Detailed Analysis of Data Mining Tools

Abstract

Today the magnificient growth of technology and adoption of the several application renaissance in the information technology sector and the related fields.Due to this striking advancement ,collecting and warehousing the data in necessity.This overall leads to the concept of data mining,which can be viewed as one of the emerging and promising technology development. Data mining is explanation and analysis of large quantities of data in order to extract implicit, previously unknown and potentially meaningful patterns by using some tools and techniques. This paper presents the comprehensive and theoretical analysis of five open source data mining tools-Rapidminer, R, Knime, Orange, Weka. The study provides the pros and cons Ziped with the technical specifications features and specialization of each tool.By this complete and hypothetical study, the best slelection of the tool can be made easy. INTRODUCTION: In this information age, with the advent of technology advances and means for mass digital storage, users typically collect and store all varieties of data, counting on the power of technology to help sort through this amalgam of information. These massive collection of data were initially stored on disparate structures, leading to the creation of the structured databases. The efficient database management system (DBMS) have been very essential and crucial assets for management of large corpus of the data. The proliferation of DBMS has also contributed to massive gathering of varieties of information. Confronted with huge collection of data, the need for the hour is to make letter managerial choices. These emergent needs are: