Comparing data series associated with two systems to identify hidden similarities between them

A system comprising:

• a sampling module configured to sample a plurality of parameters associated with a first system and a second system to yield a first set of data series and a second set of data series, respectively, each data series being associated with samples of a respective parameter;
• a repository containing a plurality of ordered transformations;
• and
• a processor configured to:
• apply, for each two respective data series having a correlation level below a specified threshold, a transformation associated with a specified order selected from the repository, such that the selected transformation is applied repeatedly to at least one of the two respective data series, wherein in each repeated application, the transformation is assigned with an increased value of a transformation parameter;
• determine, for each operational parameter, a one of the plurality of transformation parameters for which the correlation level of the two respective data series is above a specified value;
• and
• repeat the applying and the determining with a transformation that is associated with a higher order of the ordered transformations.

A computer program product, the computer program product comprising:

• a computer readable storage medium having computer readable program embodied therewith, the computer readable program comprising:
• computer readable program configured to sample a plurality of parameters associated with a first system and a second system to yield a first set of data series and a second set of data series, respectively, each data series being associated with samples of a respective parameter;
• computer readable program configured to apply, for each two respective data series having a correlation level below a specified threshold, a transformation associated with a specified order selected from a plurality of ordered transformations, such that the selected transformation is applied repeatedly to at least one of the two respective data series, wherein, in each repeated application, the transformation is assigned with a different value of a transformation parameter;
• computer readable program configured to determine, for each parameter, a one of the plurality of transformation parameters for which the correlation level of the two respective time series is above a specified value;
• and
• computer readable program configured to repeat the applying and the determining with a transformation that is associated with a higher order of the ordered transformations.

A method comprising:

• presenting a first and a second data series as a first and a second multidimensional graphic representations respectively;
• updating values of data points of at least one of the data series, in response to graphical manipulations applied to at least one of the multidimensional graphic representations, to yield updated data series;
• determining a quantitative representation of the at least one updated data series or of a relationship between the updated data series;
• and
• repeating the updating and the determining while monitoring the determined quantitative representation vis à vis respective graphical manipulations,
• wherein at least one of the presenting, the updating, the determining, and the repeating is executed by at least one processor.

A system comprising:

• a graphical user interface having a display in operative association with an input device;
• and
• a backend module having a processor and a graphic manipulations repository,
• wherein the graphical user interface is configured to present over the display, a first and a second data series as a first and a second multidimensional graphic representations respectively,
• wherein the processor is configured to:
• update values of data points of at least one of the data series, in response to graphical manipulations selected by the input device from the graphic manipulations repository and applied to at least one of the multidimensional graphic representations over the display, to yield updated data series;
• determine a quantitative representation of the updated data series or of a relationship between the updated data series;
• and
• repeat the updating and the determining while monitoring the determined correlation level vis à vis respective graphical manipulations.