Big data was developed in order to analyze different data sets at a scale beyond the capacity of most data warehouses. However, big data analytics are only valuable when the big data use cases are well defined. If you can clearly identify what information you are looking for and the data sources are best suited to provide the proper insight, big data can be extremely valuable. And no group may have more need for more big data analytics than the public sector.
The concept of use cases has been around for more than two decades. A use case was originally created by software developers in order to determine the commercial practicality of a new application (i.e. Is there a real-world use that has value for the information and data flow?). With big data, the use cases usually extend across multiple applications as well as multiple data sets. Today, big data integrates data from the cloud, social media, and stored structure data in order to feed business use cases across multiple applications.
For government use cases, the same data sets are often applied across multiple applications concurrently. For example, one agency can be running a financial report in order to assess the efficiency of procurement, while another office uses the same data for budgeting. The use cases vary, but the data sets and applications will overlap.
Here are six use cases for the public sector that take advantage of disparate data sets and multiple applications:
1. Weather patterns: The National Weather service collects terabytes of data from sensors around the globe. The Joint Polar Satellite System (JPSS) monitors environmental conditions and the JPSS Common Ground System draws data from sensors and satellites. These data are openly available and can be used in different ways. Scientists can use these data in order to understand global warming, while government agencies may be looking for trends that help them with disaster preparedness for floods and hurricanes. The same data also can be used for long-term crop forecasts and to predict water demand. It’s all a matter of determining the necessary use case.
2. Social services: Publicly stored data are increasingly being used by service agencies in order to improve operating efficiencies and reduce fraud. For example, social services are finding new ways to apply public records such as tax data, welfare claims, and public assistance statistics in order to collect more revenue, reduce operating costs, and reduce claim adjudication times while ensuring citizens receive the benefits due them. For example, in North Carolina, IBM was able to uncover millions of dollars in Medicaid fraud by assimilating insurance data, reviewing healthcare records, and identifying records in order to look for patterns that indicated falsified claims.
3. Regulatory compliance: Government regulators can apply big data analytics in order to assess compliance. For example, the Environmental Protection Agency maintains a central database of 800,000 regulated facilities, which it calls ECHO. The ECHO database provides integrated compliance and enforcement data, including a history of compliance. The data can be used by different types of agencies in order to assess compliance.
4. Health services: Using data compiled from hospitals, accident reports, disease center reports, and social services case files, government agencies can assess healthcare needs. Geographic statistics can be mapped to socioeconomic data in order to determine where there might be greater need for medical or social services, ambulance and emergency services, and other types of health services. Cross-tabulating medical and environmental data also points to potential environmental hazards, medical trends, or health risks related to regional conditions. The Centers for Disease Control and Prevention also uses big data on a routine basis in order to predict flu outbreaks and track disease patterns.
5. Law enforcement: Analyzing crime trends and statistical data is having a huge impact on law enforcement. In Durham, North Carolina, for example, the police department was able to reduce crime in a two-square-mile area by 50 percent by assessing relationships between people, places, and other factors, making the department more efficient. Correlating census data and community records can make the police department more efficient. For example, cross-referencing zoning applications for liquor licenses, new construction sites that may be theft targets, and the opening of new retail centers makes it easier to assess manpower requirements and patrol routes.
6. The Department of Homeland Security: The federal government is using big data in order to combat terrorism. In 2012, the government launched two pilot programs, Neptune and Cerberus. Neptune is a data lake of unclassified information coded with data tags in order to control access and protect personal privacy. Cerberus is a data lake of classified information that has more stringent security. Taken together, the Department of Homeland Security is able to run analytics in order to identify threat patterns and predict potential sources of domestic terrorism.
Every government agency can get value from big data use cases. Whether the use cases relate to budgeting, financial planning, and resources allocation or are predictive analytics used in order to assess a potential threat or pandemic, the federal government, state, and local governments will continue to find new ways to benefit from big data.