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Visualization of Big Data with the Map-Reduce program execution platform: Hadoop

机译:使用Map-Reduce程序执行平台可视化大数据:Hadoop

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"Big data" is the fashionable term currently found in all professional conferences related to data science, predictive modeling, data mining, to name just a few areas literally electrified by the prospect of integrating larger datasets and data flows more quickly into their business processes and other organizational processes. As is often the case when new technologies begin to transform industries, new terminologies emerge, along with new approaches to conceptualize reality, solve problems, or improve processes. A few years ago, we limited ourselves to "segment" customers into groups that could acquire specific properties or services. It is now possible and common to build models for each customer in real time as they browse the Internet for specific properties Instantly, prospects' interests are analyzed and it is possible to display highly targeted advertising, which is a level of personalization inconceivable only a few years ago. Inevitably, the disappointment may be up to expectations in many areas as technology around big data are promising. A limited number of data accurately describing a critical aspect of reality (vital to the business) is far more valuable than a deluge of data on less essential aspects of that reality. The purpose of this article is to clarify and highlight some interesting opportunities around big data, and illustrate how analytic platforms can leverage this wealth of data to optimize a process, solve problems, or improve customer knowledge.
机译:“大数据”是目前在与数据科学,预测建模,数据挖掘相关的所有专业会议中流行的时髦术语,仅列举了几个领域,这些领域真正地激发了将较大的数据集和数据流更快地集成到其业务流程中的前景。其他组织过程。当新技术开始转变行业时,通常会出现新的术语,以及用于概念化现实,解决问题或改善流程的新方法。几年前,我们仅限于将客户“细分”为可以获取特定资产或服务的群体。现在,当每个客户浏览Internet以获得特定属性时,就可以实时为每个客户建立模型了。立即分析潜在客户的兴趣,并可以显示针对性强的广告,这是只有少数几个人无法想象的个性化水平几年前。不可避免的是,随着围绕大数据的技术的发展,许多领域的失望可能会达到预期。准确描述现实的关键方面(对业务至关重要)的有限数量的数据比关于现实的次要方面的大量数据更有价值。本文的目的是阐明和强调大数据方面的一些有趣机会,并说明分析平台如何利用这些大量数据来优化流程,解决问题或改善客户知识。

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