 - A multidimensional database (MDB) is a type of database that is optimized for data warehouse and online analytical processing (OLAP) applications. Multidimensional databases are frequently created using input from existing relational databases. Whereas a relational database is typically accessed using a Structured Query Language (SQL) query, a multidimensional database allows a user to ask questions like "How many Aptivas have been sold in Nebraska so far this year?" and similar questions related to summarizing business operations and trends. An OLAP application that accesses data from a multidimensional database is known as a MOLAP (multidimensional OLAP) application.
A multidimensional database - or a multidimensional database management system (MDDBMS) - implies the ability to rapidly process the data in the database so that answers can be generated quickly. A number of vendors provide products that use multidimensional databases. Approaches to how data is stored and the user interface vary.
Conceptually, a multidimensional database uses the idea of a data cube to represent the dimensions of data available to a user. For example, "sales" could be viewed in the dimensions of product model, geography, time, or some additional dimension. In this case, "sales" is known as the measure attribute of the data cube and the other dimensions are seen as feature attributes. Additionally, a database creator can define hierarchies and levels within a dimension (for example, state and city levels within a regional hierarchy).
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Learn more about Oracle data warehousing |
| Learning Guide: Data warehousing and business intelligence: This learning guide compiles articles, analysis, tips and expert advice on basic and in-depth data warehousing and business intelligence topics. |
| Core principles of data warehouse design: This excerpt from "Database Modeling and Design: Logical Design, Fourth Edition" by Toby Teorey provides an overview of the fundamentals of data warehousing. |
| Oracle data warehousing and business intelligence guide: This learning guide compiles articles, analysis, tips and expert advice on basic and in-depth data warehousing and business intelligence topics. |
| Tip: Exposing logical attributes with virtual columns: A new feature in Oracle 11g, virtual columns, models logical attributes by exposing logical attributes while reducing object management and storage consumption. |
| Core principles of data warehouse design: This excerpt from "Database Modeling and Design: Logical Design, Fourth Edition" by Toby Teorey provides an overview of the fundamentals of data warehousing. |
| Learning Guide: Data warehousing and business intelligence: This learning guide compiles articles, analysis, tips and expert advice on basic and in-depth data warehousing and business intelligence topics. |
| Saving lives with Oracle: In the area of medical informatics, powerful tools such as Oracle Discoverer and Oracle Data Mining are improving the quality of health care and helping scientists to save lives. |
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16 Feb 2009
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