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TechAmerica: Demystifying Big Data Report

The report provides the government with a comprehensive roadmap to using Big Data to better serve the American people. While Big Data is transformative, the journey towards becoming Big Data "capable" will be iterative and cyclical, versus revolutionary. Successful initiatives tend to follow three "Patterns of Deployment".

TechAmerica: Demystifying Big Data Report Data in the world is doubling every 18 months. Across government everyone is talking about the concept of Big Data, and how this new technology will transform the way Washington does business. Looking past the excitement, many questions remained unanswered- until now. The TechAmerica Foundation's Big Data Commission has worked diligently to put together the most comprehensive report on Big Data of its kind. What is Big Data, really? How is it defined? What capabilities are required to succeed? How do you use Big Data to make intelligent decisions? How will agencies effectively govern and secure huge volumes of information, while protecting privacy and civil liberties? And perhaps most importantly, what value will it really deliver to the US Government and the citizenry we serve?

The Big Data Commission released its findings October 3rd to help answer these questions and many more.

The report, Demystifying Big Data: A Practical Guide To Transforming The Business of Government, provides the government's senior policy and decision makers with a comprehensive roadmap to using Big Data to better serve the American people.

Big Data Case Studies

Selected quotes:

  • Hidden in the immense volume, variety and velocity of data that is produced today is new information, facts, relationships, indicators and pointers, that either could not be practically discovered in the past, or simply did not exist before. This new information, effectively captured, managed, and analyzed, has the power to enhance profoundly the effectiveness of government.
  • the path to harnessing the value of Big Data is now affordable.
Leveraging Big Data - Early Experiences and Lessons Learned
  • While Big Data is transformative, the journey towards becoming Big Data "capable" will be iterative and cyclical, versus revolutionary.
  • Successful Big Data initiatives seem to start not with a discussion about technology, but rather with a burning business or mission requirement that government leaders are unable to address with traditional approaches.
  • Successful Big Data initiatives commonly start with a specific and narrowly defined business or mission requirement, versus a plan to deploy a new and universal technical platform to support perceived future requirements. This implies not a "build it and they will come" transformative undertaking, but rather a "fit for purpose" approach.
  • Successful initiatives seek to address the initial set of use cases by augmenting current IT investments, but do so with an eye to leveraging these investments for inevitable expansion to support far wider use cases in subsequent phases of deployment.
  • Once an initial set of business requirements have been identified and defined, the leaders of successful initiatives then assess the technical requirements, identify gaps in their current capabilities, and then plan the investments to close those gaps.
  • Successful initiatives tend to follow three "Patterns of Deployment" underpinned by the selection of one Big Data "entry point" that corresponds to one of the key characteristics of Big Data - volume, variety and velocity.
... Since 2000, the amount of information the federal government captures has increased exponentially. In 2009, the U.S. Government produced 848 petabytes of data1 and U.S. healthcare data alone reached 150 exabytes2 . Five exabytes (10^18 gigabytes) of data would contain all words ever spoken by human beings on earth. At this rate, Big Data for U.S. healthcare will soon reach zetabyte (10^21 gigabytes) scale and soon yottabytes (10^24 gigabytes).

Potential applications described in the report include

Healthcare Quality and Efficiency
The ability to continuously improve quality and efficiency in the delivery of healthcare while reducing costs remains an elusive goal for care providers and payers, but also represents a significant opportunity to improve the lives of everyday Americans. As of 2010, national health expenditures represent 17.9% of gross domestic product, up from 13.8% in 2000. Coupled with this rise in expenditures, certain chronic diseases, such as diabetes, are increasing in prevalence and consuming a greater percentage of healthcare resources. The management of these diseases and other health-related services profoundly affects our nation's well-being.
Big Data can help. The increased use of electronic health records (EHRs) coupled with new analytics tools presents an opportunity to mine information for the most effective outcomes across large populations. Using carefully de-identified information, researchers can look for statistically valid trends and provide assessments based upon true quality of care.

Healthcare Early Detection
Big Data in health care may involve using sensors in the hospital or home to provide continuous monitoring of key biochemical markers, performing real time analysis on the data as it streams from individual highrisk patients to a HIPAA-compliant analysis system. The analysis system can alert specific individuals and their chosen health care provider if the analysis detects a health anomaly, requiring a visit to their provider or a "911" event about to happen. This has the potential to extend and improve the quality of millions of citizens' lives.

Through improved information and autonomous features, Big Data has the potential to transform transportation in many ways. The nemesis of many American drivers, traffic jams waste energy, contribute to global warming and cost individuals time and money. Distributed sensors on handheld devices, on vehicles, and on roads can provide real-time traffic information that is analyzed and shared. This information, coupled with more autonomous features in cars can allow drivers to operate more safely and with less disruption to traffic flow. This new type of traffic ecosystem, with increasingly connected "intelligent cars," has the potential to transform how we use our roadways.

Big Data can have a profound impact on American education and our competitiveness in the global economy. For example, through in-depth tracking and analysis of on-line student learning activities - with fine grained analysis down to the level of mouse clicks - researchers can ascertain how students learn and the approaches that can be used to improve learning. This analysis can be done across thousands of students rather than through small isolated studies.6 Courses and teaching approaches, online and traditional, can be modified to reflect the information gleaned from the large scale analysis.

Fraud Detection - Healthcare Benefits Services
Big Data can transform improper payment detection and fundamentally change the risk and return perceptions of individuals that currently submit improper, erroneous or fraudulent claims. For example, a significant challenge confronting the Centers for Medicare and Medicaid Services (CMS) is managing improper payments under the Medicare Fee-For-Service Program (FFS). The FFS distributes billions of dollars in estimated improper payments. Currently, contractors and employees identify improper payments by selecting a small sample of claims, requesting medical documentation from the provider who submitted the claims, and manually reviewing the claims against the medical documentation to verify the providers' compliance with Medicare's policies.

Additional promising applications for Big Data include

  • Cyber Security
  • Fraud Detection - Tax Collection
  • Weather
  • New Ways of Combining Information - Helping the Unemployed Find Work
Government agencies should think about Big Data not as an IT solution to solve reporting and analytical information challenges but rather as a strategic asset that can be used to achieve better mission outcomes, and conceptualized in the strategic planning, enterprise architecture, and human capital of the agency. Through this lens, government agencies should create an ownership structure for the data, treating it like any other asset - one that is valued and secured. Ultimately, agencies should strive to address the following two questions - "How will the business of government change to leverage Big Data?" and "How will legacy business models and systems be disrupted?"

Here is the full report:


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