15. WORKLOAD CHARACTERIZATION › 15.3 Standard Output

15.3 Standard Output

Workload Characterization using Neugents technology produces
reports and simple graphs that describe the original data,
show the clusters tht are identified from this data, and
analyze the degree of fit with which these clusters
characterize the data.

The five reports and two graphs are:

o  Descriptive Statistics Report.  This report details the
   characteristics of the variables that are specified as
   criteria for the clustering analysis.

o  Cluster Performance Summary.  This report consists of
   three sections:  Clustering Executions, a summary of the
   options selected by the analyst for the study; Cluster
   Feature Contents, a list of each of the elements or
   features used for clustering, and the boundaries selected
   for determining normalcy of the data values; and Cluster
   Population Summary, which lists each cluster, its size and
   population, and an index used to indicate relative
   performance of the cluster.

o  Cluster Population Summary.  This report provides the
   resource consumption characteristics of each of the
   clusters.  For each cluster, its size and population is
   summarized and all clustering and reporting elements are
   listed, along with their respective usage values.  This
   report permits you to identify resource consumption
   patterns that may represent performance or capacity
   problems.

o  Data Value Exception Detail.  This report provides a
   detail listing of any observation that has one or more
   clustering elements that are identified as outliers.  The
   report is sequenced in the same order as is the original
   CA MICS files used as input, and can be used to further
   investigate why certain cases have been identified as
   outliers and whether or not they actually represent
   abnormal situations.

o  Sparse Cluster Population.  This report provides a listing
   of all clusters that have been identified as 'sparse' and
   their population contents.  A sparse cluster is defined
   within this application as one having less than 0.5% of
   the overall population of the study.  For example, if a
   sample of 2,000 cases were selected for analysis, then a
   sparse cluster would contain ten or fewer observations.

o  Cluster Index Analysis.  This graph depicts a measurement
   of relative performance for each cluster, by presenting an
   index calculated by Neugents technology in terms of the
   root mean square of the distances of the resource vectors
   or feature values from the cluster centroid.  The cluster
   index of each cluster is displayed in either a Block or a
   horizontal bar chart, depending on the number of clusters
   being presented.  This chart permits you to quickly access
   the overall performance of the workload characterization
   effort.

o  Cluster Population Analysis.  This graph depicts the
   population of the top "n" clusters in a PIE chart, which
   can be used to understand pictorially how the study data
   actually populated the clusters.

The following sections describe the fields, data elements,
and format of each report.

 1 - Descriptive Statistics Report
 2 - Cluster Performance Summary
 3 - Cluster Population Summary
 4 - Data Value Exception Detail
 5 - Sparse Cluster Population report
 6 - Cluster Index Analysis graph
 7 - Cluster Population Analysis graph