OLAP has evolved as users' needs for data analysis have grown. It provides executives, analysts and managers with valuable information via a " slice, dice and rotate" method of end user data access, augmenting or replacing the more complicated relational query. This slice and dice method gives the user consistently fast access to a wide variety of views of data organized by key selection criteria that match the real dimensions of the modern enterprise. OLAP performs multidimensional analysis of enterprise data including complex calculations, trend analysis and modeling. Derived from end-user requirements, OLAP enables end-users to perform ad hoc analysis of data in multiple dimensions, thereby giving them the insight and understanding they need for better decision making.
OLAP server technology is the key to high performance analytical use of large databases. Its added intelligence about the structure and organization of the data, as compared with flat, detailed relational tables, makes an OLAP server more responsive to end user requests while also eliminating SQL-style queries. An OLAP server may physically stage the processed multi-dimensional information to deliver consistent and rapid response times to end users, or it may populate its data structures in real-time from relational or other databases, or it may offer a choice of both.
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