HP Matrix Operating Environment Software - Manual (Page 31)

Determining trends in Capacity Advisor
Determining trends from collected utilization data can be a challenging task. Accurate trend analysis
requires adequate historical data and an understanding of the cyclic nature of the data being
analyzed as well as any special events that might be found in the historical data.
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Trends are frequently small values, on the order of percents or fractions of a percent per month.
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The cyclic data can easily be orders of magnitude greater than the trend (heavy calculations
the day before payroll distribution, floods of users logging on after work on the East coast,
and so on).
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Special events can also be orders of magnitude greater than the trend (seasonal promotions,
once per year calculations such as taxes).
Any algorithmic analysis must be able to deal with these problems. Capacity Advisor combines
aggregation of points based on known business cycles to deal with cyclic patterns with exclusion
of points to deal with special events, to provide data for a linear regression.
Aggregation of points in business interval bins
To reduce the impact of cyclic changes in the historical data, a user-specified business period is
used to break the data into time-interval based “bins” and each bin is then represented by a single
point. The point can be the average, the peak, or the 90th percentile of the data (90% of the points
are less than the value). A bin will not be used unless the percent of points within the bin that are
valid exceeds the threshold you have specified.
IMPORTANT: A trend will not be calculated unless at least two bins with an adequate percentage
of valid points exist within the range of data being analyzed.
Choosing an appropriate business interval
It is crucial to have a significant amount of data for analysis. Choosing an appropriate business
interval with a data collection period that is long enough helps to ensure that you have enough
data for a useful analysis. For example, a business interval of 1 week and data collection period
of 1 month provides only four aggregate data points. This is insufficient to provide meaningful
results.
To improve results, for this example, use a business interval of 1 day with a data collection of 1
month to provide 30 data points, or use a business interval of 1 week with a data collection of 6
months to provide 26 data points. Modifying the business interval and/or the data collection period
gives you more flexibility in arriving at a significant amount of data for analysis.
Exclusion of data points
You can set the report period to exclude a special event or mark the time period invalid to exclude
points collected during that period from a trend analysis.
Factors that affect data validity
Within any data collection period, events can occur in the polled systems that affect the quality of
data available during that time period. Capacity Advisor identifies data points that could adversely
affect the quality and validity of report results.
Determining trends in Capacity Advisor 31