A compendium on Data Mining Algorithms and Future Comprehensive
Manalisha Hazarika1, Mirzanur Rahman2

1Manalisha Hazarika, Information Technology, Gauhati University, Guwahati, India.
2Mirzanur Rahman,, Information Technology, Gauhati University, Guwahati, India.

Manuscript received on July 11, 2013. | Revised Manuscript received on July 15, 2013. | Manuscript published on July 25, 2013. | PP: 51-56 | Volume-1 Issue-9, July 2013. | Retrieval Number: I0379071913/2013©BEIESP

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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Data mining is a powerful and new method of analyzing data and finding out new patterns from vast volume data .There is an enormous amount of data stored in databases and data warehouse due to enormous technological advancements in computing and Internet. In recent days multinational companies and large organizations have operations in many places in the world. Each place of operation may generate bulk volumes of data. Corporate decision makers require access from all such sources and take strategic decisions. The information and communication technology have highly used in the industry. One of the main challenges in database mining is developing fast and efficient algorithms that can handle large volumes of data as most of the mining algorithms perform computation over the entire databases ,often very large. Today’s business environment, efficiency or speed is not the only key for competitiveness. Such tremendous amount of data, in the order of tera- to peta-bytes, has fundamentally changed science and engineering, transforming many disciplines from data-poor to increasingly data-rich, and calling for new, data-intensive methods to conduct research in science and engineering. This paper gives an outline of the existing data mining algorithms and give the future space of some algorithm.
Keywords: Data Mining, frequent item, load balance, parallel algorithm.