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) |
