Large data or drive mobile computing innovation to further develop

According to foreign media reports, the world is full of data. Imperial Commercial Bank of Canada predicts that information will increase 50 times times over the next 10 years. IDC, a market-research firm, has also made a similar forecast, saying that data will grow 44 times times from 2009 to 2020.

Mobile devices, social networks, wearable devices and the internet of things will play an important role in driving data inflation.

Six years ago, Apple released the iphone, sparking a firestorm in the E-commerce world. The birth of the iphone marks the arrival of the era of "design, software and hardware as the most important concept in science and technology".

So is the data likely to trigger the next change? Many people think it's possible.

Business Insider, a consultancy, has published a report on "Big Data and mobile devices" by the FDI of its research institute. The report defines large data, detects links between mobile devices and large data, analyzes their potential, practical applications and possible difficulties, considers large data collection approaches, and finally answers some of the most frequently asked questions about large data and mobile devices.

The following is a review of the relationship between large data and mobile devices:

1. Large data needs to be defined: Large data is usually defined as a dataset that meets the requirements in terms of quantity, type, and rate of three attributes. But there is more to it than that. "I want to say that there is a fourth attribute, that is value," said Jeep-Jones, vice president of the Skyhook Product division, a map service provider. "To make sense, data needs to be captured and stored efficiently, and then some people manage the data, analyze them, and extract the valuable parts." Data, large or not, is not worth taking time to deal with if it is worthless to people.

2. Mobile devices are ideal for capturing large data. Moving large data is not just a function of the popularity of mobile phones and the pattern of consumer use. Applications and other services also generate data during the user's use. Technically speaking, the process and the traditional network data generation process is not much different. The difference is that consumers create more data through mobile devices when they turn behavior into digital channels and leave a long list of data that records consumer behavior. Even if we don't use mobile phones on the surface, we're still creating data streams.

3, this data can be used to optimize and personalize the mobile device experience. Moving large data can be used in many ways, but it is often used to optimize and personalize mobile services. For example, application developers may use analysis from the American application analytics company flurry to improve applications. Retention time is a key metric for developers. Developers can compare the user retention time of their applications and the retention time of all other applications to learn how to improve them to increase these numbers.

4, may help lead to a surge in mobile advertising business. One major part of moving large data is local data, and local data is expected to help change the mobile advertising industry. Its conduction real-time, super local, directional advertisement ability represents the advertisement market potential important evolution direction.