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An Audit Framework for Data Lifecycles in a Big Data context

机译:在大数据上下文中的数据生命周期审计框架

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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:数据管理对企业越来越困难,特别是随着云计算的扩散以及对互联网数据产生的数据的分析中的越来越多的需求。实际上。,数据收集等任务,分析,或者可视化对于难以识别适合其数据使用环境的数据生命周期的公司变得非常复杂,并且还允许将这些数据转换为知识。要处理这种情况,并为公司能够确定其背景甚至改善它的最合适的周期。,他们必须能够评估它以确定其优缺点。本文的贡献是本文的一部分,帮助公司选择其数据生命周期。在这个意义上。,我们为数据生命周期设计了审计框架。该框架可以构成公司的有效指南,以评估其大数据生命周期。

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