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Big data brings cold thinking to the farming and animal husbandry industry

日期
2016年2月26日 00:00
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In 2015, when it was called the Internet + the beginning of the year, the agriculture and animal husbandry industry whipped up a whirlwind of Internet +. It is inseparable from the "big data" cornerstone to catch up with the "Internet +" Dongfeng farming and animal husbandry industry.

Looking back at history, the fashionable vocabulary of "Big Data" has long existed. However, what really caught people's attention and discussion was due to the rapid development of the Internet and information industry in recent years. Compared with the previous data, the biggest feature of big data is “big”. These data are not measured by G or T, at least P (1000 T), E (1 million T) or Z (1 billion T). ).

How big is the network user data accumulated across the Internet? Take the feed industry as an example, enter “feed ingredients” in Baidu, and display 11,000,000 pieces of data information, further narrow the data range, find “corn market”, and display 45,100,000 pieces of data information, even in small raw materials. The data has reached 164,000. Of course, this is only external data. If the internal data is added, the entire feed industry should generate billions of data per day.

The above data is just the tip of the iceberg of big data, big data is growing by geometric multiples, and getting bigger and bigger. The first to propose "big data" and modern change is McKinsey's management consulting firm. McKinsey believes that data has penetrated into every industry and business function area today and has become an important production factor. The mining and application of massive data indicates a new wave of productivity growth and the arrival of consumer surplus. ”

With the advent of the Internet+ era, people's understanding of big data is no longer limited to the superposition of individual data, but the use of big data as the cornerstone to build a new ecosystem.

In 2015, China's agriculture and animal husbandry industry took the "Internet +" train, and each agriculture and animal husbandry enterprise intended to make a difference. However, the traditional agriculture and animal husbandry industry, which has developed for so many years, now has to enter the "Internet +" channel. Its inherent business model and huge industrial chain system make the transformation difficult. Take a small and medium-sized feed additive company like DDC, which needs to process thousands of business information every day. Order information, production information, product quality traceability information, application test and animal test information are brought together. It is a very large one. data. Over time, this amount of data will continue to grow rapidly, putting tremendous pressure on the practical application of enterprise data.

The pressure brought by data deposition is the most problem facing agriculture and animal husbandry enterprises. Of course, the most fundamental problem is much more than that. As for a traditional enterprise such as agriculture and animal husbandry, because big data can not bring direct economic benefits to enterprises, at the enterprise operation level, big data still stays in the slogan and concept stage.

In the current agriculture and animal husbandry industry, the most realistic challenge encountered in the development of big data comes from three aspects. On the one hand, the data islands within the enterprise are serious. China's feed enterprises have begun to undergo more intense capital expansion just after the scale expansion, and the data will be more fragmented. The data of the enterprise is too scattered. If you don't open up the data, what about the value mining of big data? Another aspect of the challenge is the current low availability of big data in the agriculture and animal husbandry industry and the poor quality of big data. Taking feed enterprises as an example, in the first three quarters of 2015, the performance of many feed enterprises increased. The big reason was the decrease in raw material prices. With regard to raw material data, feed enterprises have not formed a good predictive data model, and profit and loss depend on the market. serious. The third aspect is the security of data. Especially for traditional industries such as agriculture and animal husbandry, data security, especially the security of technical data, is placed in the top position of business operations. In the era of big data, how data finds a balance between openness and privacy is a serious challenge for most farming and animal husbandry companies.

Of course, the challenges facing China's agriculture and animal husbandry industry go far beyond this. For the agriculture and animal husbandry industry, the most pragmatic approach is to start from the basics. The first is our decision-makers, who want to catch up with the big data trend or want to really use big data technology to improve the competitiveness of enterprises. This is the most critical issue. Looking forward to the next 3-5 years, with the acceleration of the transformation and upgrading of the agriculture and animal husbandry industry, big data will truly become a reality from slogans and concepts.