How do small companies cope with the big data boom? With the help of third party services, or contrarian

"Big Data" has become one of the hottest concepts on the Internet, and I've seen many entrepreneurs start talking about the commercial value of big data, entrepreneurial projects must be linked to the "big data", some people are the "big Data Age," a book as a Bible, as if only to buy a sacrifice in a corner of the home, they are qualified to talk about wide, Jiangshan. But in fact, although the book insights into the trend of data analysis and worries, but because the author Viktor Mayer Sch Nberger is a typical academic school, and there is no worthy of the practical experience, resulting in the book lack of landing sense, Large data commercial applications can only be a piece of paper without reliable technical support.

Admittedly, "large data" does have very important value, now from the traditional industry to the Internet industry many products also need to rely on "large data" as a function of support and core competitiveness, borrow Alibaba data platform and product department Data Warehouse architect (nickname) of the summary, at present stage, Major data solutions are divided into 3 categories:

1. Expand the traditional business intelligence (BI) field. Previously for large data Statistics, association analysis, trend prediction from sampling to total analysis, the return of data to various reports.

2. Business process change. The aggregation analysis of various data is used to make business process improvement and evaluation basis.

3. Data products and commercial applications. Data products or data services are formed by servicing or packaging existing data or processing capabilities.

Among them, we in the Internet industry is the most common is through the existing data to form data products and data services, the most typical scenario is "personalized recommendation", but this is not everyone can get to the concept-we know that the industry relies on four characteristics to define "big data":

First, Volume, large volume, PB level;

Second, produced, a wide range of data types;

Third, veracity, low value density;

Four, velocity, fast processing. In short, you need to grab massive amounts of data from different dimensions and quickly turn them into ordered, available information.

In fact, the Internet in China, fully equipped with the above four characteristics of Tencent, Alibaba, Baidu and other large companies, for the general company, it is simply impossible to have PB-level data, and can not support the high cost of data storage, and large data technology personnel is very scarce. Recently many entrepreneurial teams have told me the vision of their products, many ideas are very novel, but due to data processing ability, had to choose "slowly" or the product function castration. So how can such companies rise in the "Big Data" wave?

The first thing I think about is using a Third-party data-processing service platform, a business that is already mature overseas, and it's literally hard to understand that these companies provide "data" or "services" to companies that do not have large data and large processing capacity.

Services can be divided into two broad categories: basic services and personalized services.

Basic services help companies solve data storage, framework building and management of the basic capabilities of large data processing, such companies are representatives of Hadoop (distributed software framework) management software and service providers Cloudera, MongoDB database developers 10gen and so on.

The other is directly to help enterprises directly to create personalized solutions, I think these companies are more suitable for the majority of the overall lack of data capacity of China's small internet companies and the hope of the Internet of traditional enterprises, such as to help the electric business to provide personalized online shopping experience RichRelevance, Personalized and digital marketing optimization service provider Jack, for advertisers to provide data and analysis of the exelate, as well as the data auction platform BlueKai. At home, there are some good platforms starting to emerge, such as personalized recommendation engine provider percent. The use of these third-party services and data, can make small company products also have excellent personalized ability, into the big data age.

But I think there is another way to deal with the big data wave-bucking the trend. I don't think big data is the only solution to personalization, but it's also a fairly strong limitation--based on data to build models with data, and in a sense, it's like a cage: imagine if all your information comes from personalized referrals, So you're probably missing out on new areas that you've never met, and are these open, new messages that are not the most fascinating thing about the Internet?

In fact, there are already some products that do, the Li Ru of the Tang Cha plan has said that it will not be interfered with by the data to decide which ebook to sell/recommend, but solely based on their personal judgment of the content, as well as in the more watched radio fuzz, entirely by the artificial DJ to push music. Conversely, if the same type of products have accurate large data processing capabilities, then they provide users of the content is likely to be the same, and these contrarian products, but more like a real "personalized" service.

(Responsible editor: The good of the Legacy)