HierCube OLAP library for VCL 4.49 - Effective OLAP components for VCL-developers

HierCube OLAP library for VCL

HierCube OLAP library for VCL: HierCube Library is a set of VCL components designed to create fast, handy, and powerful OLAP-applications in different IDE. The library has its own OLAP-engine made using MOLAP-principle, and allows you making OLAP-views "on the fly", not wasting time and memory for intermediate calculations. Calculations performance doesn't depend on the cube capacity and the depth of hierarchical dimensions. For example, one million records fact table is processed for less than a second. No OLAP server required. Main features: - 100% Unicode support - "Star" or "Snowflake" schemas support - Hierarchical dimensions of any nesting level, defined with "Parent-Child" relations - Several flat dimensions grouped into a hierarchical one (composite or multilevel dimension). - Dimension filters: allows to exclude any members from the current OLAP-view - Dimension groups: allows to gather any members into a single group during. - History of OLAP-views: allows "undo", "redo" operations during OLAP-analysis - Three types of calculated summaries: see data that you really want. - Different aggregate functions and sub-functions: using different functions to display cube data. Sub-functions display the final result in different ways like displaying % value instead of the function value. - Supersaturated cubes: no need to group records in the SQL-queries. - Saving/Restoring: allows to save all cube and/or all OLAP-views in a disk file and restore it back later on. - Fact table editing: allows to use HierCube library to create cross tabulated tables. - Displaying current OLAP-slice in a diagram. - Dimension attributes: displaying additional information given from the dimension table from any member. - No standard problems of "sparse" multidimensional cubes like "database explosion" or "cube sparsity". - Vast export functionality: copying to Clipboard, exporting in the most common formats: PDF, RTF, HTML, XLS, CSV, BMP, WMF, and other. - Easy localization.