This week’s list of data news highlights covers September 14-20 and includes articles on CERN’s new data-related initiatives and the increasing use of analytics in the legal profession.
The Securities and Exchange Commission (SEC) is using predictive analytics to evaluate risk among the industries it regulates. The Division of Economic and Risk Analysis processes real-time data in the form of financial statements to pinpoint which firms might be most at risk of default. The system finds red flags for investigators, who then can evaluate whether an investigation is warranted.
CERN, the European Organization for Nuclear Research, has to handle astronomical amounts of data for its fundamental physics research, and two new initiatives will help it keep all that information in check. A new 50,000-core Budapest datacenter and a data analysis software redesign will work together to help the organization cut costs and boost efficiency. CERN has also pushed for cloud-based data storage and analysis to speed up some of its science.
Analytics is on the rise in law firms, and St. Louis-based Bryan Cave LLP is at the forefront. The firm uses a mixture of traditional business analytics, text mining and semantic analysis to help optimize a variety of processes and help the firm be more profitable. The analytics team helps track and predict how the firm’s lawyers spend their time, determine when rates should be changed, and guide language use in client-facing documents.
Taiwan took a big step toward transparency with the establishment of an open data alliance, consisting of more than 200 individuals and groups from the private, public and academic sectors. The alliance will promote public data releases and provide feedback and suggestions to the government on future offerings. The Taiwanese government, which began releasing some of its data in open, machine-readable formats earlier this year, hopes these releases will bolster the country’s software and application programming industries.
The private sector demand for interdisciplinary data scientists is largely unmet, and universities around the country are scrambling to create programs to help educate a new crop of these workers. The programs include George Washington University’s master’s degree in business analytics, as well as the University of Maryland’s master’s degree in marketing analytics. Some, as in George Washington University’s case, have been supported by IBM, which has partnered with over 1,000 colleges worldwide to provide software and curriculum for data science programs.
Spanish researchers have developed an infrared camera system that can remotely measure vehicle emissions on a high-capacity road. These cameras can help researchers identify the vehicles with the worst emissions and could one day help law enforcement direct notices or fines to particularly egregious offenders. It could also help city planners, who could use the system to measure the impact of changes in speed limits, lane number, traffic light synchronization, and other experimental variables.
A new wellness tracker for infants monitors vital signs and lets parents check up on the health of their children without visiting a pediatrician. The Owlet Baby Monitor, created by a team at Brigham Young University, tracks heart rate, oxygen levels, temperature and sleep habits. An accompanying app can be installed on parents’ phones for comprehensive remote monitoring.
Security analyst Bruce Schneier’s recent critique of the U.S. government’s inability to predict and respond to Syria’s use of chemical weapons carries implications for predictive analytics in other contexts. More information is not necessarily better, and unless it is clear that a computational method can outperform a seasoned veteran’s estimate, heavy investment in predictive analytics may not be worth the cost. Using such analytics to measure machine behavior, rather than human behavior, may be more successful.
Google announced this week that it has invested in Calico, a life science startup that will tackle aging and associated diseases. Although life science may seem outside Google’s typical purview, the large-scale data processing challenges inherent in much of biomedical research may present an opportunity for Google to offer its expertise.
A British think tank, the Royal United Services Institute, is urging the UK military to develop its “big data” analytics capabilities. The country’s Ministry of Defense has been somewhat slower in deploying large-scale data analysis technologies than other branches of government, despite its formidable data collection capabilities. The think tank warns that a lack of initiative in this area on the UK military’s part could hamper operations, as well as collaboration with more data-savvy allies, such as the United States and Australia.