OLAP processes vast queries
Online Analytical Processing (OLAP) helps to process vast queries online. Queries are multi dimensional and analytical. It is a part of business intelligence. It includes relational reporting and data mining. OLAP gives service in the area of business reporting for sales, business process management, marketing, management reporting etc. It also includes new areas like agriculture. The term OLAP is derived from another term which is OLTP (Online Transaction Processing).
OLAP contains some databases which use a multidimensional data model. It facilitates complex analytical and vast queries very fast. Some aspects are common to navigational as well as hierarchical databases. These databases are more speedier than relational databases. The result of an OLAP query is generally displayed in the matrix format. It is also called pivot format. Rows and columns of the matrix are made from the dimensions and the values are formed by the measures.
An OLAP cube is there in the core of an OLAP system. It is also called a multidimensional cube or a hypercube. Some numeric facts are there which is called measures. They are classified into the dimensions. We get measures from the records of the fact table and dimensions from the dimensions tables. A set of labels or its meta-data are meant by a measure. These labels are described by a dimension. It contains information about measure. For example a cube contains a store’s sales which is the measure and the date/time which is dimension. Each sale contains date/time label which describes that sale in more detail.
In an OLAP system dimensions can be added to the structure such as store, customer, and cashier. It is entered in a column which is added in a fact table. Its purpose is to enable the analyst to view measures along any combinations of dimensions. Basically a multidimensional structure is defined as a different relational model which uses multidimensional structures to systematize data and explain the relationship between the data. The structure is broken into cubes which store and access data in the boundaries of each cube.
Carlos Quijada is an IT professional associated with the field since the last 20 years. His core area of ecialization is programming. Besides working with one of the leading IT services, he writes about technology and its benefits.For more information you can visit OLAP.