insideBIGDATA Guide to Data Analytics in Government

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The insideBIGDATA Guide to Data Analytics in Government provides an in-depth overview of the use of data analytics technology in the public sector. Focus is given to how data analytics is being used in the government setting with a number of high-profile use case examples, how the Internet-of-Things is taking a firm hold in helping government agencies collect and find insights in a broadening number of data sources, how  government sponsored healthcare and life sciences are expanding, as well as how cybersecurity and data analytics are helping to secure government  applications.

Data Analytics for Government: An Overview

Data is a critical asset for government agencies. All levels of government collect an increasing amount of data every day. As these agencies strive for a meaningful digital transformation, it’s important not only to  collect and store large data sets, but also to use that data when making mission-critical decisions. This  growing use of so-called “big data” builds mounting pressure on government to use data analytics to turn all  data into actionable information. Efficient use of data is the missing link between good governance and  capacity building, where data insights can be gleaned to improve service delivery. This technology guide will help government thought leaders in how best to use data analytics to manage and derive value from an  increased dependence on data. A number of prevailing concerns include:

  • How are these data is being converted into beneficial insights?
  • What happens when you have too much data?
  • How do you make sense of it when the data volume is on a continued upward trajectory?
  • How can you keep up with the volume of data?

Government also must look at the type and source of data being collected, stored, analyzed, and consumed,  i.e. structured versus unstructured data. Structured data is the data that has been modeled and normalized to fit into a relational model, such as  traditional row/column databases. Unstructured data is information that either doesn’t have a predefined data model or doesn’t fit well into relational  tables—examples are social media, plain text, log files, video, audio, and network-type data sets. Big data for data analytics is a compilation  of both structured and unstructured data. Recognizing the importance of data analytics, the U.S. Government now has a new official role of Chief Data Scientist. Pledging to put all government records into the public domain, it is clear that U.S. Government officials are far from ignorant of the importance of the data revolution.

Certain uses are already being found for data in government-related fields, such as healthcare, cybersecurity, and education, which can potentially have huge positive impact. These include:

  • The CIA helped to fund Palantir Technologies, which produces analytical software designed to stamp out  terrorism and crack down on cyber fraud by identifying transactions that follow patterns commonly displayed during fraudulent activity.
  • American law enforcement agencies (at federal, state and county levels) have access to sophisticated ALPR (automated license plate recognition) software that alerts them to anyone in the vicinity with an outstanding warrant. And predictive technologies are used by several police  departments to predict flashpoints where crimes may occur, as well as link particular crimes to particular repeat offenders.
  • The U.S. Department of Transportation also uses license plate recognition, as well as cameras, to monitor the flow of people as they travel by  plane, train and automobile, generating insights as to where infrastructure investment is necessary, as well as predictions about how we are  likely to change the way we travel in the future.
  • In education settings around the globe, thanks to the huge increase in the amount of learning activity carried out online (both in traditional school environments and through distance learning), massive amounts of data about the way we study and learn is becoming available.
  • The U.S. Department of Agriculture supports the agricultural economy through research and development of new big data technologies. One  recent breakthrough is increasing the yield of dairy herds by identifying bulls most likely to breed high-yielding cows based on genetic records.
  • Government agencies involved in healthcare, such as the Centers for Disease Control (CDC), track the spread of illness using social media, while  the National Institutes of Health (NIH) launched an initiative called Big Data to Knowledge (BD2K) in 2012 to encourage innovation based on  data-derived insights. One project funded by the government even aims to spot the early signs of suicidal thinking among war veterans, based on their social media behavior.

Privacy concerns are often seen as the biggest challenge presented by the rise of data and analytics, and the U.S. Government has identified several  potential areas that could be infringed on through inappropriate use of data, including rights to secrecy of personal information and rights to remain  anonymous while exercising free speech. Indeed, big data use in government certainly presents big challenges—officials and politicians have a fine  line to tread if they do not want to come across as attempting to implement a real-life version of Orwell’s Big Brother.

Emerging Technologies for the Public Sector

A new report by Accenture, Emerging Technologies in Public Service, examines the adoption of emerging technologies across government agencies,  with the most interaction with citizens or the greatest responsibility for citizen-facing services: health and social services, policing and justice,  revenue, border services, pension and social security, and administration. A few of the findings of this nine country survey of nearly 800 IT leaders  include:

  • More than two-thirds of government agencies are evaluating the potential of emerging technologies including big data, but only onefourth have moved beyond the pilot stage
  • Those that have embraced technologies like IoT and machine learning all report that the most common new IT used is advanced analytics with predictive modeling
  • Nearly half of those agencies say their primary objective in harnessing the power of advanced analytics is to improve and support employee work
  • More than three-fourths indicate that implementing machine learning methods are either underway or complete

Preparing for Big Data

What can government agencies do to prepare for and embrace big data and data analytics? First of all, government agencies should try to get ahead of their data deluge. Strategy, planning and governance are critical to this process. Second, they must develop and review the life cycle for data for their agencies. The life cycle can be categorized into the following phases:

When the big data life cycle is well understood, government thought leaders need to plan and identify the following:

  • Find technology enablers – seek out and evaluate new infrastructure and new software applications, and institute pilot programs/proof-of-concept projects
  • Adopt an ecosystem approach – big data analytics is an evolving space and there will be new technology options to review and select new solutions
  • Adopt a use case-based approach – data’s value depends on the insight of the domain; look for use case-specific projects, e.g. network-centric data analytics or cybersecurity insights
  • Invest in data-centric skill sets – insights in large data sets tend to be as good as the domain knowledge of the data, so skills for data scientists  and data analysts need to be developed and nurtured

In setting the stage for successful big data deployments, government agencies also need a good sense for data lineage—source of data, change log of  data, and trustworthiness of data to limit any sort of garbage-in-garbage out (GIGO) possibilities.

Innovative Use Case Examples

There are a number of high-profile big data use case examples in a government setting:

  • Pakistan’s National Database & Registration Authority (NADRA), one of the world’s largest multi-biometric citizen databases, serves as an  example of harnessing the power of government data. NADRA is an independent and autonomous agency under Ministry of Interior and  Narcotics Control, Government of Pakistan that regulates government databases and statistically manages the sensitive registration database of  all the national citizens of Pakistan.
  • The Japanese government plans to develop a system to help disaster victims by utilizing big data gathered from sources such as internet postings, and global positioning system (GPS) data from smartphones and car navigation devices. The system will enable administrative authorities to immediately ascertain the movements of victims just after a disaster occurs. The government will gather and analyze information,  including that on isolated local communities and overcrowded shelters, to make the initial response after a disaster, such as search and rescue  operations and the delivery of goods, more efficient.
  • From Washington, DC to cities, states, and countries all around the world, “open government” is revolutionizing the way citizens interact with  government leaders. It connects like-minded citizens with each other, with government agencies, and with many other types of organizations. To support open government initiatives and uphold the values of transparency, participation, and collaboration in the US, federal agencies now make their data open. This means making large data stores publicly accessible in a format that can be shared. Open data from the government  gives citizens the information they need to hold government leaders accountable. Open data fosters collaboration between government leaders  and citizens, and encourages cooperation internally among government entities. The results can be tremendously better decisions that have the potential to drastically change lives. One fertile source of open data from the Federal Government, as well as APIs from a variety of federal  agencies and other resources, is
  • A new UKAuthority report “Digitising Policing,” indicates that advances of IT solutions like data analytics are changing the world and policing is changing with it. It is clear that police forces are rapidly adopting big data technology. It promises significant improvements in efficiency—the  management of evidence can be improved, and the provision of more information—can support better decision making at strategic and  operational level, and among officers on the beat. There are also opportunities to use data analytics to better understand factors influencing the  demands on the police.
  • Traffic and congestion control in London has been using automatic plate number recognition along with multiple video cameras across the city  for years meaning that during the planning and delivery of Olympics 2012, Transport for London (TfL) employed a number of big data tools to  make sure that during the Olympic games public (and private transport) kept people moving quickly and safely to and from the games and  generally around London
    for their normal business.

Over the next few weeks we will explore these data analytics in government topics:

If you prefer, the complete insideBIGDATA Guide to Data Analytics in Government is available for download in PDF from the insideBIGDATA White Paper Library, courtesy of Dell EMC.

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