Big data refers to gathering, analyzing, and storing data sets that are too large and complex for traditional data processing and data management applications. As data proliferates in volume, velocity, variety, and veracity, citizens press their governments to deliver experiences similar to those they experience as consumers in the private sector. Managing the influx of big data in government is a major challenge as public servants struggle to adapt to a digital culture or are held back by budgetary issues, security issues, or a lack of resources.
What is big data in government?
Big data in government is the influx of data from disparate sources such as traffic and CCTV cameras, sensors, satellites, body cameras, calls, emails, direct messages, and social media, as well as the use of emerging technology from private IT spaces and academia to better govern and manage the public sector.
Today, there is a strong focus on improving data storage and analytics processes. From simply codifying old paper records in databases, to building more predictive systems that address the implications of gathered information, big data empowers governments to serve constituents more effectively.
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Six ways government uses big data.
Governments and the public sector comprise a variety of use cases, and big data applications are gaining relevance as these agencies adapt to a changing global ecosystem.
Organizations ranging from individual cities, to states, to agencies whose responsibilities span geopolitical boundaries are finding a need for improved storage, integration, accessibility, and analytical power as the sheer volume and complexity of data continues to skyrocket.
1. Open data initiatives.
The idea of open data has grown increasingly popular in the last decade. This trend affects governing bodies in two major ways:
- Private companies and independent groups now provide more public, easily-accessible data than ever before.
- Open data initiatives in government are expanding to encourage public participation and transparency.
Data, once hidden within private silos, can be found across the Internet, available to mine for valuable information. Meanwhile, government initiatives to release data into the commons create new levels of accountability. Members of the public who view detailed reports on how they are governed in turn engage better with institutions, provide new feedback, and become more involved in the decision-making which concerns them.
It is a two-way street, and openness leads to more openness. For example, in the U.S., individual states have offered up their data in order to support a Health and Human Services (HHS) initiative to improve drug monitoring nationwide. Many states benefited from the resulting analyses and insights and were able to significantly reduce drug overdoses.
As agencies consume and generate more data, a commitment to sharing will bring many benefits. The most innovative and effective big data projects in government today involve this back-and-forth, working within the data ecosystem and with relevant populations directly.
2. Defense, enforcement, and consumer protection.
Whether protecting consumers from fraud, anticipating global political shifts, or shielding against the physical dangers of the modern world, the onus is on government to defend groups and individuals from varied threats. By necessity, these protections have expanded in new directions, such as cybersecurity, curtailing the spread of misinformation and fraud, or cutting-edge robotics hardware and artificial intelligence.
For example, the Department of Defense (DOD) makes yearly multibillion dollar investments in AI systems and underlying cloud and data platforms. These programs focus on the reduction of cybercrime and digital threats to constituents, as well as the proactive detection and prevention of higher-stakes crises like acts of terror.
Beyond these big data applications, the race toward military superiority continues worldwide and requires increasingly powerful AI in domestic, protective systems, and abroad in technologies used for strategic intervention.
The great resources available to groups like the DOD allow them to stay on top of developments in the fields of analytics, machine learning, and AI. These agencies often are at the bleeding edge, whether employing advanced anomaly detection, natural language processing (NLP), and profiling techniques on bad actors and insider threats, or enhancing military applications with improvements in security and automation.
3. Public safety.
Police now wear body cameras, cars have dash cameras, and video is recorded continuously by both individuals and city infrastructure itself. Meanwhile, police departments receive more 9-1-1 calls than ever as cities grow denser.
Law enforcement and justice departments now can acquire warrants for information from giants like Google, Apple, or Facebook including location data from GPS, WiFi connections, and cell towers. This data has helped to conclude many recent investigations, and even address cold cases.
All of this new data, and the big data techniques being used to analyze it, help law enforcement guard against internal threats, and prevent or resolve the harm which individuals can inflict upon each other.
4. Transportation and city infrastructure.
Analytics also helps cities and states gather more accurate statistics on vehicle safety, road accidents, and driving behavior. This, in turn, enables governments to build better roads, improve routes and traffic, and launch more effective programs for protecting drivers, cyclists, and pedestrians.
Using toll data, traffic analysis, and mobile bus or train trackers, agencies adjust and improve public transportation to better suit the changing needs of local commuters, all while generating new revenue.
Meanwhile, smart cities initiatives are underway to provide entire regions with a better, data-driven nervous system. These involve the integration of many existing sensors, new data gathering, and the development of analytics, all of which will contribute to more adapted, efficient city infrastructure. This will mean smarter investments in construction and repairs, reduced resource usage and waste, and a more streamlined management system for officials and city employees.
5. Public health.
From managing dangerous misinformation to acting on the persistent problem of drug abuse, many new initiatives are in place concerning the public health information accessible to government agencies.
For example, the Health and Human Services (HHS) FY19 budget included a $10 million allocation for solving the opioid crisis, including the deployment of analytics solutions ranging from predictive modeling, to pattern discovery, to data visualization. These kinds of investments can help government understand epidemics far better, flag high-risk areas or cases, and start addressing health issues among populations before these health issues get out of hand.
The National Science Foundation (NSF) and the National Institutes of Health (NIH) also are highly invested in big data research and engineering. Many science agencies use large data sets to extract detailed physical insights from chemistry, biology, epidemiology and human behavior. These insights help doctors and scientists develop new techniques in the business of healing, new cures for diseases, and public health programs which benefit entire populations.
6. Environment, energy, and utilities.
Agencies have access to data from weather, air quality, water and ground sensors, as well as consumer consumption and payment records from power use to waste management and recycling.
Some environmental agencies, such as the California Natural Resources Agency (CNRA), have embraced the role of big data in better managing humanity’s interactions with nature and use of resources. The CNRA developed a data lake containing information on a variety of resources, which other agencies and the public can access and view.
The U.S. Geological Survey (USGS) launched several programs aimed at improving our understanding of climate change and the dispersal and extinction of important animal species. Programs like these use big data to help predict and prepare for earthquakes, anticipate ecological changes, and more effectively plan emergency response during natural disasters.
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The challenges of big data in government.
Though many agencies are becoming more data-driven, more yet are struggling to adapt, and some remain unaware of the importance of big data. For all the opportunities afforded by new data sources and more accessible technology, many hurdles still need to be crossed.
Undermanned IT teams and outdated systems.
Government has been around for far longer — and has responsibilities to constituents far greater — than any other institution. This duty-bound and time-tested nature also results in a certain amount of rigidity when it comes to adopting new policies, ideas, or technology.
IT departments in public agencies and governing bodies often are purely functional and lacking the resources seen in their private analogues. In the last few decades, most agencies updated their hardware or software only when the need became dire.
Many departments still rely on paper records and information encoded in myriad deprecated storage media. Even those who have transitioned to databases and data warehouses to manage their data still deal with physical records, whether in interacting with other agencies or due to inherent requirements (for example, voting systems with paper ballots).
Processing these diverse types of information slows the modernization of IT in the public sector, and introduces unique difficulties to implementation going forward.
Data quality and data integration.
Beyond the realization that many governmental and public systems need to evolve and move to the cloud, there is the question of proper integration and ensuring data quality. Teams should be fully prepared for a collaborative, careful, and informed process if trying to build a robust data pipeline.
Some agencies have thousands of applications that need to move to the cloud, but most of the existing software has evolved independently with disparate dependencies and rare compatibility. This means that the challenge of integration remains in many agencies, even those committed to modernizing and adopting big data technologies.
Budgets in governments and the public sector are regulated more rigidly than in business, making it difficult for officials and leaders to justify investments in IT or data infrastructure.
Many powerful platforms, services, products, and applications exist in the cloud, often with changing features and evolving (sometimes prohibitive) prices. There is a danger that agencies abandon data migration efforts when faced with these kinds of incompatibility to their typical financing.
Security and system vulnerabilities.
As volume, sources, and public interest in data grows, state and local governments are discovering they face increased risk of security issues. It is important to manage this heightened danger of leaks and information breaches that are damaging and wide-ranging.
Many individual users of governmental data systems say they can access information which they should not. Meanwhile, bad actors continue to gain expertise in the infiltration of computer systems, far faster than the small or non-extant cybersecurity teams of the public sector.
There is some hope, however, as new data and governance regulations gain traction and are implemented. For example, the General Data Protection Regulation (GDPR) in the European Union serves to protect individuals and their data, while making it easier for groups to adopt and adhere to these safeguards and rules.
Politics and culture.
Unfortunately, there also is a built-in culture challenge to implementing big data in government. Many of the individuals who might lead a modernization effort, or who control policies which make or break these efforts, are not acquainted with the challenges and opportunities of big data.
Officials in government often have exaggerated expectations regarding the capabilities of their IT departments. A lack of data awareness means they also may be unaware of existing capabilities which they aren’t using effectively.
Traditional approaches to governance make it much harder for agencies to collaborate or share knowledge effectively. Governmental departments remain extremely siloed, introducing additional challenges to data integration.
Another problem has come to light: corporations using big data effectively also compete directly with institutions that are not prepared or flexible enough to adapt (for example, rideshare services disrupt the use of public transportation and create new policy issues for cities).
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The public sector, big data, and cloud solutions.
Cloud infrastructure is growing at a compound rate of almost 30 percent in the public sector. Clearly, governments and agencies are following the distributed storage and computation trends from business and the private sector.
As these groups migrate data into the cloud and begin to build critical business intelligence and analytics on top, they will need a variety of modern solutions. In most cases, government applications will require powerful data integration, careful modeling and deployment of data lakes and cloud data warehouses. Hybrid cloud solutions also are necessary to connect traditional, on-premises databases to SaaS and PaaS applications.
For city, state, and local governments, hybrid or cloud solutions come with many benefits.
- Cost savings come when moving farther from in-house IT and on-premise hardware, as operational costs decline.
- Scalability increases in distributed applications, allowing greater adaptability to the changing needs of constituents.
- Improved speed will allow agencies to respond to issues and requests ever closer to real time.
- Cloud storage and services bring greater resilience and redundancy, securing critical data.
- Best practices for data management will also ensure that data quality, accessibility, and governance requirements are met.
Data is everywhere, and it is growing.
More people means more data, and more sources of information means exponentially more data. Governments must be data-driven to manage these new, immense inputs, and to satisfy constituents who evolved along with this global data revolution.
Governments no longer can get by sifting through paperwork, jumping hurdles just to transmit and receive urgent information, or hoping that data will be robust and secure without established and modern processes. In view of the massive data influx from millions of devices, agency systems, cameras, and more, the public sector must become data-driven.
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