An article for you to understand the present and future of big data

The development premise of Big Data

　

The concept of big data in fact in 1998 has been raised, but only now began to develop, these are in fact, and the rapid development of mobile Internet is inseparable, the high-speed development of mobile Internet, for the generation of big data to provide more big data of the hardware premise, such as smart phones, smart hardware , car networking, PDA and other data generation terminal. These intelligence through the mobile communication technology and people's life closely together, in the flow of traffic, the behind the flow of information, also produced a large number of data.

　

The second is the rapid development of mobile communication technology, in the 2G era, wireless speed slow, data generation is very slow, the volume of data is not enough, so still can not form big data, and to the 4G era, the increase of terminal data, so that any mobile terminal in all the time to produce a large number of data, This is also one of the conditions for the arrival of big data.

　

The third aspect is the rapid development of big data-related technologies, such as cloud computing, cloud storage technology, their rapid development, is the birth of big data hotbed, without these technologies, even if there is a large number of data can only feel powerless. Traditional storage technology is relatively backward, according to different data implementation of a single storage, this obviously can not meet the needs of big data, and the cloud era of storage systems need not only the capacity to upgrade, the demand for performance is equally urgent, and in the past only for limited users, in the cloud era, the storage system will face a broader user base, The increase in the number of users makes the storage system must also have a rapid increase in throughput performance, only in order to respond quickly to requests, the maturity of cloud storage technology for the rapid development of big data laid the foundation.

　

What is big data?

　

But when it comes to big data, it's estimated that everyone has heard only the concept, but what exactly, how it is defined, not a standard thing, because in our impressions it seems like a lot of companies are called Big data companies, there are hundreds of kinds of business form, it doesn't feel good to understand, so I suggest or literally understand big data in Victor • The big Data era, written by Meyer-Schoenberg and Kenneth Couqueil, mentions 4 characteristics of Big data: One is large, one is value, one is fast, and the other is diversity.

　

One is the number is larger, roughly how big, is big to PB level, even ZB level, 1PB equals 1024TB,1TB equals 1024G, then 1PB equals more than 100 g, of course, the specific calculation method can be related data to query, in short, Compared with the traditional data stored in a single site database, it is more than a hundredfold, and only the volume of data reached the petabyte level above, can be called Big data. The second is the big value, the value is the large amount of data in a deeper step of the evolution, that is, if you have more than 1PB of all 20-35 young people in the country online data, then it naturally has commercial value, such as through the analysis of these data, we know these people's hobbies, and then guide the direction of product development and so on. If data were available for millions of of patients nationwide, the data could be analyzed to predict the disease. These are the values of big data.

　

The third is diversity, if there is only a single data, then the data will be worthless, such as only a single personal data, or a single user submitted data, which is not known as big data, so that big data needs to be diverse, such as the current Internet users, age, education, hobbies, Personality and so on everyone's characteristics are different, this is the diversity of big data, of course, if extended to the country, then the diversity of data will be stronger, each region, each time period, there will be a variety of data diversity.

　

The fourth one is the speed, is through the algorithm to the data logic processing speed very fast, 1 second law, can quickly obtain high value information from various types of data, this is also with the traditional data mining technology has the essential difference.

　

In short, these are the four characteristics of big data, only the data with these characteristics can be called Big data, so what is the real big data? Industry-renowned and big data-related companies, seven Qiniu storage will be held on August 29 , 30th, a big data meeting, for companies located in the big data technology industry chain, we should be able to get more dry explosive material.

　

Three levels of big data

　

Speaking of big data, big data has three levels, the first is the data acquisition layer, to the app, SaaS as the representative of the service. The second technical service layer, the Big Data Technology Service layer represented by seven cow cloud storage, including data storage, data analysis, data mining and so on, the third is the data application layer, based on data, for the future mobile social, transportation, education, financial services. Below I will mainly talk about the next three levels.

　

Data acquisition layer--app, SaaS, Smart Hardware Services

　

in the era of mobile internet, the source layer of big data has two aspects, one aspect is personal-oriented data source front-end such as a variety of apps, on the other hand is the product of SaaS service for enterprise service. For individual apps , in the Diet field of apps, such as hungry, the user through the app to choose a meal, place a single, through the app interaction will form the big data in the Diet field; In the area of the field, such as the Da Da Bus, users by using the app to ride the traffic, go to work, will form the traffic field of big data , such as clothing assistant, the user through the app to choose the color of clothes, style, to match, will form the big data of service class, of course, there are seconds to clap, quick look and other entertainment category of consumer data. App for individual users, to meet the needs of users as the main starting point, the production of user data, including personal data, including the group data, as the volume of app users grow, these app data becomes big data.

　

Personal data sources that generate data directly from the needs of the user, and--saas services for Enterprise Services are different, and they provide the enterprise with a complete set of solutions, and generate data, robot, face recognition technology, Weather Plus, Conway vision, etc. They serve the enterprise through the perfect solution, end-User service, resulting in big data, data acquisition layer, is the source of big data, is also the basis of big data.

　

Cloud storage's role in promoting big data

　

With data acquisition layer, the next step is the storage layer of data, the use of cloud storage technology to store data on the cloud host, to ensure that the data security, stability, and efficiency are required cloud storage technology to complete. Cloud storage is mainly responsible for data storage and computing, such as seven of cattle cloud storage technology, cloud storage technology is a big data development across the past, without cloud storage technology, big data can not be developed.

　

Maximum data for enterprise storage in cloud storage

　

The current cloud storage is divided into public cloud storage and private cloud storage, public cloud storage is mainly for individuals, such as Baidu Network disk, and private cloud storage is mainly enterprise-oriented, in fact, cloud storage for enterprise storage of the ultimate source of big data is from individuals, such as many of the current SaaS services, IM, statistics and other enterprise services, Services are primarily personal-oriented apps, and cloud storage like the seven Qiniu storage is based on the lower level, on top of the cloud host, and in all personal services, Enterprise services, so that the seven Qiniu storage should accumulate more big data, and through the end of the month, this "Data reconstruction future" conference, I think I can get more dry goods about big data.

　

Cloud storage meets massive data storage requirements for large volumes of data

　

With the rapid development of mobile Internet, traditional storage methods have been unable to meet the demand in capacity, performance, intelligence and so on. The advent of cloud storage, such as the cloud storage technology similar to seven cows, makes up for the shortage of traditional storage, and realizes the storage space increase and expansion through the functions of virtual large capacity storage, distributed storage and automatic operation, which improves the storage efficiency of automation and intellectualization function. In addition, the scale effect and elasticity expand, reduce the operating cost, avoid the waste of resources.

　

Cloud storage technology saves developers ' costs

　

In particular, the popularity of mobile internet, making the app industry has an explosive growth, the number of apps has reached more than 300 million, while the picture app, video app, audio apps such as camera360, Youku Video, Litchi FM and other apps will generate a lot of data in the development process, For these data, if the enterprise itself to develop a distributed storage system, this may need to build a dozens of-person development team, the cost will be greatly increased, and by using similar seven cattle-like cloud storage, can save enterprise costs, so that enterprises grow faster.

　

Cloud storage technology provides the basis for data analysis of Big data

　

As a big data storage provider, cloud storage has a very large data potential, cloud storage platform for big data analysis provides a "water" source, with this data, while the configuration of some data analysis tools, can produce some very valuable analysis data report.

　

For example, based on cloud storage services, seven of cows can provide enterprise data analysis, such as where the application is accessed more frequently and how the user prefers the application, but does not involve the analysis of user privacy-related data. Of course, it is also possible to provide audience user behavior, as well as features, for the entire image industry, the video industry, and the audio industry as a group feature.

　

These are the cloud storage in the storage of data volume to achieve the characteristics of big data, can do a series of analysis basis. Therefore, cloud storage is one of the most important aspects of big data development.

　

The future of big data industry applications

　

said the big data acquisition layer, the data storage layer, then finally said the big Data application layer, since has the big data, then takes the big data as the foundation, will produce with the mobile finance, the mobile social, the network, the online education and so on many aspects application.

　

Mobile Finance

　

With the development of mobile Internet finance, financial transaction and payment have been extended from desktop computer to mobile Intelligent terminal, the enterprise can only gain the internal insight into the operation situation, or obtain the incomplete statistic information from the market, as a decision-making reference. For example, UnionPay Chie can help enterprises to understand the market from the outside, insight into the position of the opponent, understand the market trends and their status, through the use of their own advantages through the industry-wide transaction records to obtain high-quality basic data, and for the enterprise to complete a large number of cumbersome data collection, cleaning work, integrated into the basic Business Analysis database , let enterprises do more with less.

　

When the basic data enters the enterprise database, through the user portrait simulator of UnionPay Chie, the target customer consumption behavior is modeled, and the historical transaction behavior is divided into the common characteristics of the target customers, thus complete from the consumption of gender, consumption age, consumption habits, consumption frequency, consumption area, The multi-dimension of consumer preference describes the contour of customer group, and obtains the customer's upstream and downstream related transaction behavior characteristics, so that the enterprise can truly recognize the whole picture of the customer group and make effective business decision.

　

Mobile Social

　

With the increasing number of users of social applications such as tenderness, love remembering, social behavior of users will become the basis of analysis of big data, analyze the user's social time, object, location and behavior, can analyze the user's hobbies, age, needs, and based on the user's big data, can be targeted for these data marketing, Thus greatly improved the marketing effect, and compared to the previous marketing means, is the basic personnel planning and imagination, no data reference, marketing effect is not good to control. For example, the tenderness can be through some user data for the enterprise to recruit the right people, but also for some users to provide some suitable positions, to complete the demand and supply and demand of high-precision matching.

　

And love in mind, is a record of love-oriented social apps, more vertical, then by analyzing the data between couples, you can get more emotional data, so that some of the age of men and women to provide love guidance. These are all applications based on big data.

　

Application of the class

　

The deep development of mobile Internet has promoted the prosperity of the network, and the custom bus application, which is represented by the DA-Ta bus, is the representative application of big data.

　

Traditional bus travel in the bus station, bus route setting, relatively fixed, through the analysis of a city group travel data, can get the crowd with time travel rules, such as know in the morning 8 points for travel peak, and from a community to an office building of the maximum number of people, Then I would like to customize a bus line out, for users, to meet the needs of users, and for the bus company, is to optimize the traffic route, saving resources, indirectly raise the cost, these are the benefits of big data.

　

......

　

There are more areas where big data can be used, such as big Data healthcare, Big Data marketing, wearable devices, and more. With big data you can create more value, as one article says, making things easier with big data, making the reality from three-dimensional space into a two-dimensional code space, just like the wormhole of the universe, that can reach the target directly. In the past there is no big data for reference, we need to experiment several times to know that the road is right, but now with the big data to do data reference, we can directly reach the end point. So, big data makes things easier.

　

Mobile Internet Li Jianhua,: ydhlwdyq, mobile Internet Industry Promotion personage, reprint this article, please indicate the author and, otherwise will hold your legal right.

Copyright NOTICE: This article for Bo Master original article, without Bo Master permission not reproduced.

An article for you to understand the present and future of big data