Para-Intelligence brings in two paradigm shifts over conventional Business Intelligence:
Data Analysis
Data Visualization
Examples
In this example, the user analyzed the KPIs by two dimensions simultaneously. The user was able to identify the external
factors that impacted the KPIs by each dimension. This analysis helped the user in identifying the exceptions, so that opportunities for new revenue generation could
be identified.
in this example, the user analyzed the KPI by state and month and identified different factors that impacted the KPI.
Different world events and local events were displayed that impacted the KPIs.
While the leading BI vendors provide the ability to analyze the data by only one dimension, this analysis gives the
ability to split the data by three dimensions simultaneously. In this example, the user analyzed the KPI by three dimensions and figured out what is common between
all the best performers.
In this example, the user analyzed the KPI by two dimensions simultaneously, and identified some important patterns
The user realized that the revenues from all industries are seasonal, except for one industry. Also, different industries hit their peak at different times.
In this example, the user analyzed the KPI by two dimensions simultaneously and the fluctuations by a third dimension
are animated. This animation has revealed some important insights.
In this example, the user analyzed the KPI by two dimensions simultaneously in one compartment, and split the KPIs by
another dimension in the second compartment. Large volumes of data was displayed using a birds eye view. Then, different rich patches were selected to figure out
why the KPI is high in those patches.
In this example, the user was able to find all the factors that impact the KPI and the degree of impact. For each factor,
supporting data could be displayed.
This analysis helps in identifying Cannibals and Uplifters by one dimension with respect to another dimension. In this
example, the user was able to do the friend products with respect to industry.
