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First Look – Rapid Insight Analytics


Rapid Insight was founded 10 years ago to develop tools that were easier for analysts to use to quickly extract meaning from data. Rapid Insight has been focused in higher education until recently and is expanding into fund raising and other areas. Rapid Insight Analytics is a pure data mining or predictive analytic workbench designed to support directed data mining using the maximum amount of automation.  To complete the analytic workbench, Rapid Insight Veera enables users to prepare analytic datasets.    Desktop versions are available for both products and a client-server version is available for Veera.

Veera is thus the first tool used in most analytics efforts. It is data agnostic and allows data to be pulled from multiple data sources of multiple types. Having established some connections to data sources (database, text files, Excel etc), the user can view the data structures in these sources and access them. Many jobs can then be managed, each containing a set of data sources and a visual workflow. These jobs can handle the usual kinds of tasks like filtering, cleansing, aggregation, de-duplication, merges, transformations etc. These jobs can output files suitable for the Rapid Insight Analytics workbench, write transformed data back to the database, score records using an existing model and so on.  When running against data in a database, Veera will do as much as it can in-database by generating SQL for filters, sorts, aggregations etc.

Rapid Insight Analytics’ projects start with an analytic dataset. The tool automatically assesses the variable types (continuous, binary etc) as well as missing values. It displays a wizard interface that shows the various stages of model building – variable statistics, data analysis, univariate and multivariate analysis, automated mining, variable creation, various kinds of analysis and then modeling, model comparison, what-if and reporting. Each tab within the wizard is a simple interface with many reporting and visualization tools at each level. A custom report can be assembled for a project from these various graphs – the graphs can be added to a set as they are viewed and that set can be turned into a report or exported to PPT.

The automated interface assesses the variables and finds those that are statistically related to the target variable. The user can then review each variable to see what kind of relationship, how strong a relationship etc. These graphs too can be added to the set for reporting.

The modeling tab allows logistic and OLS regression analysis. Predictive analytic models can be built automatically where each variable is assessed, transformed (bin values, use logs instead of raw values etc) and added to the model until no more predictive power is found. This can be done in a single automated step or the user can walk through the various steps manually, using features that suggest the next most suitable variable.

Models can be named and saved and then exported as a Rapid Insight scoring model file that can be used in a Veera workflow for scoring. Veera can also be used to set up processes to test model performance on an ongoing basis (i.e. monthly, weekly, daily) for model monitoring.

Rapid Insight is one of the vendors listed in our Decision Management Systems Platform Technologies report.


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