Todays’ public-sector organizations are functioning amid an information age leading to an enormous amount of data. The need to access, understand, and act decisively on data gathered from multiple sources has become increasingly important for the provision of efficient public services.
The public sector is becoming progressively aware of the potential value to be gained from big data. For example, in March of 2012, the Obama Administration put forward the Big Data Research and Development Initiative to understand the technology needed to manipulate massive volumes of information.
Here are some of the big data use cases in public sector:
Health Services:
Data gathered from hospitals, health care entities, accident reports, disease center reports, and social services case files can be used to improve medical services. The Centers for Disease Control and Prevention apply big data on a routine basis to predict flu outbreaks and track disease patterns.
Social Services:
Publicly stored data such as the IRS data, welfare claims, and public assistance statistics have been increasingly used by social services to improve operations, reduce fraud, collect more revenue, reduce operating costs, and claim adjudication times.
Sentiment Analysis:
Data gathered from both traditional and social media sources (websites, blogs, twitter feeds, etc.) can help policymakers prioritize services and be aware of citizens interests and opinions.
Cyber security:
Analyzing a vast amount of data collected from government computer networks provide critical services and the ability to detect and counter malicious attacks.
DataKare Solutions has expertise in developing big data applications on public sector data. DataKare uses big data framework to gather and ingest data from public sector end-point and develop a foundation for public and private agencies giving them an ability to perform advanced analytics, data mining and develop predictive modeling. We leverage cloud and big data technologies to build robust and scalable databases on both cloud and on-premise environments.
