859 results about "Multidimensional data" patented technology

A graphical condition builder is provided that presents a graphical representation of a search query. In an embodiment, the graphical condition builder presents a graphical and numerical preview indicating the size of the expected query results set. In an embodiment, a graphical preview is provided that includes graphical preview portions having a shape suggestive of a funnel. In an embodiment, the graphical condition builder supports formulating queries for both relational and multidimentional databases. In an embodiment, the graphical condition builder displays a textual indication of the type of logical operation being performed. In an embodiment, the graphical condition builder determines the type of logical operator to apply depending on the relative location of icons representing filter objects. In an embodiment, order dependent filters are available to the user. In an embodiment, the search query is represented by query steps, and multiple filter objects may be contained in each query step.

A method is provided for qualifying and analyzing business intelligence. At a first part of a data management system receives first, second and third streams of data. The first stream is client provided source data, the second is public source data and the third is data management system internal data previously collected and managed source data in the data management system. The three streams of data are organized into items and their attributes at the data management system. The source data is transformed at a data warehouse where it becomes normalized. Logic is applied to provide multi-dimensional analysis of transformed source data relative to a scale for at least one business intelligence. The data warehouse includes updated data from the multi-dimensional analysis. A user interface communicates with the data management system to create statistical information that illustrates impact over time and value.

A Relational Database Management System (RDBMS) having any arbitrary structure is translated into a multi-dimensional data model suitable for performing OLAP operations upon. If a relational table defining the relational model includes any tables with cardinality of 1,1 or 0,1, the tables are merged into a single table. If the relational table is not normalized, then normalization is performed and a relationship between the original table and the normalized table is created. If the relational table is normalized, but not by dependence between columns, such as in the dimension table in a snowflake schema, the normalization process is performed using the foreign key in order to generate the normalized table. Once the normalized table is generated, OLAP measures are derived from the normalized relational table by an automated method. In addition, OLAP dimensions are derived from the normalized relational table and the results of the OLAP measures derivation by an automated method according to the present invention. According to an aspect, it is possible to associate a member of a dimension to another member of the same or another dimension. According to another aspect, it is possible to create a new dimension of analysis, the members of which are all the different values that a scalar expression can take on. According to yet another aspect, it is possible to access the various instances of a Reporting Object as members in an OLAP dimension. According to the yet another aspect, it is possible to apply opaque filters or a combination of them to the data that underlies analysis.

The invention relates to data warehouses and the ability to create and maintain data cubes of multi-dimensional data. More specifically, the invention pertains to data cube architectures that permit significant reduction of storage, exhibit very efficient retrieval and provide a very efficient incremental update of the data cubes.