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电力大数据:2018,21(12):-
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信息碎片化的模式探讨企业大数据的挖掘
刘丽婕、杨昆桦、王泽芬、蒋友权
(贵州电网有限责任公司凯里供电局)
Information Fragmentation Mode Exploring Enterprise Big Data Mining
Liulijie,Yangkunhua,Wangzhefen,Jiangyouquan
(Kaili Power Supply Bureau)
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投稿时间:2018-07-31    修订日期:2018-10-31
中文摘要: 手机正在改变我们的生活。我们在不知不觉中平时很多的生活模式已切换到手机模式,这种模式的特点是碎片化、浅显化和情绪化。为了使人们不被每日手机中的所见所闻牵着走,把注意力集中在创意和思考上,我们沿袭当前信息碎片化的处理模式,利用人们当前习惯的手机微信平台,开展“众筹”“众创”的双创活动,吸引全员参与,互帮互助,把平时对信息只停留在粗浅的了解模式引进了深入的思考与体会中,结果达到双重功效,一方面不仅能够获取知识,刷新认知,而且还使企业员工的关系更为密切,组织的感觉油然而生。另一方面,在信息过载时代中,把长期接触到的浅显情绪化的认知模式,再训练,再识别,把心态转变成井然有序的状态,使员工在工作和生活中重获一种掌控感,是一种难以言表的享受。实践证明,在企业内在手机上推广带思考而且能共同参与的活动,不仅能使员工共融共乐,而且也是企业大数据挖掘收集的好路径。
Abstract:Mobile phones are changing our lives. Many of our lifestyles are unknowingly switching to the mobile phone mode, which is characterized by fragmentation, shallowness and emotionality. In order to keep people from being led away by what they see and hear daily from the mobile phones, and to focus on creativity and thinking, we follow the current information fragmentation processing mode and use the mobile WeChat platform that people are used to. Crowdfunding and the “double creation” activities of “Zhongchuang” attract all the participants to participate in each other, help each other, and introduce in-depth thinking and experience into the superficial understanding mode of information in usual. The result is dual effect——on the one hand, not only knowledge can be acquired and cognition can be refreshed, but also making the relationship of employees more close and the feeling of organization arise spontaneously. On the other hand, in the era of overloading information, the shallow and emotional recognition mode which we are long-term exposed to is retrained and re-identified, and the mentality is transformed into a well-ordered state, enabling employees to regain a kind of the sense of control in their work and life, which is an unspeakable enjoyment. Practice has proved that promoting activities with thoughts and participation in mobile phones in enterprises can not only make employees be happy together, but also is a good path for enterprise big data mining.
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