Value of data surpluses

Cloud computing fills our ears in a variety of ways. Indeed, storing or computing http://www.aliyun.com/zixun/aggregation/14304.html "> distributed products and services in the cloud are also inadvertently moving into life. The sharing of data among smartphones, tablets, PCs, Macs, and Nas has also exploded rapidly, while increasing efficiency has been accompanied by a rapid explosion of data addicted to the cloud, whether private or public. These data play a significant role in product improvement or operations, and as data is plentiful, data mining means and efficiencies are raised, and a large amount of data surpluses are generated when product or operational improvements are completed, and these surpluses are often of great value.

The obvious example is the early Taobao data cube, relying on the amount of Taobao data, in the completion of product improvement or operation to enhance the utility at the same time, resulting in a large number of valuable data surpluses. This data has not yet become a product, but the potential value that is dimly visible becomes today's top. The same example can be found in Sina Weibo.

Data allows products to be quantified, and data surpluses can help people find new niches in their products. Sounds good, but there are a lot of constraints in practice:

1. Data greed Psychological oppression: the team's desire for data is greater than the current capacity to carry, so the data personnel to meet the needs of the data structure, mechanism and performance to further evolve, and then can not talk about data surpluses;

2. Lack of visualization: data is the data, distance allows people to make the knowledge of decision-making. How many people can read data in a report or a stereotyped chart? How many times do you provide data to co-workers, and they will confirm the meaning? No fool, only good products, the data itself is certainly the product. Through visualization, so that the data closer to the knowledge, help people is more self;

3. The corruption of the structure: summer insects can not be language ice, tigers can not climb trees. An inappropriate architecture makes late-stage data slow (other products are the same), and a number of failures, but changing the architecture is painful and frustrating. Even if the original architecture for a variety of reasons to become a reality, but also to change, the opposite, to mend, it is not too late.

Cloud computing is necessarily a large amount of data in the calculation, it is bound to the timeliness of strict requirements, will produce data surpluses. First of all, the data should be first, then, as soon as possible visualization to King. At this point, the data surplus will appear, let these surpluses add value to the Cloud bar.