Not all companies apply big Data

Foam is not cracked, but large data applications in the domestic has been a prototype.

Yili dairy industry uses terminal management technology, aggregated retail terminal store sales of scattered data, so that the sales plan no longer rely on the head to finish; Shandong Province a group of "large data" as the label of tourism sites, according to the tourists before the purchase behavior, for different tourists to provide targeted services; China's High-tech companies are planning to set up a special department for large data research ...

However, I believe that not all enterprises are suitable for large data. Not on the big data from the actual situation and specific needs of enterprises, enterprises only have talent training, capital investment, technology platform and other comprehensive protection to obtain data value.

First, the development of data analyst is the most important. "Big Data hype has reached its peak. The existence of large data bubbles is not because the role of the data is exaggerated, but the real analytical ability of the data analyst is rare, so that large data can not be better value. Shi Gong, deputy general manager of the same party data resources division, said in an interview with reporters. The Harvard Business Review argues that data analysts are "the hottest jobs of the 21st century", with the lure of massive data gouging and the high skill requirements that make data analysts scarce. "The special large data plan of the shares of the same party, in addition to capital investment, is more crucial to cultivate talents and foster the development of large data industry." "I said.

In the fields of finance, medical treatment and so on, complex talents are indispensable. Academician Wei Yu of the Chinese Academy of Engineering has said that it is urgent to solve the problem of the lack of complex talents in biomedicine and information science through the introduction of large data.

Second, big data is really expensive, and businesses have to measure whether they're investing in big data. It is understood that Facebook stores about 100TB of user data per day; NASA processes about 24TB of data a day. The staggering figure behind the high cost of the Amazon redshift pricing, NASA needs to 45 days of data storage services to pay more than 1 million dollars.

The author has interviewed several CIO of the enterprise, they most say the data that the enterprise needs to deal with daily is not very big, and the cost of data storage and processing is too high, cannot withstand the cost of large data deployment according to their budget.

Finally, if the application of large data, enterprises to choose a mature large data platform, and Data Warehouse has high-performance connection, easy to allow different people to apply, according to business needs to enable technicians to use the platform to quickly improve the value of the data. This is the enterprise needs capital, technology input "big Head", is also the enterprise is worth doing homework place.

The big data is good for the icing on the cake, not the help, if the business is not done well, do not expect large data to be helpful. As Shi told reporters, only pay attention to the technology platform, the appropriate investment, can attract excellent data analysis talent enterprises, can be in the Big Data era.

(Responsible editor: The good of the Legacy)