Para-Intelligence brings in two paradigm shifts over conventional Business Intelligence:

  1. Data Analysis
  2. Data Visualization.

viewrich_paradigm_1 First paradigm shift: Data Analysis

In today’s world, the meaning of the phrase “Business Intelligence” has reduced to slicing & dicing. To develop a deeper insight into the data, corporations are relying on software products that specialize in data mining. A new job definition called “Data Scientist” has emerged. Predictive Analytics has grown into a well defined discipline. Para-Intelligence helps in fusing business intelligence, artificial intelligence, data mining, knowledge discovery, predictive analytics and situation intelligence into one software offering. Para-Intelligence encompasses several algorithms for data analysis that help in developing deeper insights.


viewrich_paradigm_2 Second paradigm shift: Data Visualization

Our research shows that a human can develop a better insight of the data with 3D visualization. A three-dimensional scene that is guided by a two-dimensional navigator makes a more profound impact on the human brain than the flat charts offered by current day BI applications. Inherently, every data has shape. Para-Intelligence helps in discovering the shape of your data and presenting it in a more consumable and analyzable manner.



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.