Bigdata is not omnipotent! Disclosure Big Data Four drawbacks

Large data and user privacy are difficult to reconcile

Alibaba founder Ma Yun said: "Users do not understand the PC era, mobile internet came; When the mobile internet was not understood, the big data age came. His words were a good testament to the heat of the word "big data" in the industry since 2013.

Admittedly, the era of big data that has been preached seems to have come true. Under the halo of Zhongxingpengyue, "Big Data" is like a sweet pastry, everyone wants a piece. So, big data is really as good as we think?

I think, in the information age today, the vast and complex data collation and judgment is necessary, the data also does exist a large number of treasures. But it's like picking up a treasure in a dump, and it's always more than a baby.

Many times, we cannot judge the true validity of the data, which is a great harm to the final judgment. When the data source is not at that time, this is a kind of harm to user's privacy. Enterprises need to use data to profit while paying attention to not prying into user privacy, many times, it is difficult to grasp such a balance point.

In life, "dirty data" everywhere, for example, the existence of the network of the Navy has greatly affected the authenticity of the Internet information. A product, his value and quality is molded, placed there, but the evaluation of it can vary. According to the principle of statistics, the larger the base of the commentary, the closer the result is to the real, but the premise must be the user's real and objective feedback. But in the presence of the network Navy, this condition is not allowed.

For example, a low quality film has been pushed to the market, because of the success of marketing, attendance is also high, the film site has a high score. But this is not real data, and a large number of the navy submerged the authenticity of the information. If the data is not analyzed and judged directly, no matter how high the calculation precision, the result is meaningless, because the data itself is problematic.

Similar examples also, Taobao sellers brush drill, micro-bo zombie fans, paste forum marketing stickers and so on. Dirty data is ubiquitous in the network, in the large data is not enough today, in fact, there is no very effective way to "dirty data" to identify.

Summary of the four drawbacks of large data

Big data can only find the past, not the future

In the information age, each byte contains incredible data information, the information to be summed up, to extract effective information to help companies or enterprises to make better decisions, is the "big data" meaning and purpose. But the problem comes along, in addition to the problem of "data authenticity" and "dirty data" mentioned above, there is also an important question that markets are fickle and unpredictable, and that creative thinking by policymakers cannot be reflected in data, instead, data is stifling innovation.

The most obvious example is the handset maker Motorola and Nokia. At the beginning of the new Century, Motorola V3 series of mobile phones have been successful, known as sales up to 100 million, once the disdain of the warlords. Motorcycle from a large number of data and feedback received good news, think it should be on the V3 model up and down articles. But the sameness, the lack of change will only make consumers tired. Nokia in 2007--2010 years can be said to be high, Symbian system can be said to be eminence, regardless of the data or scene, have the upper hand. But the problem is, the average consumer is not very clear about their own needs, only the real products come out, they will be surprised to praise, turned to the old products thrown aside. So soon, Symbian was gongchenglvede by "new forces" like iOS and Android. Today, Motorola and Nokia have been acquired by Google and Microsoft respectively.

In a new field, in front of the first pioneer is actually Yimapingchuan, there is no data to follow, there is no experience good reference, all in the groping in the beginning. In such a scenario, big data has no effect at all, and may even backfire. An obvious example, before Facebook's success, the internet Giants ' data analysis concluded that social networks did not have great opportunities and that, after Facebook's success, the Giants ' ideas were the opposite of what they had been. To that end, Google CEO Eric Schmidt said in an interview a few days ago: "The biggest mistake I've made in Google is that I didn't (let Google) participate in the rise of social networking." ”

Comprehensive above, I think that large data mainly have the following drawbacks:

1. Low Data conversion rates

2. Privacy Security Issues

3. Data authenticity remains to be tested

4. Data has no reference value to innovation

Summary: The value of large data should be recognized, not exaggerated. The big data at this stage is just a picture of the pie, far away to eat. Big data is not everything, don't be obsessed with big data.

(Responsible editor: The good of the Legacy)