An Audit Framework for Data Lifecycles in a Big Data context

M. E. Arass, I. Tikito, N. Souissi
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引用次数: 8

Abstract

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.
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大数据环境下数据生命周期审计框架
数据管理对企业来说变得越来越困难,尤其是随着云计算的普及和对物联网等大数据分析需求的增加。确实。、数据收集等任务。、分析。对于那些难以确定适合其数据使用环境的数据生命周期并允许将这些数据转换为知识的公司来说,可视化变得非常复杂。为了处理这种情况,为了让公司能够确定最适合其环境的周期,甚至改进它。,他们必须能够评估它,以确定它的优点和缺点。本文的贡献就是帮助公司选择数据生命周期。在这个意义上。,我们为数据生命周期设计了一个审计框架。该框架可以为企业评估其大数据生命周期提供有效的指导。
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