Involve complex calculations between data elements e.g. expected profit as calculated as a function of sales revenue for each type of sales channel in a particular region. Are able to respond quickly to user requests so that users can pursue an analytical thought process without being stymied by the system. The transactions usually retrieve and update a small number of records that are contained in several distinct tables. The relationships between the tables are generally simple. A typical customer order entry OLTP transaction might retrieve all of the data relating to a specific customer and then insert a new order for the customer.
Information is selected from the customer, customer order, and detail line tables.
Each row in each table contains a customer identification number which is used to relate the rows from the different tables. The relationships between the records are simple and only a few records are actually retrieved or updated by a single transaction. Both OLAP and OLTP, have specialized requirements and therefore require special optimized servers for the two types of processing. OLAP database servers use multidimensional structures to store data and relationships between data. Multidimensional structures can be best visualized as cubes of data, and cubes within cubes of data.