Eight typical large data application cases

1. Macy's real-time pricing mechanism. According to demand and inventory, the company based on the SAS system for up to 73 million kinds of goods for real-time price adjustment.

2. TIPP24 AG's betting and forecasting platform for the European gaming industry. The company uses Kxen software to analyze billions of of transactions and customer characteristics, and then through the predictive model for specific users to carry out dynamic marketing activities. The move reduced the 90% forecast model build time. SAP is trying to buy kxen.

3. Wal-Mart search. The retail oligopoly has designed the latest search engine http://www.aliyun.com/zixun/aggregation/16887.html ">polaris" for its website Walmart.com, using semantic data for textual analysis, Machine learning and synonym mining. According to Wal-Mart, the use of semantic search technology has increased the completion rate of online shopping by 10% to 15%. "For Wal-Mart, that means billions of dollars." "Laney said.

4. Video analysis of fast food industry. The company uses video to analyze the length of waiting queues, and then automatically changes what the electronic menu displays. If the queue is longer, displays food that can be supplied quickly, and if the queue is shorter, displays those foods that have a higher profit but are prepared for a relatively long time.

5. Morton Steak Shop Brand awareness. Morton began his social show when a customer made a joke by tweeting to the Chicago steak chain to take it to Newark Airport in New York, where he would arrive after a day of work. First of all, the analysis of Twitter data, found that the customer is our regular customers, is also a popular Twitter. According to the customer's previous orders, speculated on the flight, and sent a waiter in a tuxedo to provide dinner for the client.

6. PredPol Inc. PredPol, working with police in Los Angeles and Santa Cruz and a group of researchers, predicts the probability of a crime based on variants of the Earthquake prediction algorithm and crime data, which can be as accurate as 500 square feet. In Los Angeles, where the algorithm was used, the distribution of theft and violent crime fell by 33% and 21%.

7. Tesco PLC (special easy to purchase) and operation efficiency. The supermarket chain collects data from 7 million refrigerators in its data warehouse. Through the analysis of these data, more comprehensive monitoring and proactive maintenance to reduce overall energy consumption.

8. Anglo Express (American Express, AMEX) and business intelligence. In the past, Amex can only realize the hindsight report and lag prediction. "Traditional bi has not been able to meet the needs of business development. "Laney thinks. As a result, Amex began building models that were truly capable of predicting loyalty, based on historical transaction data, with 115 variables for analysis and prediction. The company says it has been able to identify 24% of its customers who will be lost in the next four months.