Once the sole domain of expensive scientific computers, parallel processing has plunged in price, and in response commercial applications have proliferated. It now replaces many mainframe systems for online transaction processing and online analytical processing, including decision support. A parallel computer paired with a parallel database engine increasingly is touted by vendors, analysts and users as the preferred solution for the rapid access, flexible queries, modeling and analysis needed in decision support systems. It finds many ready uses. A stock trader who can analyze derivatives faster than competitors makes more money.
Large retailers can study the buying trends of groups or individuals.
Banks can detect credit card fraud. Airlines can analyze travel patterns. Pharmaceutical companies can tailor sales pitches to individual doctors based on their prescription writing patterns. Because decision support applications like these are mission-critical, parallel processing earns consideration. Before getting into the technical details, an organization should identify its database and data query needs.