1. Application case of big data: medical industry.

1)Seton Healthcare is the first customer to use IBM's latest Watson technology to analyze and predict healthcare content. This technology allows enterprises to find a large number of clinical medical information related to patients and better analyze patient information through big data processing.

In a hospital in Toronto, Canada, there are more than 3000 premature babies' data readings every second. Through the analysis of these data, hospitals can know in advance which premature babies have problems and take targeted measures to prevent premature babies from dying.

It makes it easier for more entrepreneurs to develop products, such as health applications that collect data through social networks. Maybe in the next few years, the data they collected will make your diagnosis more accurate. For example, instead of taking one tablet three times a day for adults, it will automatically remind you to take the medicine again when it is detected that the drugs in your blood have been metabolized.

2) Big data combined with Jobs' cancer treatment

Jobs was the first person in the world to sequence all his DNA and tumor DNA. He paid hundreds of thousands of dollars for this. What he got was not a sample, but a data document containing the whole gene. Doctors prescribed drugs on demand according to all genes, which finally helped Jobs to extend his life for several years.

2. One application case of big data: energy industry.

1) Smart Grid Now Europe has realized the terminal, which is the so-called smart meter. In Germany, in order to encourage the use of solar energy, solar energy will be installed at home. In addition to selling electricity to you, you can buy back the surplus electricity from your solar energy.

Data is collected every five minutes or ten minutes through the power grid, and the collected data can be used to predict customers' electricity consumption habits, so as to infer how much electricity the whole power grid needs in the next 2-3 months. With this forecast, you can buy a certain amount of electricity from power generation or power supply enterprises.

Because electricity is a bit like futures, it will be cheaper to buy it in advance and more expensive to buy it in stock. Through this forecast, the procurement cost can be reduced.

2) Danish Vestas Wind Systems uses big data, and the system relies on BigInsights software and IBM supercomputer to analyze where the turbine generator should be installed. In fact, this is a big challenge in the field of wind energy. In the process of wind farm operation for more than 20 years, accurate positioning can help the factory to maximize energy output.

In order to lock the ideal position, Vestas analyzes information from various aspects: wind and weather data, turbulence, topographic maps, and sensor data sent back by the company's more than 25,000 controlled turbine units all over the world. Such an information processing system has brought the company a unique competitive advantage and helped its customers get the maximum return on investment.

3. Application case of big data: communication industry-saving core customers through big data analysis.

Telekomunikacja Polska, a Polish telecom company under France Telecom -Orange Group, is the largest voice and broadband fixed-line provider in Poland, hoping to accurately predict and solve the customer churn problem in an effective way.

They decided to segment customers by building a "social map"-analyzing the data records of millions of phone calls of customers, paying special attention to "who called whom" and "call frequency". "Social Atlas" divides company users into several categories, such as: network type, bridge type, leading type and following type.

Such relational data can help telecom service providers gain insight into a series of problems, such as: who will have a greater impact on customers who may "give up" company services? How difficult is it to retain the most valuable customers? Using this method, the accuracy of the company's customer churn prediction model has increased by 47%.

4. Application case of big data: retail industry-big data helps retail enterprises to formulate promotion strategies.

Best Buy, a North American retailer, has a very active sales activity in North America, with more than 30,000 kinds of products, and the prices of products vary according to regions and market conditions. Due to the variety of products, the cost changes frequently, up to four times a year.

As a result, the number of price adjustments per year is as high as 6.5438+0.2 million. The biggest headache for executives is the pricing promotion strategy. The company has set up a team of 1 1 people, hoping to improve the accuracy and response speed of pricing by analyzing consumers' purchase records and related information.

The analysis of the pricing team revolves around three key dimensions:

1) Quantity: The team needs to analyze a huge amount of information. They collected the purchase records of tens of millions of consumers, analyzed them from different dimensions of customers, and understood the highest acceptance ability of customers for each product category, so as to set the best price for products.

2) Diversity: In addition to analyzing structured data such as purchase records, the team also uses social media to publish new unstructured data. Because consumers need to like or leave a message on the retailer's special page to get coupons, the team uses the emotion analysis formula to analyze the emotions of consumers on the special page, so as to judge whether they are satisfied with the company's promotion activities and fine-tune the promotion strategy.

3) Speed: In order to maximize the value, the team processes data in real time or near real time. According to the consumer's past record of purchasing grain, they successfully sent coupons to him/her at the supermarket grain counter, which brought convenience and surprise to customers.

Through this series of activities, the team improved the accuracy and response speed of pricing, and increased tens of millions of dollars in sales and profits for retailers.

5. Application Case of Big Data: Network Marketing Industry (SEM)

In the process of doing SEM, many enterprises have this feeling that they spend a lot of budget on SEM promotion every year, but because the input and output of keywords can't be visualized, they often spend a lot of money but can't see specific returns.

In such a fiercely competitive SEM market, enterprises need an efficient data analysis tool to help them optimize SEM promotion as much as possible, such as BDP, to help them save unnecessary expenses and improve their overall business performance.

Enterprises can get through various search engine marketing (SEM), online customer service systems and CRM systems with the help of network marketing integration solutions provided by data platforms. Marketing bidders can simply drag and drop reports, observe the input and output of each keyword, and analyze the transformation of each page, thus effectively reducing the delivery cost.

Through the live broadcast analysis data of BDP, we can quickly understand the delivery time, region and ranking of opponent keywords, and make visual analysis, monitor the delivery situation of ourselves and competitors in real time, understand the delivery strategy of opponents, support self-defined setting of the time point, monitoring frequency and time period of data update, and adjust the strategy in time. If you know what you know, you can win every battle.

6. Big data application case: e-commerce industry

Unexpectedly, the girl with the biggest breasts is Xinjiang. Taobao once showed that the bra size most bought by women in China is B cup. Cup B accounts for 4 1.45%, of which 75B is the best seller, followed by Cup A, accounting for 25.26%, and Cup C is only 8.96%.

Although Taobao data platform can't represent everything, considering the reality, it is universal, and we can only feel the general size of women in China. Among the bra colors, black is the best seller, and black is absolutely versatile, which is a must for every woman.

Judging from the ranking of provinces and cities, the girl with the biggest chest is Xinjiang. These data are a good reference for bra shops, and lay a data foundation for strategies such as inventory, pricing and style selection.

7. Application case of big data: entertainment industry.

Microsoft Big Data successfully predicted 2 1 Oscar. 20 13 David, an economist at Microsoft new york research institute? David Roth child successfully predicted 19 of 24 Oscar awards by using big data, which became a hot topic.

This year, Rothschild made persistent efforts and successfully predicted 265,438+0 of the 24 awards in the 86th Academy Awards Ceremony, continuing to show people the magical power of modern technology.

In general, the ultimate goal of big data is not only to change the competitive environment, but to completely reverse the entire competitive environment and bring new opportunities. Enterprises need to adapt to the times. Only when enterprises realize this, analyze products with appropriate data and use and manage data intelligently can they become the ultimate winners in the long-term competition.