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Managing big data integrity

机译:管理大数据完整性

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摘要

Big data becomes a real opportunity and a serious worry for data managers, data scientists, researchers and even for business managers. An opportunity as a set of powerful technologies and a bunch of interesting concepts that aim resolving business problems of an organization. A worry because big data implies big challenges and big resources that make harder the task of mining value from all the available data. The data, even in context of big data, need to have a value to help on making good business decisions. In fact, sound decision requires confidence on data that must draw the real world, at any stage of data processing. In other words, the data have to keep their integrity properties from origination until the final destination in analysis reports or in a business indicator. In this paper, we will throw light on integrity issues for big data and we introduce a new model about how preserving integrity in the context of big data.
机译:大数据成为数据经理,数据科学家,研究人员乃至业务经理的真正机遇和严重担忧。机遇,因为它是一组强大的技术和一系列有趣的概念,旨在解决组织的业务问题。令人担忧的是,大数据意味着大挑战和大资源,这使从所有可用数据中挖掘价值的任务变得更加困难。即使在大数据的情况下,数据也需要具有价值,以帮助制定良好的业务决策。实际上,在数据处理的任何阶段,正确的决策都需要对必须绘制真实世界的数据充满信心。换句话说,数据必须保留其完整性属性,直到分析报告或业务指标中的最终目的地为止。在本文中,我们将重点介绍大数据的完整性问题,并介绍一种有关如何在大数据的上下文中保持完整性的新模型。

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