The inevitable way for the development of large data--it and business combination

Since 2000, there have been a number of hot-spot technologies or topics in the IT industry, from earlier high-performance and parallel computing, followed by data disaster recovery and business continuity, and recent cloud computing and large data. It is easy to see that the trend is to constantly shift from technological innovation to business-driven, focusing on how to really drive the user's business.

The rise of large data is also related to the level of computing technology development. Before the 80 's, the application of computing technology is limited to the high-speed mechanized implementation of a particular business or operation, some calculation is implemented through the established programming logic, and the results are delivered; with the enhancement of storage technology, primarily in memory capacity and processor programmability, it enters the era of programmable systems, In this stage, in order to personalize the business needs, we build the IT infrastructure and application to support related business, and through various technologies, such as disaster tolerance, business continuity, compliance audit and other standards, set up the corresponding security mechanism of the business. So we have a more objective understanding of it value, such as total cost of ownership analysis, ROI ratio, etc.

And today, we have a whole new change in the past: data. In any case, the data is always growing, and the underlying cause of today's data explosion is the emergence of new technologies and the data of information that could not otherwise be recorded. Weibo, the rise of micro-letter, video surveillance enhancements, all kinds of RFID technology popularization, who knows tomorrow will not appear a new application began to spread in everyone's intelligent terminals, information interaction, and even record every move of life. The concept of large data contains what everyone is thinking and doing in their hands.

Imagine if you had all this data, what would you do? You can accurately anticipate the trend of various commodity futures next month, because you know what people will need at that time, you can simply achieve zero inventory because you know which customers will be buying at what time, and you can clearly schedule the lifecycle of each product line and when you should develop what kind of product, Because you know what's needed in the market.

But maybe you can't do anything because you can't handle all this data. Today's it is still unable to implement the "Time Machine" of the librarian's artificial intelligence, you can simply ask questions, he will improve the various related raw data.

Fortunately, today's data is not so much, you can, and should pay attention to social networks, mobile data and so on:

Human resources-the ability to quickly recruit and fill job vacancies, and to monitor and enhance the productivity of non-sales people, if they are cost-effective

Supply chain-the ability to change the route of a pickup truck to avoid costly delays due to real-time traffic conditions, weather impacts, and efficient transportation

Purchasing & Supplier Management-to identify trends based on information provided by social media and to adopt smarter purchasing decisions

Finance-the ability to analyze bulk transactions within the group and improve the efficiency of cash flow

Marketing-the ability to tap into the personality and sourcing characteristics of existing and potential customers from social media to provide more accurate customer tiering and accurate targeted marketing

Sales planning-can be based on historical and foreign sales trends, supplier site visits and social networking site chat, forecast this year's Mid-Autumn festival, spring, and other selling the hottest gifts

Store management-the ability to perceive and take positive action when local competitors offer competitive prices

If Kodak can notice the proliferation of digital photos on the web--an order of magnitude every six months--it will not be so out of focus on digital imagery, and if Nokia notices the buzz about Apple in social information, it can be fame before the iphone 4.

It is therefore difficult to define a standard for the IT environment under large data applications, how big it should be? How small? More storage or calculation rate? It all depends on the user, what is the user's business goal? What data sources and methods can be monitored to provide support or alarms for business decisions? What kind of IT systems are needed for these methods?

Some wonder why there are many large data solutions available on the market, rather than large data consulting services and deployment implementations at the IT level. If a few years ago the various deployments of enterprise resource Management (ERP) can refer to the general, then the big data is completely different, the purpose of large data is to help users in the competitive market to find a blue sea, rather than let everyone in the Red Sea to fight more intense.

(Responsible editor: The good of the Legacy)