuration actions or the order in which to perform the set of configuration actions. The device may perform the set of configuration actions.

Abstract: A device may process configuration data to identify category data that identifies possible categories of data included in the configuration data. The device may process the category data, after identifying the category data, using a natural language processing technique to generate a set of terms to be processed using an artificial intelligence module. The device may utilize the artificial intelligence module to process the set of terms to predict a set of configuration actions to be performed with respect to the configuration data and to determine an order in which to perform the set of configuration actions. The artificial intelligence module may be associated with translating the configuration data into a computer-readable form. The device may generate an execution script based on the set of configuration actions or the order in which to perform the set of configuration actions. The device may perform the set of configuration actions.

Abstract: A device may receive time series data from one or more data sources. The device may pre-process the time series data to generate a respective time series chart for multiple classifications included in the time series data. The device may randomly select a pair of respective time series charts and a correlation detection technique after pre-processing the time series data. The device may determine a correlation for the pair of respective time series charts based on using the correlation detection technique. The device may determine a score for the pair of respective time series charts based on the correlation of the pair of respective time series charts. The score may indicate an extent to which the pair of respective time series charts is correlated with each other. The device may perform one or more actions after determining the score for the pair of respective time series charts.