Sales could be viewed in the dimensions of product model, geography, time, or some additional dimension.pproaches to how data is stored and the user interface vary. A multidimensional database (MDB) is a type of database that is optimized for data warehouse and online analytical processing (OLAP) applications.For example, sales could be viewed in the dimensions of product model, geography, time, or some additional dimension. In multi-dimensional analysis, data entities such as products, regions, customers, dates.
In multidimensional databases, the number of data views is limited only by the database outline, the structure that defines all elements of the database. Users can pivot the data to see information from a different viewpoint, drill down to find more detailed information, or drill up to see an overview. This section introduces the concepts of outlines, dimensions, and members within a multidimensional database. If you understand dimensions and members, you are well on your way to understanding the power of That is, multidimensional database systems offer an extension to the relational system to provide a multi-dimensional view of the data (Rand). For example, in multi-dimensional analysis, data entities such as products, regions, customers, dates etc. may all represent different dimensions. A dimensional database is one which, rather than representing data in multiple relations (as a relational database does), represents key data entities as Cubes contain all the dimensions on which users base their analyses of fact data. An instance of a database dimension in a cube is called a cube dimension and relates to one or more measure groups in the cube. A database dimension can be used multiple times in a cube. The relational implementation of the multidimensional data model is typically a star schema, as shown in Figure 2-2, or a snowflake schema. A star schema is a convention for organizing the data into dimension tables, fact tables, and materialized views. In Oracle Database, you can define a logical multidimensional model for relational tables using the OLAP Catalog or AWXML, as described in Chapter 5. The metadata distinguishes level columns from attribute columns in the dimension tables and specifies the hierarchical relationships among the levels. A database dimension is a collection of related objects, called attributes, which can be used to provide information about fact data in one or more cubes. For example, typical attributes in a product dimension might be product name, product category, product line, product size, and product price. An instance of a database dimension in a cube is called a cube dimension and relates to one or more measure groups in the cube. A database dimension can be used multiple times in a cube. An Analysis Services database is a collection of data sources, data source views, cubes, dimensions, and roles. Optionally, an Analysis Services database can include structures for data mining, and custom assemblies that provide a way for you to add user-defined functions to the database. Deploy an Analysis Services project from SQL Server Data Tools (SSDT) to a designated instance of Analysis Services. This process creates an Analysis Services database, if a database with that name does not already exist within that instance, and instantiates the designed objects within the newly created database. Teradata. 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 database s. 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. An OLAP cube is a term that typical refers to multi-dimensional array of data. OLAP is an acronym for online analytical processing, which is a computer-based technique of analyzing data to look for insights.  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 Key to OLAP systems are multidimensional databases, which not only consolidate and calculate data; but also provide retrieval and calculation of a variety of data subsets. A multidimensional database supports multiple views of data sets for users who need to analyze the relationships between data categories. Slicing the database in different ways gives you different perspectives of the data. This section introduces the concepts of outlines, dimensions, and members within a multidimensional database. If you understand dimensions and members, you are well on your way to understanding the power of
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