Using DataScope Automation Suite, once a data mining project has been completed, it can be repeated any time on a scheduled basis on the latest database contents with no personal assistance. The analysis results can be exported back to the corporate database or delivered onto the corporate Intranet, utilizing the flexibility of automatically generated HTML or XML pages hence generating up-to-date reports on a weekly, daily or hourly basis. Events can also be monitored triggering email alerts and other actions or applications.

DataScope Automation Suite can be integrated into complex analysis/reporting systems and can run on servers unattended. It can accept data and commands from other applications using standard information exchange and scripting methods.

DataScope Automation Suite comprises all DataScope modules and thus offers a complete data analysis solution. These modules are DataScope Explorer base component and Predictor, Clusterer, Decision Support, Data Map, Reporter, AutoExporter, Monitor, Integrator 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

Dinamic 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

DataMap Module

Make import of data into DataScope simple using predefined database schema
Data import from multiple tables of a relational database
Predefine data transformations and data hierarchies, create new virtual calculated fields
Apply field name aliases

Reporter Module

Generate reports in HTML format
Export data and calculated results into XML
Publish reports on Intranet or Internet
Highly customizable appearance
CSS style sheet support
(See sample report)

AutoExporter Module

Schedule database and HTML exports or allow triggering them from other applications
Runs DataScope unattended on servers

Monitor Module

Scheduled data-refresh from database and automatic recalculation of the analysis
Monitor and detect events expressed by the data or specified by functions
Send messages, email, trigger external programs

Integrator Module

External control of DataScope through scripts and command line interfaces
CGI script interface for integration into websites
Synchronize DataScope processes with database actions\events