Improving Decision Support Systems with Data mining, Data warehousing, OLAP and OLTP Technologies (International Journal of Engineering and Computer Science, 2017)
: Rapidly changing markets and global competition require up-to-date, high-quality and complete information for decision support. Data mining, data warehousing, on-line analytical processing (OLAP), on-line transaction processing (OLTP) are important elements to support decision making process which has increasingly become a focus of the database industry. This paper provides a review of data mining, data warehousing, OLAP and OLTP technologies, with an emphasis on the components of Data warehouse architecture. A "data warehouse" is an organization-wide snapshot of data, typically used for decisionmaking. The use of data mining to facilitate decision support can lead to an improved performance of decision making. OLAP technology is used to perform complex analysis of the data in a data warehouse. OLTP technology is used to perform updates on operational or transactional systems. Online Transaction and Processing helps and manages applications based on transactions involving high volume of data. Decision Support System is a computer based information system designed to facilitate the decision making process of semi structured tasks. DSS systems and warehouses are typically separate from the on-line transaction processing (OLTP) system. Unlike a traditional relational database model or On-Line Transactional Processing (OLTP) system, an OLAP system is optimized to provide data to end users in a meaningful format through a Decision Support System (DSS) Application.