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Enterprise data analytics and processing with an integrated hadoop and R platforms

机译:利用集成的hadoop和R平台进行企业数据分析和处理

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Business in today's world mainly depends on business analytics like market analysis, product analysis, and price prediction etc. Analyzing such a huge data is a herculean task. Almost all data which is recurring day to day can be collectively termed as Big Data. Processing and analyzing such a Big data requires a parallel processing platform like Hadoop. Hadoop mainly does a mapping function and reduce function which together helps in faster processing. Business analytics also requires a faster data processing and faster execution. Developing such a environment requires an effective Analytical platform. The research carried forward in the paper put forwards an integrated platform of Hadoop for data processing and R platform for data analytics. The platform has been tested with the help of an enterprise data of employees of a company and their accidental insurance claims. The data has been preprocessed initially with Discretization function in R and then converted to transactions and put in for a Map reduce with an Éclat algorithm to find out the frequent items occurring in the record. Thus the research in the paper portrays an efficient processing and analytic platform for business data.
机译:当今世界的业务主要取决于市场分析,产品分析和价格预测等业务分析。分析如此庞大的数据是一项艰巨的任务。几乎每天都会重复出现的所有数据统称为大数据。处理和分析这样的大数据需要像Hadoop这样的并行处理平台。 Hadoop主要执行映射功能和归约功能,共同帮助加快处理速度。业务分析还需要更快的数据处理和更快的执行。开发这样的环境需要一个有效的分析平台。本文进行的研究提出了一个用于数据处理的Hadoop集成平台和一个用于数据分析的R平台。该平台已通过公司员工及其意外保险索赔的企业数据进行了测试。最初使用R中的离散化功能对数据进行预处理,然后将其转换为事务,然后使用Éclat算法将其放入Map Reduce中,以查找记录中出现的频繁项。因此,本文的研究描绘了一种有效的业务数据处理和分析平台。

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