An OLAP Control/Component by Radar-Soft, L.L.C.

Data sources

RadarCube supports the data warehouse structure by using several tables from the data source, which are connected to each other at that. RadarCube dimensions and measures structures allows you to most thoroughly reflect the data warehouse structure in the final OLAP-report. Unlike the products of the competitive firms, RadarCube supports such DWH structures as "star" and "snowflake", several fact tables, Parent-Child relations in the dimension tables.

In the OLAP-schema, all this is reflected in multilevel (for the "snowflake" schema) and the "Parent-Child" hierarchies. You only need to create a standard DataSet and describe all table relations and then you can and use it as a data source for RadarCube. In addition, in comparison with the only table or view, this allows you to save memory and reduce the time for the data loading.

Performance

Despite the fact that RadarCube is 100% managed, it doesn't lose in its performance to its VCL analogues: HierCube and RadarCube for VCL. The unique technology of the calculation OLAP-slices "on the fly" first implemented in HierCube and updated in RadarCube, allows calculating only data which at the moment is displayed in the Grid, no more. Such technology saves memory and strongly shortens the OLAP-slice calculation time. Thus, RadarCube easily works with the data warehouse containing up to several million records in the fact table, and still keeps the response time within a few seconds.

Using DataSet as a data source, RadarCube has an ability to fetch the data directly from the database using the IDbReader interfaces working in the "Forward only" mode. If this is the case, the OLAP-application using RadarCube roughly takes as much memory as it would have taken with fully filled DataSet without any OLAP-component.

Key features: Cube definition

• One or several tables/views /stored procedures described in a DataSet object. Also direct working with the components supporting the IDbCommand interface is possible to speed up the data fetching.
  
• A set of standard aggregation functions like Sum, Count, Distinct Count, Min, Max, Biased or Unbiased Variance, Median and so on. Custom aggregation functions are also possible.
  
• Numbers, strings or dates can be used as measure values.
  
• All entities of modern industrial OLAP-servers are supported: dimensions, hierarchies, hierarchy levels and their relations.
  
• Hierarchies of three types:
  
  
  
  • Parent-child hierarchies (both balanced and unbalanced);
    
  • Multilevel hierarchies (both regular and ragged);
    
  • Mixed from all previous types.
    
  
  
• An ability to create calculated measures, dimensions, hierarchies and hierarchy levels the fact table rows as well as from the related rows of the dimension tables, that are connected to the fact table by the foreign key.
  
• An ability to create additional calculated measures using the values of any other cube cells.
  
• Calculated members of hierarchies.
  
• Auto conversion of the DateTime fields into multilevel hierarchies. Any conversion algorithms.
  

Key features: Data visualization

• Unicode support.
  
• An ability to display several measures in the Grid at the same time.
  
• Several types of drilling down: to the nearest successor, to the next level, to the next hierarchy.
  
• Hierarchy members grouping (including multilevel and parent-child hierarchies).
  
• Separate sorting of different hierarchy levels. Ability to override any sorting method.
  
• Ascending or descending sorting based on the column values in the grid.
  
• Filtering of hierarchy members with or without applying these filters to the OLAP calculations.
  
• Auto filtering of the hierarchy members depending on their values in the grid. An ability to select some major/minor members, either according to their rank or to the Pareto principle.
  
• An ability to display in the grid not only the values of the measures but also value percentage in totals, subtotals, or grand totals.
• An ability to create your own context-sensitive rules for measure displaying.
  
• Ability to place pictures into grid cells, and automatically position picture and text within the cell, depending on the parameters defined by a programmer.
  
• A complete control over the cells contents, ability of custom drawing within the cells.
  
• Ability to change the context menus in the grid.
  
• Ability to drag hierarchy member within the grid with the mouse.
  
• Auto sizing of the cell depending on their contents.
  
• An ability to edit OLAP data directly in the grid.
  
• The IListSource interface implementation. A feature which allows OLAP Grid to be used as the data source for other components working with data (for example, Chart or export components).
  
• Flexible export to: BMP, CSV, GIF, HTML, JPEG, PDF, PNG, TIFF, TXT, XLS, XML.
  
• Easy localization.