Week 4: Data mining and Knowledge Discovery

‘Data mining is the process of exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules’. (Berry & Linoff 2000) In data mining, data sampling is very important. Data mining is not only automatic process but it is automatic as well as manual process which involves human interaction, because without human interaction and participation organization cannot build the software that is required for gathering the useful information for data mining. Algorithms pattern for proper interaction with organizations data mining, data warehousing is very important. In the presentation of Raman lyer, the author believes that data mining is discovered due to the major gap between disk capacity and the process ability to maintain the data. Data mining can be used for classification, estimation, segmentation, association, forecasting, text analysis and advanced data exploration. Lecturer in the lecture gives an idea about Data mining and Knowledge discovery which can be used in cross pointing the organization. It is said that data mining is the part knowledge discovery. To put in nutshell, Knowledge discovery are more than data mining. People can discover knowledge from various sources as it is and end product of a chain. It is believed that we cannot use the information unless it is not accurate or to the point, and if we cannot use the information that it is not a part of knowledge. Thus the information which is useful can only be said as knowledge. To increase the knowledge any one needs information and data. In short, data mining can also be seen as part of knowledge discovery. This is because knowledge can be gain through different methods, and data mining is one of the methods for gaining the knowledge. Thus in my opinion data mining plays an important role.