[Phenomenon] Under the wave of big data, some enterprises turned their attention to traditional small data and improved relevant products accordingly. For example, compared with the past, the lids of cans and soda bottles are easier to open, the doors can be closed effortlessly, and the opening and closing of drawers are designed to be smoother. This is due to the keen attention of enterprises to a detail: with the reduction of physical labor caused by the development of technology, and the degradation of writing caused by computers and touch screens, people's hands are no longer as powerful as before. Similar small data and small trends are changing our lives together with big data.
[Comment] The generation of big data has simplified people's understanding of the world. By transforming human behavior into countless quantifiable data nodes, it provides a "data portrait" for people. However, some of the current big data applications still remain at the label level, ignoring individual differences, which is likely to lead to the result of "one thousand people, one side".
If big data focuses on the overall and general rules, small data focuses on the individual and delicate facts. Compared with big data, the value of small data is that it comes from the details of various social behaviors, is closer to people's individual feelings, and is more accurate in the presentation of needs. For example, according to the big data portrait, baby diapers may be associated with milk powder, toys and other commodities, and beer consumers may also buy peanuts, potato chips and other snacks. According to the analysis of small data by a foreign retailer, male customers often reward themselves with a few bottles of beer when buying baby diapers, so they tried to launch a promotion method of putting beer and diapers together, and it was successful.
Whether it is big data or small data, the most important thing is to analyze the data. To take an ancient example, in the battle of Maling, Pang Juan was good at data analysis, while Sun Bin used the opposite method to trap Pang Juan by fabricating the data of "making the Qi army enter the Wei area into 100000 cooking stoves, 50000 cooking stoves tomorrow, and 30000 cooking stoves tomorrow". This is the result of Pang Juan's habit of using big data of "stove" while neglecting the analysis of small data such as footprints. To achieve a deeper understanding of things, we need to combine big data thinking with small data details.
As for the future trend, some experts predict that in the near future, the boundaries between big data and small data will be eliminated and replaced by "full data" or full data, that is, all data. For example, in the future in the field of intelligent transportation, it will be possible to use full amount of real-time data to perceive the specific location of each vehicle in the city and the vehicle information at each traffic light intersection, and conduct global regulation on these situations, thus greatly improving the efficiency of urban traffic operations. To achieve this goal, data mining and analysis as well as deep learning of artificial intelligence are indispensable.
In his book Digital Anthropology, Thomas Krupp, a British mathematician, pointed out that the essence of data is people, and analyzing data is to analyze the human race itself. Data is generated from various activities of human society, and its value also lies in serving human society and making life better. For the public sector and enterprises, on the premise of ensuring data security, transforming data into services and products can more accurately match people's needs and expectations, so that data can better serve human society and constantly improve people's happiness.
(Editor in charge: Wu Xiaojuan)
