data

The (SEC) protects investors, maintains fair and orderly markets, and facilitates capital formation. It is organized into five divisions, one of which is the Enforcement Division, where Ms. Walsh’s Center is housed. Ms. Walsh says , “the Enforcement Division’s mission is to pursue violations of securities laws and to try to get meaningful remedies, with significant deterrent value. So identify, pursue, and prevent violations of the securities laws.” The SEC has several analytics programs that are structured in a “hub and spoke system.” Ms.

The Recovery, Accountability, and Transparency Board (fondly known as RAT) was originally created by the American Recovery and Reinvestment Act of 2009 (ARRA) to provide transparency of ARRA-related funds and detect and prevent fraud, waste, and mismanagement of those funds. Later the RAT Board's authority was expanded to include oversight of all federal funding. Mr. Beltz has worked for the public sector for over three decades, mostly in law enforcement as a “detective and reconstructionist.” Mr.

In this final installment, we provide highlights from these federal leaders on the most important ingredients for a successful analytics program. (You can watch the video of the panel discussion and listen to each of the seven podcast interviews too.) The executives profiled complex programs in several agencies that have a wide impact on citizens, who benefit greatly from leveraging data as a strategic asset in program operations. What follows are some highlights from those executives on salient take-aways for government and stakeholder groups who are implementing key data-driven programs.

Big data should not be defined as “big” based on the size of the data alone. As defined by an important Commission on Big Data, big data is “a phenomenon that is a result of the rapid acceleration and exponential growth in the expanding volume of high velocity, complex and diverse types of data.” Organizations that do not necessarily have a large volume of data can benefit from a better understanding of the art of the possible with the new generation of analytic tools designed for big data.

This blog entry provides examples of how federal agencies and other levels of government are developing and applying big data strategies in the areas of fraud detection, financial market analysis, health related research, government oversight, education, criminology, environmental protection, and energy exploration.

Introduction

The "data" movement has many names. In Robert Behn's new book, The Performance Stat Potential, "PerformanceStat" refers to the many "Stat" programs initiated after the New York City Police Department successfully launched CompStat in the 1990s.Others use the term "analytics" to capture the use of data. While the trend toward increased use of data to measure performance has received much attention, the training that civil servants need to use data effectively has received less attention.

Across the government, agencies are working under leadership from the Office of Management and Budget (OMB) and the Department of Treasury to implement the Digital Accountability and Transparency Act (DATA Act).

Information technology has made possible the availability of real-time data and the tools to display that data, such as dash­boards, scorecards, and heat maps. This has boosted the use of data and evidence by government decision makers in meeting their agency and program missions. But what about the use of performance metrics by agency chief information officers themselves? Background. Typically, CIOs have a good inventory of metrics regarding the performance of their technical infrastructure, such as server down time.

Previous IBM Center posts about the Digital Accountability and Transparency Act (DATA Act) of 2014 by Dan Chenok (The DATA Act and Transparency: 4 Ways that Industry Will Benefit and The DATA Act Moves Forward) and John Kamensky (Here’s Why DATA Act Implementation May Be Successful) discuss various aspects about the law. This post provides a very brief background to the law and focuses on its implementation implications for Federal agencies.