Everyone is "data animal" large data analysis activates industry chain

In an internal email to Alibaba employees, Mr Ma said the IT era, with its control as the starting point, was moving toward the data age of Marvell, the purpose of activating productivity. With the development of computer technology, large data computing becomes more and more realistic, and companies based on large data application services are emerging. The application of large data in the field of marketing has turned advertising into a "narrow"-precision marketing, and in the context of Internet finance, large data in the financial industry, the application of credit is gradually rising.

Everyone is a "data animal."

Unlike "There is no trace of birds in the sky, but I have flown," people, whether chatting online, shopping or browsing the web, sending micro-letters, micro-blogging, will leave more or less records, these records are stored in the form of data. With the rapid development of mobile Internet, no matter when, where, where, mobile phones and other web portals and ubiquitous sensors will collect, store, use and share personal data. And a lot of data combined, through analysis, it is not difficult to restore a person's "appearance"-the image of the data.

Many people have this experience when browsing the Web, the ads on the site often appear on their own recently browsed products, or recently searched the content, this is the big data in the marketing application.

Beijing Collection Austrian Polymerization Technology Co., Ltd. is a large data service provider, the company launched the Dataquate solution is mainly used to solve the operators of large data access, mining and applications, for operators to transform the value of large data to provide end-to-end services.

It is through the excavation of large data that the collection Austrian polymerization helps advertisers to carry out advertisements more accurately. According to the introduction of CMO Deberi polymerization, through systematic analysis of massive and fragmented network user behavior data, the company adopts scientific classification and feature model to data mining and user modeling, and maximizes the "User Portrait", analyzes and obtains the user multidimensional information and realizes the business value of the data.

Although such advertising has a certain lag, but compared to the past "cast nets" type of advertising, in the precision has been a greater degree of improvement. Deberi said that the "freshness" of user data directly affected the user's response rate. The accuracy of the data to the user's interest is rapidly reduced over time, as the viewer is likely to have completed a purchase behavior. So data light is not enough, the data side must also ensure timeliness.

In addition, the current large data technology to restore data to a terminal, based on PC-side data can not distinguish between the specific data from one or more people, may also appear imprecise. However, with the popularity of mobile internet, mobile phone terminal of a pair of characteristics, for large data tracking to specific users created conditions. Deberi that the existing large data base coupled with real-time data analysis, and even the dynamic tracking of data sources, will help the advertising push more accurate and forward-looking.

In fact, the commercial application of large data is far more than a field of marketing, and the collection of Austrian aggregates has recently developed personal credit data products for Internet finance. "In fact, whether marketing or credit, data collection methods are the same, but the data output dimension is different." "Deberi said.

Large data analysis activates industry chain

According to IDC's research over the past five years, the volume of global data has doubled about every two years. However, there is often a strange phase in the big data chain: Companies with data do not know how to use them, and companies that need data do not have enough data sources or technology to analyze data. In this context, a large number of large data service companies are generated, and they quickly get valuable information from a variety of types of data through large data technologies, and are provided to companies that need data.

As operators of building and managing data pipelines, they have natural resource advantages in large data fields. Take a provincial-level telecom operator as an example, each day can produce 70~100TB data volume, billions of clicks of the Internet record. Operators have recognized the value of information assets and are starting to build their user data warehouses. However, because of the limited experience of industry application and data operation, operators need to apply data mining, need data value conversion tools and operational level strategic partners.

According to the industry, according to the value provided by different sources, there are currently mainly three kinds of large data companies. Three sources of data are: data itself, skills and thinking.

Companies that are based on the data themselves tend to have large amounts of data or at least a large amount of data, but not necessarily the skills to extract value from the data or to generate innovative ideas with data. such as social networks and carriers such as microblogs. The set of Austrian aggregates mentioned above belong to a technology-based company. These companies are able to perform different levels of large data collation and analysis and provide it to companies that need data. Companies based on large data thinking, through the processing of existing data, creatively provide users with more valuable ideas and suggestions. The key to the success of these companies is not in how much data and data are available, but in the way they innovate.

Alibaba's financial business is an important achievement in business innovation based on its data assets. The overall layout of Alibaba in the financial industry has been to the traditional banks, insurance, small loans and other industries to form a shock, especially in technology, mode and thinking has formed a huge impact, and will promote the restructuring of the financial industry pattern. And this is what Ma Yun claims to "shake" the foundation of traditional finance.

One person in the big data business told the China Securities News reporter that his large data service would provide financial firms with an analysis of their personal data and conduct ratings to promote differential pricing of financial products. For example, a lower loan rate is given to lenders with good credit, or lower insurance premiums for cars with good driving behavior.

The contradictions of privacy protection

Privacy issues have been a hot topic of increasingly social internet debate, and the big data age has pushed the debate further. Large data from the specific network behavior, as the individuals who make these actions, the most concerned is of course that their own privacy data will be leaked and abused.

According to media reports, a study by the European Parliament said: Big data on cloud computing has created a more serious threat to personal privacy than imagined. The report also said: Cloud computing privacy threat is underestimated. In the large data age, the existing technology means protection is far from the personal privacy, in addition to the establishment of a sound personal privacy protection laws and regulations and basic rules, encourage privacy protection technology research and development, innovation and use, from the technical level to protect privacy and improve the user protection system.

According to Deberi, the collection of Austrian aggregates used in the non-cookies (access to the network when stored in the user's local terminal data) data, not only to more comprehensive audience description, but also to help protect user privacy information. "In the network, in fact, there are many places are" public places ", such as online shop, website information, etc., users in these areas generated data is our main use. ”

It is understood that the collection of Austrian aggregation in the privacy security has the exclusive initiative of the core technology, the company uses three-level data security technology to comprehensively protect the privacy of user data security. The first stage adopts the collection Austrian aggregation large data collection solution, eliminates the user privacy in the data source; The second stage adopts large data mining and value application solutions, and communication between systems through IPSec Tunneling protocol, with Non-repudiation, replay, data integrity, data reliability and authentication function The third stage adopts the large data mining solution, the Operation Dimension Support System maintains the mining system through the SSL Tunneling Protocol, and has the function of identity recognition and data encryption.