RayQ Functions






Functions

 

Data Source:

Native Sybase IQ and Sybase RAP access
 
Native Orcale access
 
ODBC-driver for server based databases
 
Database module with graphical editor to easiy generate SQLqueries
 
Join-module with graphical editor to join or filter tables within RayQ
   
 
Union-module to join tables from different sources
 
Data generator to generate number series or random numbers (standard distribution,
   white noise)
 
Client Data Import module for the quick import of tables from local files or serverbased
  databases
 
Client Data Import module for the quick import of text from local files
 
simplified Datasource-Module for quick access to different external data sources

 

 

Container:

Aggregation of Analysis for further processing to achieve higher clarity or to catalog
  analysis

 

 

Automation:

Timer (time triggered starter for modules or complete analysis)
 
Trigger (for oracle database) (event triggered starter for modules or complete
  analysis)
 
Socket Listener (event triggered starter for modules or complete analysis based on
  an external event)

 

 

Data Export:

Client Data Export: HTML, XML, ASCII (CSV), Excel (XLS)
 
Client Graphic-Export: JPEG, BMP
 
Server Data Export of HTML, XML, ASCII (CSV), Excel (XLS) for automatic
  subsequent processing e.g. on a Webserver
 
Optimized Server Export Format optimized for analysis (RQD) to include self generated
  tables as data sources

 

 

 

Data  
Manipulation:

Group Mark (generated form marked, user defined groups of data sets new tables)

 

 

Methods for Analysis:

Neuronal network based on Cohonen- Algorithms for Cluster analysis and grouping
 
linear and reciprocal Transformation
 
Root-Transformation
 
logarithmic Transformation
 
Box-Cox-Transformation and Arc-Sinus- Transformation
 
Z-Transformationen
 
linear and square (multiple) Regression analysis
 
Correlation (generates a correlation matrix based on selected columns)
 
Box-Plots (graphical outliers analysis)
 
Floating Average
 
Grouping (grouping and aggregation)
 
Base Table Statistics (provides Minimum, Maximum, Average, standard deviation and
  Variance)
 
K-Means (iterative cluster method)
 
Quantiles (calculates empirical and theoretical Quantiles)
 
Chi-Square (distribution test, to distinguish real dependencies from random ones)
 
Tokenizer to break down Strings of discretionary columns according to defined criterion
  in existing sub strings
 
Token information to compare strings of discretionary rows with a list of sub strings.
 
Token Matrix as extension of Tokenizer and Token Information
 
variety of aggregation functions (Group, Pivot, Windowed Aggregation)
 
ANOVA (Variance analysis)
 
Sorting
 
Sim Analysis to determine text similarities according to the Levenstein and Fuzzy N-Gram method

 

 

Functional
  
Programming:

Formulas with extensive mathematic functional library
 
Functions for text manipulation and ligical operations

 

 

Visualisation:

Tables
 
2D-Graphic: Scatter, Box-Plot, Histogram
 
3D-Grafik: Surface, Scatter, Box-Plot, Histogram
 
Matrix View (shows internal 2 dimensional tables)
 
Pivot (generates a Pivot-Table from discretionary data sources with aggregations (Sum, Min
  Max, Average, Quadratical Sum, Quadratical Average, Count, Variance, Standard Variance)