The document discusses how governments and organizations are increasingly collecting and analyzing large amounts of data. It provides examples of how the US government collects millions of documents annually and is moving from paper to electronic records. It also gives examples of how transportation agencies and healthcare systems are using analytics to improve operations and decision making. The document argues that advances in data analytics can help governments and businesses gain insights, increase efficiencies, and detect issues like fraud.

1. Contributors feed
The alchemy of big data in government
By Chuck Brooks, contributor, andDavid Logsdon
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For nine luminous centuries, the Library of Alexandria was a grand beacon of innovation. The
ancient Egyptians understood the power of collected and analyzed data (containing over
700,000 manuscripts), which helped elevate Egypt to a world power. The Library of Alexandria
stood as antiquity's shining light, playing a central role in the development of medical thought
and practice.

2. The potential for today's Alexandria can be found in the expansive amount of readily publically
available data. The possibilities of this data leading a digital transformation are endless.
According to Eric Schmidt, CEO of Google, we produce more data every other day than we did
from the inception of early civilization until the year 2003, combined. Therefore, the organizing,
managing and analyzing of data are all more important than ever.
Data are everywhere, flowing from the sensor networks that surround us and at the root of our
transactional activities. What, why and how we make choices in our lives are reflected in, and
can be discerned through, the collection, organization and taxonomy of data.
The U.S. government maintains one of largest repository of documents in the world. Millions of
supporting documents are compiled and stored every year by a multitude of government
agencies, which have a responsibility to preserve, secure and retrieve vital information when
needed. While paper documents are still very much routine for government operations, the
goal has been to increasingly move from paper to electronic images.
The means and processes of transactions can vary within financial systems or on the global
digital marketplace. The information we can gain from analyzing these transactions can be very
important to any business. When the extracted data are systematically combined with multi-
layered analytics, a forensic and predictive meaning is created that can be transformed into
actionable insights in reporting systems.
Data analytics can be of great value to both the public and private sectors. In government,
transactional activities can be found throughout all agencies. The processing and disbursement
of payments occurs every day to millions of beneficiaries through Social Security, veterans
benefits, workman's compensation, federal retirement, utilities and insurance needs resulting
from natural disasters.
In 2012, the Obama administration announced the Big Data Research and Development
Initiative. Six federal departments and agencies were selected and provided with more than
$200 million in new commitments that "together, promise to greatly improve the tools and
techniques needed to access, organize, and glean discoveries from huge volumes of digital
data." The purpose of the initiative was to improve government's ability to extract insights from
various data streams and make better decisions in support of national security objectives,
scientific discovery or to help drive economic growth. Two years later, the government has
embraced data analytics as an integral aspect of operational function in the federal space.

3. The Big Data Research and Development Initiative does formulate a working paradigm for a
better qualification of risk management. In various government programs, including financial
services, transportation, human resources, Medicaid, government subsidies and expense
management, the resulting analytics can be used, to detect fraud, waste and abuse by
examining habits and trends derived from transactions.
Another industry that is effectively using and analyzing data to make informed, educated
decisions is transportation. Government agencies are using data to gain information on
scheduling mass transit arrival times to provide updates to citizens and data gained from
cameras, sensors and geo-tracking with analytics can "see" whether a particular spot is
occupied or not, and transmit that information to a device within the car, such as GPS or the
driver's mobile phone, to actually guide the driver to the closest available space. Predictive
analytics can also be used to enable transit operators and managers to make decisions rapidly
for near real-time adjustments of vehicles or services. For example, analytics can be used to
plan roadways based on projected population growth, anticipate the impact of temporarily
closing a road, build a new station or change a route. Agencies can also anticipate rider reaction
to a fare increase to determine potential attrition, or to identify what would happen if a specific
route was cancelled or adjusted by 15 minutes.
Additionally, data can provide informed insights in the healthcare system. By analyzing
information gained from data, statistics can be used to curtail unnecessary spending and
enhance visibility by measuring outcomes and value. This insight helps track quality of care and
serves as care management software to make sense of, and direct patient care from, all
perspectives.
This type of analysis on the agency level can save taxpayers money, therefore strengthening
public trust and increasing efficiency by providing timely and needed aid. Advances in
automation and transactional data modeling can also directly impact customer service,
especially in contact centers, by allowing for more rapid and accurate agency decision-making.
In the critical and specialized area of government response to disasters, cultivating data from
spending patterns on products, medicines and services during a hurricane can provide real-
time, vital information to local law enforcement, Federal Emergency Management Agency
(FEMA) and the Coast Guard regarding logistics gaps by location. Lessons learned and insights
gained through data retrieval can lead to better protocols, preparation and the ability to predict
trends in the face of future catastrophic events.

4. In the private sector, information mined from transactions can be used for demographical
analysis and to calculate consumer purchasing habits, credit risks and predict consumer trends.
Financial institutions can use predictive algorithms to create the best financial management
options from market and transactional data. Combined with social media analytics, optimizing
economic forecasting has become a new data analytic art.
In both the commercial and government arenas, the field of data analytics is relatively new and
has room for growth. The world's data production has been estimated to double every two
years and the ability to store, prioritize, analyze and share data is a key to research and
development (R&D) investment.
A major focus of R&D investment is how to take high-speed data streams of both 'structured
data" (residing in a predetermined field) and "unstructured data" (not organized in a pre-
defined manner). Eighty percent of data is unstructured. That means specialized optic
technologies, software algorithms and innovative processes are necessary to de-clutter data
and allow for distillation and sophisticated assessment. The goal of this type of technology is to
develop a deployable, fully automated, real-time, secure way to collect and analyze complex
streams of data.
The future of applied data analytics looms bright and the data sets of disparate information are
seemingly endless. Technological R&D advances such as "machine thinking," which will allow
connected devices on the "Internet of Things" to talk to and learn from each other, will
contribute immensely to the use of data analytics. These smart devices will also recognize who
we are from biometric authentications, as well as augmenting our expertise. Data analytics is an
exciting new frontier providing insights into the future conduct of our world. It is a science
deeply rooted in our daily communications and transactions.
The splendid ambition that was the Library of Alexandria can be captured again. The alchemy of
data to knowledge to learning can, and will, digitally transform our nation.
Logsdon is the senior director of public advocacy for CompTIA. In this role, he runs the
association's New and Emerging Technologies Committee (focused on the policy surrounding
social, mobile, big data/data analytics, cloud, Internet of Things and smart cities). He was also
the staff lead for CompTIA's federally focused technology convergence commission, which
examined the impact on the public sector when social, mobile, analytics and cloud converge.
Follow him on Twitter @DJLSmartData. Brooks serves as the vice president for government
relations and marketing for Sutherland Government Solutions. He is also vice chairman of the

5. CompTIA New and Emerging Technologies Committee. Brooks served at the Department of
Homeland Security as the first director of legislative affairs for the Science and Technology
Directorate. He also spent six years on Capitol Hill as a senior advisor to the late Sen. Arlen
Specter (Pa.). Follow him on Twitter @ChuckDBrooks and on LinkedIn.
Tags: Big data, Data analysis