SQL Server Analysis Services

Microsoft® SQL Server™ Analysis Services is a middle-tier server for online analytical processing (OLAP) and data mining.
The Analysis Services system includes a server that manages multidimensional cubes of data for analysis and provides rapid client access to cube information. Analysis Services organises data from a data warehouse into cubes with pre-calculated aggregation data to provide rapid answers to complex analytical queries. Analysis Services also allows you to create data mining models from both multidimensional (OLAP) and relational data sources. You can apply data mining models to both types of data. PivotTable® Service, the included OLE DB compliant provider, is used by Microsoft Excel and applications from other vendors to retrieve data from the server and present it to the user, or create local data cubes for offline analysis.

SQL Server 2005 Analysis Services consists of two major, and complementary, pieces of functionality: On-Line Analytical Processing (OLAP) and Data Mining.
Online analytical processing (OLAP) is typically defined as the processing and analysis of shared multidimensional data. In practice, OLAP systems analyse data drawn from large, low-transaction, high-latency relational databases, such as data warehouses. The purpose of such analysis is to aggregate and organize business information into a readily accessible, easy to use multidimensional structure.

OLAP systems store some or all of this aggregated information either within tables in a relational database (also known as relational OLAP, or ROLAP, storage) or in specialized data structures in multidimensional databases (also known as multidimensional OLAP, or MOLAP, storage).

OLAP queries can be answered much more quickly than similar relational queries because the aggregations and computations have already been completed and the resulting derived values are readily available from a ROLAP table or MOLAP storage.

Microsoft SQL Server Analysis Services provides users with Real-Time OLAP – challenging the traditional view of OLAP by performing aggregations quickly enough to provide multidimensional data from low-latency data sources.

In Analysis Services, real-time OLAP represents the capability to quickly retrieve, organize, aggregate and present multidimensional data for cubes and dimensions whenever the data changes in the underlying relational data source, without requiring the cube or dimension to be explicitly processed first.