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Comprehensive study of data analytics tools (RapidMiner, Weka, R tool, Knime)

机译:全面研究数据分析工具(RapidMiner,Weka,R工具,Knime)

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摘要

In today's era, data has been increasing in volume, velocity and variety. Due to large and complex collection of datasets, it is difficult to process on traditional data processing application. So, this leads to emerging of new technology called data analytics. Data analytics is a science of exploring raw data and elicitation the useful information and hidden pattern. The main aim of data analytics is to use advance analytics techniques for huge and different datasets. Datasets may vary in sizes from terabytes to zettabytes and can be structured or unstructured. The paper gives the comprehensive and theoretical analysis of four open source data analytics tools which are RapidMiner, Weka, R Tool and KNIME. The study describes the technical specification, features, and specialization for each selected tool. By employing the study the choice and selection of tools can be made easy. The tools are evaluated on basis of various parameters like volume of data used, response time, ease of use, price tag, analysis algorithm and handling.
机译:在当今时代,数据的数量,速度和种类都在不断增加。由于数据集的收集量大而复杂,因此很难在传统的数据处理应用程序上进行处理。因此,这导致了称为数据分析的新技术的出现。数据分析是一门探索原始数据并产生有用信息和隐藏模式的科学。数据分析的主要目的是对大量不同的数据集使用高级分析技术。数据集的大小可能从TB到ZB不等,并且可以是结构化的或非结构化的。本文对四种开源数据分析工具(RapidMiner,Weka,R Tool和KNIME)进行了全面的理论分析。该研究描述了每种所选工具的技术规格,功能和专业性。通过进行这项研究,可以简化工具的选择和选择。根据各种参数对工具进行评估,例如使用的数据量,响应时间,易用性,价格标签,分析算法和处理方式。

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