Large data is "enthusiasm"

Recently, some people have poured cold water on the "Big Data heat", implying that what is now known as "Big Data" may not be reliable. The person who released the speech was not aloof's "fake connoisseur", the co-founder and CEO of AYASDI, a big data analyst for the http://www.aliyun.com/zixun/aggregation/14294.html of the United States. Gurjeet Singht.

He points out that analyzing data from the start of a query is a dead end in itself. The researchers now only extract 1% from the collected data to analyze and extract insights, and 1% of the data analysed can dominate the enterprise's innovation and formation of insights, known as "Big Data".

Gurjeet Singht's comments, we have to let us reflect on the current "Big data" and in this heat wave constantly by various institutions of the "Big Data Analysis" is not a bit "false" too prosperous.

Gurjeet Singht's argument is not without foundation. The size of the digital universe has indeed doubled in the last two years, and in the face of this explosive growth, the pace of technological development does not match the pace of the development of the data universe. According to IDC's latest report, people can collect about 1qB of data a day, the size of the digital universe has reached 2.8ZB of data volume. IDC predicts the size of the digital universe will reach 40ZB by 2020. With the development of mobile technology and sensing technology, the ability of people to collect data is increasing, but the technology of identifying data is not so optimistic. For example, in the current data universe, a lot of valuable data, are based on the document of the unmarked unstructured data, people of this kind of data recognition, processing technology research has just begun. However, the so-called mature large data analysis methods in the market are generally based on valid data identification to collect data for analysis. According to this method, some data cannot be labeled because it is unrecognized, and therefore cannot be considered valid data, and they are discarded before being used for analysis. This problem resulted in the loss of a large amount of valuable data and was not exploited at all.

The value of large data to enterprises lies in the analysis and extraction of insights. If this "insight" comes only from the analysis of valuable data less than 5%, the analysis method is only the pre-judgment of some "scientists", the enterprise also depends on such a view "business", such "big Data" is not a disaster?

U.S. private data Analysis service providers ' valuations have been pushed up to $ billions of trillion. A few days ago, the U.S. tourism industry also blew up "strange Wind", some do not know what the big data of the start-up companies, are relying on large data concept circle money, and the effect is good. The big data has just been a toddler, and some people have judged that their future will be "the president" and have already pulled the ballot for him. In the data analysis technology is very immature today, the capital market for large data-related enterprises of excessive enthusiasm, is undoubtedly a dangerous signal.