Four types of data and four companies in the big Data age

Large data is used to describe such data sets, which are larger than the ability of everyday software to acquire, manage, and process data within tolerable deadlines. Some of the leading companies in the network technology are investing in expensive large data technology, with remarkable results. Big Data makes innovative companies the first recipients of new ways of doing business and more successful.

In today's world, big data is everywhere, it affects our work, life and learning, and will continue to exert greater influence.

Large data is used to describe such data sets, which are larger than the ability of everyday software to acquire, manage, and process data within tolerable deadlines. Some of the leading companies in the network technology are investing in expensive large data technology, with remarkable results. Big Data makes innovative companies the first recipients of new ways of doing business and more successful. Through the analysis and mining of large data, the company can discover new business model and improve the process. For example, when you learn about consumer behavior, you can use the discovery for certain changes, such as reducing costs or increasing sales, and creating value. Using statistical methods in any large data set can find useful information that will benefit from commercialization of this information.

Everything is changing in the big Data age, and the answer is to change everything. The mode of operation has changed--making decisions becomes deeply integrated with action; the way in which information is used has changed-from being at the edge of management to being at the centre of all aspects; technology has changed-from batch processing to real-time processing, from segmentation to integration; The way people work has changed- From the command and control mode to operate in a cooperative environment responsible for their own information and interactive applications.

According to the McKinsey Global Research Institute, using large data can produce significant financial value in all walks of life. The U.S. health care utilization of large data output of 300 billion U.S. dollars annually, the annual labor productivity increased by 0.7%, European public management value of 250 billion euros per year, annual labor productivity increased by 0.5%; Global personal positioning Data service provider gains more than 100 billion US dollars, providing end users with up to 700 billion dollar value , the net income of US retail business can increase 6%, the annual labor productivity raise 0.5-1%, the manufacturing industry can save 50% of product development and assemble cost, the working capital drops 7%.

According to International Data Corporation (IDC), the 2011 digital World will produce 1800EB of data, 2012 years will grow 40%, to 2500EB. As of 2020, it will reach 35000EB and there seems to be not enough disk space to store it. For traditional IT companies, the growth of structured and unstructured data is staggering. 2005 Enterprise Storage of structured data for 4EB, to 2015 will increase to 29EB, the annual composite growth rate of more than 20%. Unstructured data has grown even more fiercely. 2005 is 22eb,2015 year will increase to 1600EB, the annual compound growth rate of about 60%, far faster than Moore's law.

In addition to the large amount of data produced by specialized research institutions today (up to 40TB per second of CERN's Ion Collider), large data related to business operations can be divided into four sources:

1. An increasing number of machines are equipped with continuous measurement and reporting operations. A few years ago, tracking telemetry engines ran only millions of dollars worth of space shuttles. Now, car manufacturers in the vehicle equipped with monitors, continuous provision of vehicle mechanical system overall operation. Once the data is available, the company will make every effort to profit. These machine sensing data fall into the range of large data.

2. Computer-generated data may contain interesting information on the Internet and other user actions and behaviours, thus providing a potential useful understanding of their desires and needs.

3. Data/information generated by the user itself. Text messages generated by emails, text messages, tweets, etc.

4. The largest data to date is audio, video and symbolic data. These data structures are loosely structured and large in number, and it is difficult to dig meaningful conclusions and useful information from them.

Large Internet-focused companies such as Amazon, Google, EBay, Twitter and Facebook are using the latter three types of information to understand consumer behavior, predicting specific needs and overall trends. The first type of data may produce less business, but it can drive some of the business model to change in real terms. For example, car sensing data used to evaluate drivers ' behavior will drive a profound change in the auto insurance industry.

Big data has changed the way all the companies in all industries operate. From the understanding of the market to how to tap business information, large data can insight into each change. An industry dedicated to collecting and analyzing large data has been formed, having a profound impact on existing companies. According to the survey, 10% of the companies think that over the past five years, big data has radically changed the way they operate. 46% of companies agree that big data is an important support factor in their decisions.