Stands for "Online Analytical Processing." OLAP allows users to analyze database information from multiple database systems at one time. While relational databases are considered to be two-dimensional, OLAP data is multidimensional, meaning the information can be compared in many different ways. For example, a company might compare their computer sales in June with sales in July, then compare those results with the sales from another location, which might be stored in a different database.
In order to process database information using OLAP, an OLAP server is required to organize and compare the information. Clients can analyze different sets of data using functions built into the OLAP server. Some popular OLAP server software programs include Oracle Express Server and Hyperion Solutions Essbase. Because of its powerful data analysis capabilities, OLAP processing is often used for data mining, which aims to discover new relationships between different sets of data.
OLAP can be performed in data warehouses that undergo frequent updates and that do not. Following are some of the examples to show how OLAP solves complex queries involving facts to be measured across companyï¿½s best-interested dimensions.
Comparison of sales (fact) of a product (dimension) over years (dimension) in the same region (dimension). How may members (fact) have opened a savings account (dimension), in USA branch (dimension), over a period (dimension) How many mortgage loans (fact) have been approved in fixed mortgage (dimension) or Adjustable Rate Mortgage (dimension) in New York City (dimension), over a period (dimension) What is the total sales value (fact) of a particular product (dimension) in a particular grocery store (dimension), over a period (dimension) What is the amount spent (fact) for a particular product promotion (dimension) in a particular branch (dimension) or in a particular city (dimension), over a period (dimension)
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