BIG DATA REAL WORLD APPLICATIONS Big Data tracking

BIG DATA REAL WORLD APPLICATIONS

Big Data tracking the spread of disease

Source: https: //www. technologyreview. com/s/513721/big-data-from-cheap-phones/ This map, a product of cell-phone data analytics, shows the most important sources of malaria infections (darker shades)—taking into account the potential for further transmission caused by human travel—as well as the major destinations of people exposed to the disease (lighter shades). It can be used to determine where best to focus warnings and mosquito control techniques. The researchers at IBM, Johns Hopkins University, and the University of California at San Francisco are applying analytics from large data sets to see how changes in rainfall, temperature, and even soil acidity can dramatically affect the populations of wild animals and insects that carry the diseases. They’re also merging that information with other data, like airport and highway traffic, to further understand outbreaks. Source: http: //venturebeat. com/2013/09/29/ibm-uses-big-datato-predict-outbreaks-of-dengue-fever-and-malaria/ Source: http: //www. internewskenya. org/dataportal/data/27

Big Data Tracking crime

Source: http: //www. theguardian. com/cities/2014/jun/25/predictingcrime-lapd-los-angeles-police-data-analysis-algorithmminority-report The dashboard for New York Police Department's 'Domain Awareness System'. Photograph: Shannon Stapleton/Reuters An Arizona Department of Public Safety officer keeps an eye on his dashboard computer as it reads passing car licence plates. Photograph: Ross D Franklin/AP NYPD's Domain Awareness System uses hi-tech tools previously used in counterterrorism operations. Photograph: Shannon Stapleton/Reuters

Big Data Detecting fraud What: Identity fraud affected more than 12 million individual in 2012, according to a Javelin Strategy & Research Report, resulting in theft of nearly $21 billion. In the past year, we’ve seen an alarming rise in the number of retailers hacked, banks compromised and personal information stolen from popular websites. How: The technology can help organizations turn Big data and cloud into an investigative asset to help identify, disrupt and prevent fraud Source: http: //www. forbes. com/sites/ibm/2014/03/24/three-ways-to-fight-fraud-in-a-world-of-bigdata/#541 fa 7 bd 1 fd 8

Big Data Detecting fraud Who: By Judith Hurwitz, Alan Nugent, Fern Halper, and Marcia Kaufman. What: An insurance company need to invest in new analytical capabilities to help them to spot unknown and complex fraud activities. How: These analytical capabilities include incongruity detection, predictive modelling, unstructured data mining and social network analysis. Anomaly detection aims at discovering fraud by identifying those elements that vary from the norm. Predictive models use past fraud events to produce fraud propensity scores. Adjusters simply enter data and claims are automatically scored against the likelihood of them being fraudulent. These scores are then made available for review. Use of predictive modelling makes it possible to understand new fraud trends. Social network visualisation tools allow investigators to actually see network connections so they can uncover previously unknown relationships and conduct more effective and efficient investigations. Source: http: //www. reply. eu/en/topics/big-data-and-analytics/can-big-data-help-in-detecting-insurance-fraud

Google自動搜尋“流感” 所形成的地圖 Source：https: //ephinformatics. wordpress. com/category/mobile-health-mhealth/ Flu View 接收並處理來自”醫生、醫院 以及CDC實驗室”的大量數據 Source：http: //www. colorado. edu/news/features/seasonal-flu-levels-high-protect-yourself-andothers

Big Data Tracking crime 波士頓馬拉松爆炸案 Who：FBI和波士頓聖克魯斯警局。The Boston Marathon bombing was a terrorist attack, followed by subsequent related shootings, that occurred when two pressure cooker bombs exploded during the Boston Marathon on April 15, 2013. Where/What： 2013年 4月15日波士頓發生馬拉松爆炸案。FBI蒐集了1 TB的數據，因為資料 量太龐大，加上品質無法統一，所以無法分析。 How/Result：利用最新的警用Apache Hadoop大數據分析系統，推測犯罪地點和時間，並分 析歷史案件， 找出犯罪趨勢和犯罪模式，以及共同點和相關性，經由分析城市數據和社交網絡 數據，鎖定並逮捕嫌疑犯。 Source: http: //big 5. 3 mt. com. cn/g 2 b. aspx/ido. 3 mt. com. cn/Article/201304/show 3034413 c 7 p 1. html