9 High value large data applications that change the world

1. Understanding, positioning and providing services to customers

This is one of the largest and most widely known data applications in the world today. The focus here is on using large data to better understand customers and their behavior and preferences. Companies are keen to collect social media data, browser logs, text analysis, and sensor data to get a fuller picture of their customers. In most cases, the overall goal here is to create a predictive model. For example, US retailer target, by using large data analysis, can now predict very accurately when their customers want children. In addition, by using large data, telecoms companies can now better predict customer churn, Wal-Mart can better predict which products will be hot, auto insurance companies can understand the driving standards of their customers, and the government can understand voter preferences.

9 High value large data applications that change the world

2. Understanding and optimizing business processes

Large data is also being used more and more to streamline business processes. By leveraging predictive information from social media data, web search trends, and weather forecasts, retailers can optimize their inventories. One of the most widely used data analysis business processes is supply chain or distribution route optimization. In this regard, geo-positioning or radio frequency identification sensors are used to track goods or delivery vans and to optimize routes by integrating real-time traffic data. Human resources business processes can also be improved by using large data analysis. This includes optimizing talent recruitment and using large data tools to measure corporate culture and people participation.

3. Large data to improve everyone's life

Big data applies not only to businesses and governments, but also to everyone. We can now use data generated from wearable devices such as smart watches or smart bracelets, which allows us to track our calorie consumption, sleep patterns, and so on. We can also use large data analysis to find love, and most online dating sites use large data tools and algorithms to help us find the right target.

4. Improving medical and research

The computational power of large data analysis allows us to decode the entire DNA in a matter of minutes and allow us to find new therapies that better understand and predict disease patterns. Just as everyone can benefit from the data produced by smart watches and wearable devices, large data can also help patients heal better. Future clinical trials will not be limited to small samples but will serve everyone. Large data technologies have been used to monitor premature babies and sick babies. By recording and analyzing each heartbeat and breathing pattern, doctors can now predict 24 hours before any symptoms of physical discomfort occur. In this way, doctors can save sick babies earlier.

5. Improving Sports Performance

Now many sports have begun to use large data analysis techniques. For example, the IBM SlamTracker tool for tennis nasal congestion, we use video analysis to track the performance of each player in a football or baseball game, and the sensor technology in sports equipment (such as basketball or golf clubs) allows us to gain data on the game and how to improve it. Many elite sports teams also track the activities of athletes outside the game environment-by using intelligent technology to track their nutritional status and sleep, as well as social dialogue to monitor their emotional status.

6. Optimize machine and equipment performance

Large data analysis also allows machines and devices to become more intelligent and autonomous. For example, large data tools are used to run Google's self-driving car. Toyota's Prius is equipped with cameras, GPS and powerful computers and sensors to drive safely on the road without the need for human intervention. Large data tools can also be used to optimize smart grids. We can even use large data tools to optimize the performance of computers and data warehouses.

7. Improving security and law enforcement

Large data is widely used to improve security and law enforcement processes. We must all know that the National Security Agency (NSA) is using large data analysis to counter terrorist activities and even to monitor our lives. Other enterprises use large data technology to detect and prevent network attacks. Police can also use large data tools to catch criminals and even predict criminal activity, and credit card companies use large data to detect fraudulent transactions.

8. Improved and optimized cities and countries

Big data is also being used to improve many aspects of our cities and countries. For example, it allows cities to optimize traffic based on real-time traffic information, social media, and weather data. Many cities are experimenting with large data-analysis techniques, trying to turn into intelligent cities, adding transport infrastructure and utilities.

9. Financial transactions

Large data in the financial industry are mainly used in financial transactions. High-frequency trading (HFT) is an area where large data applications are more widely used. Among them, large data algorithms are used to make trading decisions. Now, most equity deals are done through large data algorithms, which increasingly take into account the information of social media networks and news sites to make buying and selling decisions within seconds.

These 9 areas are the areas where large data applications are most common, and of course, with the growing popularity of large data tools, there are many other large data applications and many new applications.

(Responsible editor: The good of the Legacy)