DataScope Professional extends the intuitive data visualization of DataScope Explorer with a rich set of algorithmic data mining and decision support techniques to create a powerful data mining and knowledge discovery environment suitable for a wide range of industries and applications. Using DataScope Professional, prediction and decision models can be built to compute customer value, predict customer churn, assess loan applicants, identify fraudulent transactions and many more. Additionally, the integrated Decision Support module allows decision alternatives to be ranked based on user preferences and criteria, and provides tools for evaluating and understanding the reasons behind the suggested ranking.

DataScope Professional Suite comprises DataScope Explorer base component and Predictor, Clusterer, Decision Support modules.

Product features by component:

DataScope Explorer

Flexible data input/output connectivity using ODBC and native interfaces
Data transformations using calculated data fields and converters
Multi-dimensional interactive synchronized charts
Real time 3D image rendering
Visual data query without commands
Data hierarchies and drill-down analysis
Data quality reports
Automatic correlation finder
Automatically generated natural language chart descriptions
Customizable printed reports
Flexible exports of calculated results and chart images

DataScope Predictor Module

Wizard guided model training
Data filters with custom expressions for training and test data set definition
Random sampling of data sets
Auto validation of training and test data sets
Learning from data sets containing not known (n/a) values
Visual display of models
Export models to DataScope Model Executor
PMML model export

Modeling methods supported:
	Clustering Methods: Kohonen, Shepherd, Fuzzy C-Means Classification Methods: Decision Tree, Rule Set Instance-based Methods: K-Nearest Neighbor (k-NN) Regression Methods: Neural Network, Linear Regression, Quadratic Regression, Trend Analysis with Non-Linear Regression, Support Vector Machine, Logistic Regression

DataScope Clusterer Module

Dynamic recalculation of clusters on data changes
Flexibly reusable cluster results
Tight integration into DataScope Explorer
Clustering methods supported: Kohonen, Shepherd and Fuzzy C-Means

DataScope Decision Support Module

Ranking of alternatives based on many contradictory decision criteria
Offers visual tools for evaluating the decision results and ranking in detail
Capable of learning decision hierarchies from existing ranking results
Tight integration into DataScope Explorer