Big Data, Big Data What is it? How much data is called big data? Prosperous moment analysis of the data to us, have said does not analyze the data business will not last long, but what kind of data it is big data, what data is the biggest of it?
If you had any contact with large data, then you do not know exactly how big data, what data can be called big data to big. Well, according to data collected between ports, businesses and individuals terminal end, a large number of levels of data are different.
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What is Big Data is considered exactly how big data
Big data?
How much data is called big data?
Many people do not come into contact with large data, are difficult to clearly know how much the amount of data that can only be called big data. Well, according to data collected between ports, businesses and individuals terminal end, a large number of levels of data are different.
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End enterprise level (B-side) data of nearly a million, can be called big data; personal end (C-terminus) to reach tens of millions of large data levels. Collection channels no specific requirements, PC side, the mobile terminal or traditional channels can be focused to achieve this magnitude of valid data, form data service can be. Very interesting, as you can see. 2B and 2C, the difference between the two types of big data by two orders of magnitude.
Some small companies, the size of data only 1000-10000, but after collection and analysis, but also from the targeted sum up the principles of this group, the user is also able to guide enterprises in a certain degree of analysis, acquisition or service work, but this is not a big data, but the general data mining.
Just days ××× share of that case, saying that earlier this year a principal street vendor selling fruit with 50 middle-aged man, he does not understand big data, but he became its hand to collect fruit: he knows what how much rain the next place, the sweetness of the fruit will be how much and where consumers would like to eat this sweet fruit. Sold last sold 137 stores, 470 million in annual sales.
This really is a small data mining, but not the data analysis. Although born out of this big data analytics, large data-oriented but is more of a mass of data, by means of the analytical methods broader knowledge database. Most of the company's data source data is massive, its collection and analysis, is not confined to the individual, but in a very, very broad target group is expanded.
Chain Big Data is like?
I was in an interview, in accordance with the company's big data on upstream and downstream relationships in the industry chain, proposed to divide them into three different categories:
Big data acquisition company
The so-called "Find data" inside could be split in two ways:
In the normal operation of the process itself can produce a large number of data sources;
Through cooperation with telecom operators, financial institutions, access to data sources.
Big Data Analytics company
This type of company, basically have their own set of models, but most of the database model from the same number of mechanisms, including statistical models, algorithms, etc. depth learning. Also US-based IBM, cloudera developed application-oriented analysis module, and so on.
Big data marketing company
Although data are selling, but not a single sale of data, but on a complete solution of data, such as precision marketing and so on.
How these three companies is collaboration, and the role of big data? The most easily understood is now put on the micro-channel circle of friends in our lives ads.
Tencent when the advertising to each user, have the user precise analysis done. After the people by collecting habits in the micro-letter, and then analyzes the user's spending power, consumer habits, the formation of a precision marketing solutions to advertisers to generate some targeted advertising.
For example, Lancome ads will never promote to male users, advertising luxury cars will not be pushed to the graduates. The entire micro-channel advertising systems are used in the analysis of large data models, there was general feedback, Tencent advertising conversion rate on ads served than Netease, Sina and other platforms served, it has benefited from a large data base of Tencent.
The investment value of the company's big data
How to understand the investment value of big data?
Big Data is now so fire, its commercial value is obvious, but really honored, not many people.
To deliver on the business value of big data, the first requirement is to achieve data on the order of large data. So at present, the amount of data in the most advantageous BAT is three. In the PC era, Baidu advantage in the data is very strong, but in the mobile era, Tencent and Ali achieve the go-ahead.
Tencent micro-channel, QQ, to get the amount of data generation mobile terminal ninety; Ali use its resource consumption data, and more perpendicularity. So for SMEs, start-ups, focusing on the commercial value of the cash becomes, how their own smaller scale when using a large data resources of others for their own business better service. This is a deep-seated need to judge and mining.
Therefore, the data related to the company, at the time of investment judgment, not only to see the development of existing businesses, more importantly, in the course of his ongoing development, can not be accumulated valid data, accumulated data of high accuracy, achieve real-time updates of data. Such companies can better build barriers to competition.
For example, in the field of developer services, such as talkingdata Aurora, etc., when we look at the project Fosun brothers very important point, which is now operated by the project's business is to provide services for a single developer? I was in the service, to their own the accumulation of valid data, the formation of long-term barriers?
2B is a big industry data breach
I have mentioned before BAT for large data collection is a monopoly, start-ups want to achieve massive amounts of data (ten million or even billions of C-terminal user) at the C-terminus is very difficult. At present, the domestic real live billions of dollars of monthly app only 15, before the app is BAT *** 10 is controlled rate, such as micro letter, QQ, Taobao, UC browsers. If the bypass BAT, to have the C-terminus of massive data, only relatively traditional telecommunications, finance and so on.
See, if want to invest in big data areas of the company, to start from the C-terminus of difficulty is high. So, I think if you want the big data industry layout, 2B field is the key: on the one hand 2B late development, BAT has not yet formed a monopoly; second, the development threshold is relatively high; third, the amount of data relative to demand less reached 100,000 level that can analyze large data service, so if you want to invest in big data field, pay attention to the main areas 2B field.
2B in the field, there are three different categories:
The first category is B2B trading platforms; the current trend, basically vertical field of e-commerce trading platform for industry, core competence is to break the information asymmetry between buyers and sellers, opaque. So the key point of this area of the company is not a record trading volume, but every valid data. In this area, we invested Huimin network, primarily serving small and medium business over its suppliers and trading platform, then such a variety of "found" series of projects, and so on.
The second category, is now very fire of enterprise services to SaaS-based; such as customer management CRM, HRM Human plates and so on. They get user license and ensuring data security of the premise, to accumulate a large number of business users through the service business, and corporate employee data. For example, only network management and so on.
The third category is for the service to developers; cloud storage, statistical operating data push and instant communication within the app.
Fosun brothers mainly to invest in this project among the three types of 2B, 2B because the business model of these projects can be effectively accumulate large data. This is why big data Fosun also concerned about the field of business services and 2B - 2B because of business services in the field, to find the best and most effective big data.
2B future industry investment targets
If we predict the future of this industry, I have the following view.
Big data has a rich source of business, will become the investment targets within the industry's hottest.
In the big data industry, analysis of differences algorithm, the accuracy of analytical results caused by the practical difference is the difference between 93 points and 95 points. The quality difference caused by the data source, are different 60 points and 90 points. In particular, a large and constantly updated data, the algorithm is able to verify the accuracy and optimize effective way to big data analysis results.
Binding project ahead of the most urgent demand side data, you will win.
At present, basically the financial sector in the field of big data customers are willing to pay the most, banks, insurance companies and so on. They want the user multi-faceted analysis and services, so the purchase intention is very strong. The next layer is the emerging Internet companies, in order to obtain a more accurate user, improve the conversion rate, but also more willing to pay, such as the new American and so on. The next step may transition to the consumer goods industry were to go.
Based on those opportunities of Big Data
Intelligent hardware and artificial intelligence is still a long harvest
Big Data and intelligent hardware combination model, in fact, currently it is very challenging, the main reason is that on the order of big data. Currently shipments of smart hardware is far from matching the data required for large orders of magnitude. At present, the largest shipments millet bracelet, and the second is 360 children guards. The remaining intelligent hardware shipments, often in the hundreds of thousands to hundreds of thousands of the order is good. This requires the C-terminus with large data of millions, one hundred million times it is also a difference.
Field of artificial intelligence is relatively better, are situations such as Japan liter. Overseas in Google, Amazon, Softbank has invested in a number of investment targets, but still some of the concepts in the field of project is not immediately possible commercial services. Including Google unmanned vehicles, even has been able to accumulate a million miles of safe driving mileage, but still has some application process. There are also a small number of angels, early institution, has been optimistic about the field to start investing, but its flowering period that may have to wait at least five years.
Therefore, investment in this area to have a certain patience, there is now more hope that the field of honor, including the semantics of voice recognition, AR / VR, unmanned aerial vehicles and so on.
SaaS project what kind of fire?
In fact, many people do not understand the SaaS model and the traditional software services in the end what is the difference and why it is a big data based on the rise of industry?
SaaS and traditional software service, the middle of a lot of difference. The most basic difference is that their entire architecture is different: SaaS is built on a public cloud, standardized service modules, data is also stored on a public cloud SaaS platform. The service is basically a traditional software deployment in the LAN. This architectural difference decided that all the other differences.
For example, since SaaS architecture in the cloud, and adhering to the standardized, universal principle, therefore, the implementation process is very fast. At least, before the implementation of on-site construction work is much less, then get the user corresponding to speed up. The traditional model can take a long time to a total of hundreds of customers, SaaS model can accumulate thousands, tens of thousands of customers are not difficult in a short time.
As another example, different, traditional software has pre-paid model on the implementation of fees, the annual cost update, specialized custom service charges, fees, etc. troubleshooting. Overall speaking, high costs, complicated payment, often only large companies only from consumption. The SaaS hand to reduce the initial cost of deployment, and the system architecture and can serve multiple users. It's basically charging mode, is closing monthly fee or annual fee, only a few hundred pieces a month, many small and medium enterprises, can enjoy the service.
Q & A link
Q: Participating in small, scattered data, SaaS investment of AI's work?
A: I think the only way to currently small, scattered want to participate in this area of investment, probably through equity crowdfunding. Barriers to entry of these projects decided, in order to cast small, scattered through such projects best professional crowdfunding platform.
Specifically, for several reasons:
High threshold projects. We tend to be small, scattered contacts project through their own circle of friends, but this type of project entrepreneurs are basically professionals, we are out of the reach of small, scattered.
Such projects high professional experience requirements for founders, small, scattered, difficult to make this project a professional tone. And professional crowdfunding platform, before the project to promote small and medium investors to give you, I've done a background check on the project. For the realization of small, scattered investment to achieve a protection.
All in all, this type of project industries with high barriers to entry, high professional requirements, want to invest in small, scattered will have to get off this crowdfunding platform angels responsible
Q: Everyone says we are now in the age of the Internet, you emphasized that we are now data in the Information Age. How to understand this?
A: We are already in the era of big data, big data and Internet mobile Internet is not in conflict, but it is the Internet, in particular the emergence of mobile Internet, so that big data can greatly enhance the efficient collection, so large data and mobile Internet era came to be hand in hand together.
What is big data, how much data can be called big data, you know it, if you want to learn big data technology, then it up, way in the future, we know how to analyze the data, you can grasp the future!