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An Audit Framework for Data Lifecycles in a Big Data context

机译:大数据环境下数据生命周期的审计框架

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Data management is becoming increasingly difficult for businesses especially with the proliferation of cloud computing and the increasing needs in analytics for big data such as data generated by the Internet of Things. Indeed., tasks such as data collection., analysis., or visualization become very complicated for companies that have difficulty identifying the data lifecycle that fits their data usage context and that also allows to transform this data into knowledge. To deal with this situation and in order for companies to be able to identify the most appropriate cycle for their context or even improve it., they must be able to evaluate it to determine its advantages and disadvantages. The contribution of this paper is part of this perspective to help companies choose their data lifecycle. In this sense., we have designed an audit framework for data lifecycles. This framework could constitute an efficient guide for companies to evaluate their Big data lifecycles.
机译:对于企业而言,数据管理正变得越来越困难,尤其是随着云计算的普及以及对大数据(如物联网生成的数据)的分析需求不断增加。确实,对于难以识别适合其数据使用环境的数据生命周期并且也难以将其转换为知识的公司而言,诸如数据收集,分析或可视化之类的任务变得非常复杂。为了应对这种情况,并使公司能够根据自己的情况确定最合适的周期,甚至对其进行改进,他们必须能够对其进行评估,以确定其优缺点。本文的贡献是帮助企业选择数据生命周期的这一观点的一部分。从这个意义上讲,我们为数据生命周期设计了一个审核框架。该框架可以构成公司评估其大数据生命周期的有效指南。

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