This post brings forth to the audience, few glimpses (strictly) of insights that were obtained from a case of how predictive analytic’s helped a fortune 1000 client to unlock the value in their huge log files of the IT Support system. Going to quick background, a large organization was interested in value added insights (actionable ones) from thousands of records logged in the past, as they saw both expense increase at no higher productivity.
The first graph (below one) is a time series calendar heat map adopted from Paul Bleicher, shows us the number of tickets raised day-wise over every week of each month for the last year (green and its light shades represent less numbers, where as red and its shades represent higher numbers).
Herein, if one carefully observe the above graph, it will be very evident for us that, except for the month of April & December, all other months have sudden increase in the number of tickets raised over last Saturday’s and Sunday’s; and this was more clearly visible at Quarter ends of March, June, September (also at November which is not a Quarter end). One can think of this as …read more
Source:: r-bloggers.com