The primary role of government is to protect the safety and well-being of its citizens.
Since 2000, statistics reveal that the amount of information being captured by the federal government is increasing exponentially and, since 2013, big data capture is expected to double as each year passes.
Analysis of such data is nothing new. As far back as 1967, the then-Office of Education and Office of Economic Development launched a program that spent more than $600 million in an attempt to correlate low household income with academic achievement. And that was just the beginning.
The information that can now be obtained from government databases is enormous; but with government budgets under continual strain, Sean Brophy of Tableau Software explains that the pressure is on for “agencies to find and use higher-value, more flexible tools, especially ones that help them see their data faster and clearer.”
Not surprisingly, that has encouraged a new generation of Big Data enterprises; from BI suites from the likes of Japersoft and Pentaho to dedicated flexible big data analysis databases such as those offered by players like SQream Technologies, technological solutions abound to help best draw rapid insights from large volumes of data.
But how exactly can governments turn this data analysis into concrete federal programming, designed to protect the lives of citizens? Here are a few areas which can benefit enormously from accurate analysis of big data.
The management of transportation suffers from any number of variable factors, including weather conditions and driver ability, but big data analysis can ensure that both federal and local governments are able to plan ahead. For instance, based on analysis of traffic movements, greater numbers of traffic officers can be allocated to specific locations, and better traffic calming measures can be installed at accident hotspots.
SPATIOWL by Fujitsu is one of the most developed services that deal with data coming from public transportations, vehicles, and pedestrians’ smartphones in urban areas through sensors. It analyzes across various data layers, and provides insights from the data to identify relevant actions in the user context.
2. Emergency Preparedness
Every population faces risks from one sort of natural disaster or another, from earthquakes to tornadoes to unexpectedly large snowfalls. Big data analysis is already providing new abilities to improve disaster prediction and management.
In recent years, huge amounts of data have been stored across most every scientific discipline. Whether we’re talking about high-resolution satellite imagery or seismic data, high-speed data analytics makes it possible to recognize patterns which may make it possible to anticipate natural disasters, and anticipate vulnerabilities in a city’s infrastructure.
But, even with better predictions, disaster management will remain critical. During and following an event, real-time analysis of vast networks such as wireless sensors and cameras, transportation grids, and even social media can alleviate suffering by improving the delivery of emergency services.
3. Climate Research
According to its website, the organization “has access to over 20 years of atmospheric data gathered during normal operations and field campaigns” and will “explore more than 350 instruments that collect data at locales spanning diverse climate regimes.”
Although unstated, the goals of ARM are to use the data gathered to further human understanding of our climate, and ideally ensure that we are better placed to deal with the increased threats from global warming and other climate change issues.
Overall, despite the sometimes confusing technological language involved and the sheer volume of data in question, the benefits of big data to the government’s mission to protect its citizens are clear.
With that in mind, in 2012, the Obama administration announced a $200 million investment in big data research-and-development programs, which spanned agencies including defense, intelligence, and cybersecurity.
As the results of these programs roll in, there will no doubt be an increased demand for such analysis as time goes on.