Big data is not a castle in the air. Only from the data supply end to the middle end of collecting, cleaning and processing data and then to the demand end, from the beginning of laying the foundation, can we build a high-rise building with big data applications.
Recently, I heard that my cousin, who has just been admitted to the ideal university, recalled his anxiety when he filled in his volunteers for the college entrance examination. "I almost found' big data' to help me tell my fortune." It is said that this year, some college entrance examination volunteer consulting institutions claim that they can use big data to help candidates analyze which university and which major is the best. In fact, this kind of consultation does not know the source and scale of the data, nor can it produce an analysis model. However, because of wearing the hat of "big data", it has added some authority. Even if the price is high, it makes candidates rush. Perhaps we have all been given such a big data "chicken soup": big data can tell merchants that it will be better to sell beer and diapers together. Big data knows what products they need better than consumers themselves. Big data can help you analyze genes to prevent diseases ... as if you have enough massive data, you can predict everything. In fact, many cases turned out to be just good gimmicks. Big data is "big" enough to be "used" and then used to make big money, how can it be done in one step! Big data is not a castle in the air. Only from the data supply end to the middle end of collecting, cleaning and processing data and then to the demand end, from the beginning of laying the foundation, can we build a high-rise building with big data applications.
If big data is "big" enough, it must have full coverage of data collection. Judging from the application of big data in China, the coverage area is still very limited, mostly Internet companies, and the application of government, public services, industry and agriculture has just started. The fundamental crux is that the big data industry chain is still not perfect and it is impossible to build a data "high-rise building". Except for geographic information and voice data, most industries have not established a complete chain of data collection, processing, analysis and application. Only by establishing a mature big data industry chain and solving big data can we get more reliable and in-depth answers.
Interconnection, eliminating data islands, big data is "useful". In terms of data supply, open access has made a good start. Beijing and Shanghai have established government data open websites, and Guiyang and Wuhan have also launched big data trading platforms. Not long ago, the the State Council executive meeting deliberated and adopted the "Action Plan for Promoting the Development of Big Data", with the core content of promoting the opening of data resources, striving to form a huge demonstration role with government data taking the lead in opening up, promoting social awareness, taking government applications as a sample to promote the awakening of enterprise data awareness, and accelerating the pace of data opening and inclusion in the whole society.
From "useful" to "useful", it is inseparable from the cultivation of big data service providers. Although some companies with massive data, such as Alibaba, have begun to use big data technology for their own decision-making development and external services, most customer enterprises, especially those in traditional industries, still lack professional data processing and analysis methods, and there is a strong demand for data intermediaries that can collect and integrate multi-source data and analyze unstructured data. At the same time, data intermediaries with technical, information security and legal responsibilities can largely dispel the concerns of data owners and make them feel more secure about the circulation of their data resources in the market. Filling this gap between data supply and application is a compulsory course for the prosperity of China's big data industry. In the future, we should focus on encouraging the development of more professional data intermediaries.
Expanding the application of big data also requires the application side to exert its own strength. At present, the market demand for big data is huge, but only by exploring more practical application scenarios can we promote the development of data supply and processing. The development of application scenarios requires the participation of a large number of traditional talents who are familiar with the specific situation and knowledge of the industry, and solves problems such as what kind of data to choose after getting big data results and how to guide actual behavior.
Big data from fire to live is slow motion. Give more patience to the development of big data and gradually improve the mature overall industrial chain. Big data can really live in social management and economic development.
The above is what Bian Xiao shared for everyone. Big data is not a castle in the air from fire to living, but a slow-motion related content. For more information, you can pay attention to Global Ivy and share more dry goods.