Everyone can aspire to big data.

Source: Internet
Author: User
Keywords Large data large data helm large data helm talent large data helm talent large data program large data helm talent large data program become

Now, talking about big data is not new, all walks of life are competing in the excavation of large data "great value", resulting in a wide variety of customized large data programs. On the other hand, there are large groups of "double-edged swords" that hold large data at risk. Is big data a business opportunity or a crisis? If you have to choose, I think it is business opportunities, and any business opportunities are risk factors, the risk need not blindly expand to sensational. If everyone can obtain success from the big data, then the benefit is the social overall progress, but will not change the social individual or the group's strength pattern. I think, although large data value is already the majority of the people, however, not everyone can become large data at the helm, successful people in the future for a long time belong to the minority, can only say that the benefit of the public. If you aspire to be a big data pilot, you need to consider the water first.

The author of this paper is to discuss the large data at the helm is defined as two categories, one for the large data solution provider, the other is the industry users. Large data solution providers use their own technology or collaborate with third parties to integrate solutions for user services. Among them, the competition of the same trade cannot be neglected. To be at the helm is a wise man who is differentiated. Industry users, with large data, mainly through large data to try to change their survival status. Among them, who first step to the value of large data, who may become the helm. As for the above two groups, the author gives some suggestions to the large data of water test, as a suggestion of 2013 years.

Become a large data-Helm large data solution provider Test Water essentials:

There are a number of vendors offering large data solutions, with the pinch pointing to IBM, SAP, Teradata, HP, Oracle, Intel, EMC, Microsoft, the wave ... Over time, more vendors will be involved in providing large data programs. This is bound to attract competition. Stand out and become the helm, consider the following points:

1. Flexible and diverse product portfolio

To enlarge the data solution provider, the product mix must be diversified, which involves the user-group breadth problem. In the era of customization, the large data solution involves not only diversification but also flexible combination. This is not only a user-tailored age requirement, but also a flexible combination to help the program business save cost.

2. The product plan to simplify

The overall solution is not the more complex the product the more advantages. The scheme maker can try to simplify the scheme. The so-called simplification is not to reduce the product category, but how to integrate the integration of the problem, at present in the integration of integrated, IBM and Oracle performance better. IBM's Puresystem, Oracle cover from server, storage, database, middleware, fusion applications and so on, including Exadata database cloud server, exalogic Middleware cloud server, exalytics Business Intelligence cloud Server, large data machine and SPARC Supercluster integration of soft and hard integrated product solutions. It is a way to simplify it by making an integrated system on a product-wide basis. After all, the user's business, or the internal generation and external demand of the volume of data increasingly in the explosion and miscellaneous, large data product solutions if cumbersome, all levels need manual intervention or closed operation, then not only will increase the cost of the Program Guide, but also to increase the user's hands-on operation of the difficulty, outweigh the gains.

3. The training of large data professionals

Talent is the key to maintaining sustainable competitiveness, especially in the IT circle where technology products are being updated quickly. The author thinks, the big data think tank of the scheme business will be the most important element that directly affects whether it can become the big data helm. The programme can increase the professionalism of its large data professionals by digging up talent from competitors or by offering training courses of its own. January 20, in Beijing University of Aeronautics and Astronautics, China's first "big Data technology and applications" software engineering master started. This can be seen as a useful move in the domestic cultivation of large data professionals. And another question comes along, who teaches the question. After all, the shortage of large data talent is a reality, know how to do training of talent is not many. Program business can take the training of large data professionals of the road, and the prerequisite is to find a capable person can teach. By contrast, digging up talent seems a lot easier. In fact, this is an ecological chain, a large number of mining talent to more talent training, to the Big Data program excellence.

4. Good drilling large data industry "empty Vault"

To help users to explore large data opportunities, the program business people like to use a variety of slogans or publicity platform, to show users their product solutions insight. Flock to, with similar propaganda caliber to recommend to the user, then users in a variety of options, often rely on their original inertia thinking to choose their own more recognized brand, this test is only the brand power of the scheme, the big data on its own "strength", care rate accounted for is not high. Sometimes, we need to know how to reverse thinking and learn to take loopholes. When most of the solution is talking about the opportunity mining, reverse thinking, in other words, the rescue risk, the effect of the spread may be easily immediate. Unfortunately, in the case of large data risks, the industry experts talk a lot, and when they preach their large data products, they also mention it, but basically when they talk about how to help users dig out the value of large data, they simply strip down the so-called risk-reducing word eye. In reverse thinking, mining large data "empty Vault" aspect, IBM's performance is more eye-catching. IBM is explicitly proposing a "smart storage" strategy to reduce the risk of large data. The great scheme maker may not be blown out. In the discussion of large data opportunities in the field of proposal, IBM also positive participation, but also understand the reverse thinking to the user to convey large data risk concept, in order to launch their own solutions. Just to change the angle, you can drill into the large data industry, "empty Vault", a winner, this is the current lack of many programme providers. blindly follow, but do not understand the loopholes beyond, large data of the helm is doomed to not belong to this category.

To become a major data-steering industry user Test Water essentials:

Industry users as the direct users of large data programs, their use or not, the extent of use or popularity, the large data program to the strategic formulation and competition pattern will have an impact. In parallel, will affect their own industry status. To become a large data-steering, so that large data services really drive their business value, industry users have the following suggestions for water, for reference only.

1. Clear the goal of large test water data

The emergence of a new industry, the phenomenon is inevitable, no one seems to want to fall behind. However, the water test large data industry can not be blind, which covers the enterprise business data centralized integration, data storage, data analysis, data management and so on, it can be said that a ring of blindness, the whole chain will "fall apart", and then affect the development of enterprises. What is the goal of large test water data? According to the target to the control of large data-related business chain each node, the advantage of this is to focus on the control of the enterprise budget. Success belongs to those who are prepared. To become a large data-steering, it is necessary to fully analyze their own needs, so as to determine the target to start the industry users.

2. Rational choice of cooperative supplier option step

Although the twist of inertia thinking is difficult, when choosing large data partners, industry users can not only ignore the reputation of the brand, but also evaluate the service qualification of the scheme provider. It is recommended to choose a supplier with overall solution service, and to select a cooperative supplier step in the large data business chain, which will avoid the problem of the one-woman of the data of one side. Song, chairman of the China Business Federation's Data Analysis Professional committee, pointed out that the big data industry is still in happy enclosure stage, industry chaos is unavoidable. He said that false qualifications, service is not standardized, quality control is not strict and so is the main problem in this industry. In the large data industry is not really mature now, it is recommended that the water industry users rational choice of cooperative suppliers, avoid the risk of cooperation at the same time from the large data business to find the return value of investment.

3. Large Data Investment 37 open

Large data investment, recommend equipment (program) procurement and personnel training 37 open. At present, many industry users too much in the equipment (program) to work hard, ignoring talent training. The purchase of equipment (scheme) is hard investment, when the enterprise large data business category expansion and equipment (program) aging or vulnerabilities appear, equipment (scheme) upgrade optimization is unavoidable, and industry users in this process to cultivate a group of large data business capable talent, not only can save in equipment (program) On the continuous hard investment, at the same time to feed their own large data business. To become a large data helm, the industry users themselves need to have the basic data analysis and technology personnel, otherwise, the crisis exists, by Third-party solutions to provide data storage, data analysis, data disclosure for the time being, the authenticity of data analysis is worth the industry users smell.

There has been a growing lack of skepticism about the trend of the big data age. People are thinking more about how to cope with and take advantage of a series of changes brought about by the big data age. The big data has even risen to a number of national strategic areas: in March 2012, the Obama administration issued a "large Data research and development program" announcing the upfront investment of more than $200 million trillion in the development of large data-critical technologies to preempt data resources and exploit the commanding heights. May 2012, the United Nations "Global Pulse" program released "Big Data development: Opportunities and challenges" report. October 2012 China also established a large data committee of China Communications Association. As a big data industry can be sustainable development of the two main protagonists: large data solution providers and industry users, yearning for large data value of the beautiful scene easily, become the real big data in their field of the helm is not easy. Radiation, rising to global competition.

(Responsible editor: The good of the Legacy)

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