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Data Warehousing OLAP and Data Mining S. Nagabhushana
Publisher: to New Age International Pvt Ltd Publishers

The data warehouse is then used for reporting and data analysis. Some differences between a A data warehouse is used for Online Analytical Processing (OLAP). Data warehouses are sometimes called "OLAP" databases, which stands for "on-line analytical processing", in contrast to the more common "OLTP", or "on-line transaction processing" databases that manage data for an online storefront, a bug tracker, or a blog. - OLTP (On -line Transaction Processing) is characterized by a large number of short OLAP applications are widely used by Data Mining techniques. A typical OLTP database supports applications that and might take minutes or hours to complete. Database is just an organized collection of data. It offers a suite of open source Business Intelligence (BI) products called Pentaho Business Analytics providing data integration, OLAP services, reporting, dash-boarding, data mining and ETL capabilities. The data warehouse may also be used to analyze the data; however the actual process of analysis is called data mining. In general we can assume that OLTP systems provide source data to data warehouses, whereas OLAP systems help to analyze it. A data warehouse is a database used to store data. What is the difference between Data Warehouse and Database? Such queries will often include heavy-duty statistical processing and data mining, involving terabytes of data. Data mining implies drawing the existing data stored in data warehouses according to the necessity of the individual and using it to draw important conclusions which are going to be of great help for the functioning of the organisation. OLTP vs OLAP We can divide IT systems into transactional (OLTP) and analytical (OLAP).