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看清大数据:是工具而非万能钥匙 Big data, just a tool not a master key


大数据在当前时代契合了互联网的本质属性,因为二者都是虚拟的,这也是时代发展到当前必然出现的现象。但是,企业若将转型的精力全部放在大数据的应用上,而无视其它盈利模式,在某种程度上反而得不偿失。 Big data accords with the essential nature of Internet in our times as they two are all virtual, which is also an inevitable phenomenon of social development. However, if the enterprises devote all energy in big data application and neglect other profit models during transformation, they will lose more than they gain.


一方面,企业借助互联网产生盈利,这是新时期背景下企业的盈利模式。因为实体经济的萎靡不振,线下的道路几被堵死,在这种情况下,传统企业只能在线上寻找新的赢利空间。这种转向并不是企业在赶时髦,而实在是出于无奈。 On the one hand, enterprise benefiting from the internet is an inevitable profit model in the new era context. Because the entity economy remains sluggish and the offline ways are almost blocked, traditional enterprises can only seek for new profit space through internet. This diversion is not to follow the fashion but because they have no alternatives.


另一方面,市场电商化过程中沉淀了大量数据,较好的适应了产业链的重构,于是很多具有轻资产性质的公司较早的进入了线上产业重构的时代浪潮中,并成为在大数据产生之前最早盈利的弄潮儿。大数据的产生无形之中又推动了这批弄潮儿向着更加广阔的盈利空间迈进,并产生新的盈利。由此,传统的企业在转型的过程中,眼睛里几乎被这些盈利的弄潮儿占据了,因此造成了一种假象:所有搞大数据的企业都是盈利的。被拍死在这波浪潮中的企业直接被无视掉了。 On the other hand, mass of data is stored when the market is e-commercialized, which caters to the reconstruction of industry chains better. In such a case, many asset-light enterprises integrate into the tides of online industrial reconstruction very early and become the leader to make profit before the big data emerges. The formation of big data invisibly drives these people to enter in a wider profit space and benefit more. Thus, traditional enterprises only focus on these “tide players” during transformation while neglecting those losers, which produces an illusion that all enterprises committed to big data application are profitable.


其实,现在线上的所谓大数据,体量还是极小的,真正大体量的数据还未被挖掘出来,或者说还没有被共享出来。目前,大体量的数据绝大部分仍旧存储在制造业、政府、传媒或银行中等待唤醒。目前市场上的数据处理软件在应对已经被释放出来的数据时,已经显得力不从心。相关的数据挖掘技术、数据智能处理技术、数据动态追踪手段尚需完备。 Actually, the size of so-called online big data is small and the truly large-scale data has not been dug out or shared. At present, the true big data are still stored in the manufacturing, government, media or banks, and remain to be awakened. The current data processing software is inefficient to handle the released data on the market so the relevant data mining, data intelligent processing technology and dynamic tracking approaches need to be perfected.







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