Big data applications can help us get useful value in life. As the application of big data becomes more widespread and the industry of applications is getting lower and lower, we can see some novel applications of big data every day to help people get really useful value. Many organizations or individuals are affected by the analysis of big data.
Big data applications in some areas First, medical big data is more effectiveIn addition to Internet companies that have been using big data earlier, the medical industry is one of the traditional industries that make big data analysis the first to grow. The medical industry has a large number of cases, pathology reports, cure programs, drug reports and more. If these data can be collated and applied, it will greatly help doctors and patients. The number and variety of germs, viruses, and tumor cells we face are constantly evolving. When a diagnosis of a disease is found, the diagnosis of the disease and the determination of the treatment plan are the most difficult. In the future, with the help of big data platforms, we can collect different cases and treatments, as well as the basic characteristics of patients, and establish a database for disease characteristics. If the future genetic technology is mature, it can be classified according to the patient's genetic sequence characteristics, and establish a patient classification database for the medical industry. When the doctor diagnoses the patient, he can refer to the patient's disease characteristics, test report and test report, and refer to the disease database to quickly help the patient to confirm the diagnosis and clearly locate the disease. When formulating a treatment plan, doctors can select effective treatment plans with similar genes, age, race, and physical condition according to the patient's genetic characteristics, and develop a treatment plan suitable for patients to help more people to treat in time. At the same time, these data are also conducive to the development of more effective drugs and medical devices in the pharmaceutical industry.
Second, financial big data wealth management toolBig data is widely used in the financial industry. Typical cases include Citibank's use of IBM Watson computers to recommend products for wealth management customers; Bank of America uses customer click data sets to provide customers with distinctive services, such as competitive credit lines; China Merchants Bank Use customer action data such as credit card, deposit and withdrawal, electronic bank transfer, WeChat comment, etc., and send targeted advertising information to customers every week, which contains products and preferential information that customers may be interested in.
It can be seen that the application of big data in the financial industry can be summarized into the following five aspects: Precision Marketing: Recommend according to customer spending habits, geographical location, and consumption time.
Risk Management: Provide credit rating or financing support based on customer spending and cash flow, and implement credit card anti-fraud using customer social behavior records
Decision support: use the strategy tree technology to enter the mortgage management, use the data analysis report to implement the industrial credit risk control
Efficiency improvement: use the global data of the financial industry to understand the weak points of business operations, and use big data technology to speed up internal data processing
Product design: use big data computing technology to recommend products for wealth customers, use customer behavior data to design financial products that meet customer needs
Third, traffic big data smooth travelAt present, the big data application of transportation is mainly in two aspects. On one hand, big data sensor data can be used to understand vehicle traffic density, and reasonable road planning includes single-line circuit planning. On the other hand, you can use the big live data to realize the real-time signal dispatching and improve the existing line running capability. Scientific arrangement of signal lights is a complex system engineering, and a big data computing platform must be used to calculate a more reasonable solution. The scientific signal arrangement will increase the capacity of existing roads by about 30%. In the United States, the government added traffic lights based on traffic accident information on a certain section, reducing traffic accident rates by more than 50%. Airport flight departures and landings rely on big data to improve flight management efficiency. Airlines can use big data to increase attendance and reduce operating costs. Railways can effectively arrange passenger and freight trains with big data to improve efficiency and reduce costs.
Fourth, education big data to teach studentsIn the classroom, data can not only help improve education and teaching, but also make big data more useful in major education decision-making and education reform. The United States uses data to diagnose students at risk of dropping out of school, explore the relationship between educational spending and student achievement, and explore the relationship between absenteeism and achievement. For example, the data analysis of public primary and secondary schools in a certain state in the United States shows that in the Chinese language scores, the teacher college entrance examination scores and student achievement are significantly positively correlated. In other words, the teacher's college entrance examination scores have a very obvious relationship with the students' academic performances in the language classes they are currently teaching. The better the teacher's college entrance examination scores, the better the students' language scores. This relationship allows us to further explore the real reasons behind it. In fact, the high level of the college entrance examination is partly due to the fact that certain characteristics of the teacher are at work, and it is this characteristic that plays a vital role in teaching good students. The teacher's college entrance examination score can be used as an indicator for selecting teachers. If you have sufficient data, you can explore the relationship between more teacher characteristics and student achievement, thus providing a better reference for selecting teachers.
Big data can also help parents and teachers identify learning gaps and effective learning methods. For example, the McGraw-Hill Education Publishing Group in the United States has developed a predictive assessment tool to help students assess the gaps in their existing knowledge and the required level of test, and to point out where students need to improve. The assessment tool allows the teacher to track student learning and find out the learning characteristics and methods of the student. Some students are suitable for step-by-step, while others are more suitable for non-linear learning of graphical information and integrated information. These can be quickly identified through big data collection and analysis, thus providing a solid basis for education and teaching.
In China, especially in Beijing, Shanghai, Guangdong and other cities, big data has a lot of applications in the field of education, such as MOOC, online courses, flip classrooms, etc., which use a large number of big data tools.
Big data application field inventoryCase:
The earliest story about big data occurred in the second-largest supermarket in the United States, the Target Department Store. In order to attract pregnant women, a group with high gold content, Taggit asked the customer data analysis department to establish a model to confirm the pregnant women during the second trimester.
Through the modeling and analysis of customer consumption data, the customer data analysis department selects the consumption data of 25 typical commodities to construct the “pregnancy prediction indexâ€, which can predict the pregnancy of the customer within a small error range, and can provide pregnant women with preferential advertisements. Send it to the customer.
Wal-Mart, the global retail giant, also benefited from big data. In analyzing the consumer's shopping behavior, the company found that male customers often used a few bottles of beer to treat themselves when they purchased baby diapers, so they launched a promotional method that bundled beer and diapers. Today, the data analysis of this "beer + diaper" has become a classic case of big data technology applications.
China's big data market industry fit and application may analyze China's big data market concentration and maturity analysis
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