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ACCA PM大数据特点：Velocity and Veracity

文章来源：ACCA官网

发布时间：2021-08-17 15:54

阅读：1188次

Velocity

Information must be provided quickly enough to be of use in decision-making and performance management.For example,in the above store scenario,there would be little use in obtaining the price-comparison information and texting customers once they had left the store.If facial recognition is going to be used by shops and hotels,it has to be more or less instant so that guests can be welcomed by name.【点击免费下载>>>更多ACCA学习相关资料】

You will understand that the volume and variety conspire against velocity and,so,methods have to be found to process huge quantities of non-uniform,awkward data in real-time.

Veracity

Veracity means accuracy and truthfulness and relates to the quality of the data.In the context of big data,for any analysis to provide useful findings for decision making,the data collected must be true.To assess how true the data collected is,companies must consider not only how accurate or reliable a data set might be but also how trusted is the source of the data.Companies must be able to trust the source of the data being collected and be confident that the data is reliable and accurate if they are to base important,and often costly decisions on the findings of its analysis.

The difficulty that companies face here is that by its very nature,the data collected comes from many different sources.Some will be more trustworthy that others.For example machine and transactional sourced data would be seen as more reliable than human sourced data.Data from transactional and machine sources would be easier to verify and less easy to manipulate.Human data,for example from social media,however can be more easily manipulated and care must be taken when using this type of data,particularly given the recent increase in so called‘fake news’and growing reports of deliberately manipulated customer reviews on retail sites.

Veracity also ties in to velocity.To be useful in decision making,data needs to be analysed as soon as possible.Velocity shows that the data being collected changes quickly.Analysing out of date data could lead to poor decision making.

翻译参考

速度

必须足够快地提供信息以用于决策和绩效管理。例如，在上面的商店场景中，一旦客户离开商店，获取比价信息和发短信几乎没有用处。如果商店和酒店要使用面部识别，它或多或少必须是即时的，以便客人可以通过名字受到欢迎。

您会明白，数量和种类与速度相悖，因此必须找到方法来实时处理大量不均匀、笨拙的数据。

真实性

真实性意味着准确性和真实性，与数据的质量有关。在大数据的背景下，要为决策提供有用的分析结果，收集的数据必须是真实的。为了评估收集到的数据的真实性，公司不仅必须考虑数据集的准确性或可靠性，还必须考虑数据来源的可信度。公司必须能够信任所收集数据的来源，并确信数据的可靠性和准确性，才能根据分析结果做出重要且通常成本高昂的决策。

公司在这里面临的困难在于，就其性质而言，收集的数据来自许多不同的来源。有些人会比其他人更值得信赖。例如，机器和交易来源的数据将被视为比人工来源的数据更可靠。来自交易和机器来源的数据将更容易验证并且更不容易操作。然而，例如来自社交媒体的人类数据更容易被操纵，在使用此类数据时必须小心，特别是考虑到最近所谓的“假新闻”和零售网站上故意操纵客户评论的报道越来越多.

真实性也与速度有关。为了在决策中有用，需要尽快分析数据。Velocity表明正在收集的数据变化很快。分析过时的数据可能会导致决策失误。

以上翻译仅供参考，请以ACCA官网内容为准！

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