From Data Mining to Knowledge Discovery in Databases
Usama Fayyad, Gregory Piatetsky
http://www.aaai.org/ojs/index.php/aimagazine/article/viewArticle/1230
Fayyad gives a complete insight into the process of data mining. The article gives a step y step utilization of data mining process and the effect it has on archiving processes. The article argues about the need for embracement of data mining techniques based on the popularity of the process. It gives the accumulation of anarchized information as an urgent pointer to need for introduction of new data mining exercises that will ensure the current challenges are fully addressed. Based on the article, the aspect of data mining is given a new face through its step by step analysis. The article features works from renowned data mining experts who argues that the current trend in data mining is inadequate. It inadequacy is viewed as the main reason behind the failure of the process in certain sectors of the community. The article is fully technical and it offers chances for one to learn the process in a step by step process that is included in the body of the text. The historical perspective of the data mining process has also been given prominence in the article. Fayyad has attributed the current stalemate in information processing to lack of adequate knowledge on the process of data mining. The argument presented by the article is that the process has been widely ignored by the masses who proffered carrying out manual archiving. This is pointed out as the major setback in the improvement of data mining process. Another point that comes out in the article is that the rate of development in the information exchange industry is becoming a challenge to data mining. The article summarizes the current developments in the IT industry that seen too complex for the developers of data mining software. The authors feel that it is the work of the innovators to come up with platforms that highly embrace technological dynamism that is currently being witnessed in the world. According to piatetsky, the current trend in technological advancement cannot be blamed for the stagnation in innovation of new technological approach on data mining. It is the feeling of the author that the developers of the new information sharing platforms should be able to offer avenues through which other developers can launch their platform. It is through such synchronization that the two arms of information sharing platform can work together. Another major argument in the article is the urgency with which people should embrace data mining. Based on the prevailing situation on information backlog, Gregory believes that it is time for a radical change in the way data mining is viewed in the mainstream. The author feels that the process needs to be more embraced by users so as to eliminate chances of data loss due to poor use of the process. The relevance with which the author tackles the preexisting problems in data mining is one of the main attractions of the article. George offers his knowledge in data mining process by clearly pointing out the areas that need closer supervision. It is the author’s belief that the process needs to be upgraded to give it a clear understanding of the persisting drawbacks in its implementation. Based on the information prov
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The article offers an insight into the development of data mining in database management. The author bases his arguments on the fact that database management relies on data mining for its existence. One of the major areas that the article tackles is the area of development of new data mining processes. The author feels that the current setting of the processes is highly linked to database management. The process is known to give a lot of impendence to the clarity with which information can be retrieved from a set of data. The author goers further to explain the implication of data mining to the database concept. One of the main arguments presented in this article is the need to create a database platform that focuses on the reliability of the data as provided by existing sets of information. It is important to note that the author has fully summarized the process of merging data mining applications with database management. The process gives one an opportunity to understand the major bearing of data base management on data mining. The historical perspective on the link between data mining and database development is also addressed in the article. The author gives an incisive analysis of the preexisting factors that affect the operationalization of database management protocol. The protocol is viewed as the pivotal factor that influences the institutionalization of the eminent factors that are present on the mining interface. The argument projected in this assumption is that the protocol is able to merge with the mining interface with deface interchanges that may necessitate the upgrade of the model into a higher version that incorporates the complex nature of raw data.
