A control chart uses data from a specified period to derive average and upper and lower control values. For this example we are using some CPU utilization data from a UNIX machine collected over the 4 month period January through April 2011 and delivered in a CSV file. The baseline period is January, from which we calculate average values and standard deviations for each clock hour. We can then plot our control chart and compare successive month’s average with the control to see a clear picture of change.
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Step 1 - Import the CPU utilization data.
The following dialog shows the table definition selecting the “Delimited text file” source type. Specify a name and folder and choose the source type.
Here we see the text file definition, all that is required is the filename and a specification of the date time format.
Step 2 – Import and view the data
This Window shows the main Captell dialog with the task importing the data
And here a view of the imported data; during the import of the data Captell automatically determines correct data types.
Step 3 – Create a query to calculate the base line
This query calculates the average and average +/- 2 standard deviations for data from January.
The query output.
Step 4 – Create a query to summarise single months data
This query calculates the average CPU for each hour throughout the month selected by the Captell parameter ‘Data\Month’.
The query output:
Step 5 – Create a chart to combine the two queries
This chart shows the baseline average CPU utilisation and upper control limit along with the average values from the current month. Captell’s ability to plot data from different sources, in this case the baseline data and the data from the new month makes reporting quite easy. The blue line with the square symbols shows the average hourly data for March, well within the control limit and all hourly values below the baseline average.
Step 6 – Change the parameter to compare a different month
Here we can see the parameter changed to April and the resultant chart. The blue line with the square symbols shows the average hourly data for April, mostly above the upper control limit and all but one hour above the January mean, indicating a substantial increase in utilization.
(Posted with the Adrian's Heald permission)