CIO should think about how to make large data produce great value

According to a report by IDC called "The Digital Universe", it is expected that the global data usage of the http://www.aliyun.com/zixun/aggregation/33722.html ">2020 year will reach 35.2ZB." In the face of such a huge amount of data, the efficiency of processing data is the life of the enterprise.

However, some corporate CIOs are still watching and questioning whether the big numbers are really coming.

The development process from mass data to large data is a process from quantitative change to qualitative change. The data has been growing for years, doubling the pace every year. Past technology has been able to manage it better, but once it reaches a tipping point there is a qualitative change, the past technology has not met the current trend of development, the need for new technologies to meet the needs of the new order of magnitude. So the concept of large data emerges.

Large data has the following meanings: first, large scale. The rapid growth of business in the market, increasing customer volume, the production of data is more and more, according to IDC survey, the next decade, the global data volume will increase 4 times times; second, a wide range of sources. Now the concept of large data, data is not only from the internal application of the enterprise data generated, but also include external. As an enterprise, it can include suppliers, customers and other data sources. Third, the data type is many, the data contains the transaction type structural data, the semi-structured data and the non-structural data.

The current market competition is fierce, the customer's demand is changeable, the market situation is changing rapidly, make these data must change with the business continuously. So in this era of data explosion, corporate CIOs should begin to think about how to effectively master and manage massive amounts of data. How to extract information from a wide range of data that is useful for the development of a company's business, helping to enhance operational efficiency, and how to make large data valuable.

(Responsible editor: The good of the Legacy)