Mapping of an RDBMS schema onto a multidimensional data model

• US 7,181,440 B2
• Filed: 07/26/2004
• Issued: 02/20/2007
• Est. Priority Date: 04/03/2000
• Status: Expired due to Term

• Current Assignee: Business Objects Incorporated (SAP SE)
• Original Assignee: Business Objects SA (SAP SE)
• Inventors: Polo-Malouvier, Ricardo, Biestro, Henri, Cras, Jean-Yves
• Primary Examiner(s): ALAM, SHAHID AL
• Application Number:
  US10/899,862
• Publication Number:
  US 20050015360A1
• Time in Patent Office: 939 Days
• Field of Search: 707/2, 707/3, 707/10, 707/100, 707/103.R, 707/200, 707/101, 707/102, 715/501.1, 709/201, 709/203, 709/224, 709/232, 702/62
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2428 Query predicate definition using graphical user interfaces, including menus and forms G06F16/2423 takes precedence
• CPC Class Codes: G06F 16/283 Multi-dimensional databases or data warehouses, e.g. MOLAP or ROLAP
• CPC Class Codes: Y10S 707/99932 Access augmentation or optimizing
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99944 Object-oriented database structure
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

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.

Claims

1. A method of translating a universe data source into a multi-dimensional data model, the method comprising:

accessing a universe data source operating as a semantic layer between a user and a database, wherein the universe data source includes classes and objects, where the objects map to data in the database;

mapping each dimension from the universe into a corresponding dimension in the multi-dimensional model;

creating a single level for each dimension in the multi-dimensional model; and

assigning a default member to each dimension in the multi-dimensional model.

2. A method as in claim 1, further comprising:

creating a member in the multi-dimensional model corresponding to each member in the universe.

3. A method as in claim 1, further comprising:

when the universe contains one or more measures, creating a measure dimension in the multi-dimensional model.

4. A method as in claim 3, further comprising:

for each measure in the universe, creating a corresponding measure within the measure dimension of the multi-dimensional model.

5. A method as in claim 3 wherein a name of the measure dimension within the multi-dimensional model is localizable.