The key to the application of big data, and also its necessary conditions, lies in the integration of "IT" and "business", of course, the meaning of business here can be very broad, from the operation of a retail store to the operation of a city. The following is about all walks of life, different organizations in the application of big data cases, hereby affirming that the following cases are from the network, this article is only for reference, and on this basis for a simple sorting and classification.
Big Data Application Case: Healthcare Industry
SetonHealthcare is the first customer to adopt IBM's latest Watson technology healthcare content analytics prediction. The technology allows organizations to find a large amount of patient-related clinical medical information to better analyze patient information through big data processing.
At a hospital in Toronto, Canada, more than 3,000 data readings are taken every second for premature babies. By analyzing this data, the hospital is able to know in advance which premature babies are having problems and take targeted measures to prevent premature babies from dying.
Big Data Application Case: Energy Industry
Smart grids have now reached the end of the line in Europe, with so-called smart meters. In Germany, in order to encourage the use of solar energy, will be installed in the home solar energy, in addition to selling electricity to you, when your solar energy has excess electricity can also be bought back. Data is collected through the grid every five or ten minutes, and this data collected can be used to predict the customer's electricity habits, etc., so that it can be deduced how much electricity the entire grid will probably need in the next two to three months time. With this prediction, a certain amount of electricity can be purchased from the power generation or supply company. Because electricity is a bit like futures, if you buy in advance will be cheaper, buy spot is more expensive. With this forecast, the purchase cost can be reduced.
Vestas Wind Systems, which relies on BigInsights software and IBM supercomputers, then analyzes the weather data to figure out the best places to install wind turbines and entire wind farms. Using big data, analysis that used to take weeks now takes less than an hour to complete.
Big Data Use Case: Communications Industry
XOCommunications reduced customer churn by nearly half by using IBMSPSS predictive analytics software. xo can now predict customer behavior, spot behavioral trends, and identify flawed segments to help the company take timely action to retain customers. In addition, IBM's new Netezza Network Analytics Accelerator will help communications companies make more scientific and rational decisions by providing a single scalable platform with end-to-end network, service, and customer analytics views.
Telecommunications companies, through tens of millions of customer data, can analyze a wide range of user behaviors and trends and sell them to companies that need them, which is the new data economy.
China Mobile uses big data analytics to provide targeted monitoring, early warning, and tracking of the full range of businesses operated by the company. The system automatically captures market changes at the first time, and then pushes them to the designated person in charge in the quickest way, so that he is informed of the market situation in the shortest time.
NTTdocomo combines cell phone location information with information on the Internet to provide customers with information on nearby restaurants and a last train information service when it is close to the last train time.
Big Data Application Case: Retail
"One of our clients, a leading specialty fashion retailer, serves its customers through local department stores, the Internet and its mail-order catalog business. The company wanted to offer a differentiated service to their customers, and how to position the company to differentiate themselves, they gained a deeper understanding of the marketing model for cosmetics by gathering social information from Twitter and Facebook, and subsequently realized that they had to retain two types of valuable customers: high consumers and high influencers. The hope was that by receiving free makeup services, users would engage in word-of-mouth promotion, a perfect combination of transactional and interactive data that provided a solution to the business challenge." Informatica's technology helped the retailer enrich customer master data with data from social platforms to make his business services more targeted.
The retailer also monitors customers' in-store walks and interactions with merchandise. They combine this data with transaction history to analyze it and give advice on what to sell, how to position items, and when to adjust selling prices, which has helped one leading retailer reduce inventory by 17% while increasing the proportion of high-margin private label items while maintaining market share.