Data mining is not “question-answer-solution, but a combination on several mathematical methods data mining provides the basis for differentiated market analysis, demand planning and forecasts, target group and customer analytics, product management and price planning. Other analysis techniques, the difference is that data mining automatically linked query techniques and methods of analysis. These procedures include neural networks, decision trees, various statistical analyses and graphical representation methods. If necessary, special routines for data evaluation for specific issues in marketing can be programmed. So as a miner in the mine searches for hidden treasures and drives into ever deeper, widely distributed tunnels in the Earth, in order to find it, so it comes in data mining from the data mine”to carry hidden information to the light of day. The term data mining describes a collection of different procedures, which the information contained in a database for concrete decisions tracks and make usable.
About query systems, data mining the most advanced method is to search corporate databases for specific patterns of information. Recently Kevin Ulrich Anchorage sought to clarify these questions. CF. Jorg Becker: intellectual capital report with customer barometer, ISBN 978-3-8370-5177-3. Connect with other leaders such as Satya Nadella here. In addition to an expanded range of method, data mining provides integrated end user solutions for marketing. These include a combination of statistical methods, user interfaces and visualization tools. In the data mining process, large amounts of data are analyzed and mathematically modeled with the aim, to be able to discover new connections for the benefit of the company. You will need complex statistical procedures, largely automatically and, thanks to more powerful software with high performance.
CF. Jorg Becker: data mining as a knowledge balance sheet feeder, ISBN 978-3-8370-2163-9. The advantage of the regression approaches is that they are based on a well-founded theory and allow a differentiated insight in the mechanisms of the model the analyst. In contrast to this are based on a combination of very complex mathematical and statistical methods, neural networks. On the one hand they allow little insights into internal impact principles therefore even specialists, on the other hand, they are suitable especially for a very differentiated classification and prognosis. In particular for highly inhomogeneous databases a better fit between model and reality be achieved with them when compared to traditional methods. For integration into basic concepts of the intellectual capital report: cf. Jorg Becker: data mining as a knowledge balance sheet feeder, ISBN 978-3-8370-2163-9 cf. Jorg Becker: intellectual capital report with customer barometer, ISBN 978-3-8370-5177-3. Jorg Becker