Data Warehousing and Mining Essay Example | Topics and Well Written Essays - 4500 words

Data Warehousing and digging - Essay ExampleThis study will discuss the concept of information mining in detail. This paper will discuss the important aspects, techniques and algorithms of data mining. This paper will also assess the market applications of data mining. DATA MINING Data mining is a technique which is used to evaluate business or corporate data from a target source and after that turn that data into valuable and useable information. This corporate information is normally employed to facilitate a business to raise profits, reduce press expenditure in specific business areas. Moreover, the main purpose of data mining applications is to recognize and take- by standardised business configuration enclosed in a given set of corporate data (Bradford, 2011). significant DATA MINING TECHNIQUES This section outlines some of the prime and important data mining techniques. Some of the main techniques are presented below Neural Networks/Pattern Recognition Neural Networks ar e utilized in a blackbox style. In this technique, an individual produces a set of data for testing purpose, which allows the neural network to find out traffic patterns found on the identified results, then for these data permits the neural network imprecise on wide amounts of data provided. ... Memory Based Reasoning This technique can offer same results which can be achieved from neural network however the working of this technique is different from neural networks. In addition, the memory based reasoning searches for closely related type of data, rather than considering similar working patterns (Chicago Business Intelligence Group, 2011) and (Han & Kamber, 2006). clump Detection This is a standard technique of data mining which is used to assess the relationship betwixt market and business transaction data because it utters associations from data patterns. Mainly, this method discovers associations in clients or product or anywhere we desire to discover interaction in data (Chicago Business Intelligence Group, 2011) and (Han & Kamber, 2006). Link depth psychology This is an early(a) method for relating similar business records. However, this method is not utilized extensively on the other hand, a number of methods and software applications have been built on the basis of this technique. Since its name states, this technique attempts to discover associations, either in dealings, various products, consumers, etc. as well as reveals those associations (Chicago Business Intelligence Group, 2011) and (Han & Kamber, 2006). visual percept This method of data mining facilitates the users to recognize their data. In this scenario, visualization is used to create the association from school text established to visual/graphical arrangement. In addition, various other techniques such as rule, decision tree, pattern visualization and cluster facilitate users to observe data associations rather than reading the associations. Moreover, a lot of right on data mini ng systems have taken effective actions for enhancing their