Submitted by cmasingo on Fri, 12/22/2017 - 11:58
This blog was written by our guest blogger: Chris Trainor
Submitted by cmasingo on Fri, 12/22/2017 - 10:48
Major Jim Markham is an operations research / systems analyst in the Army. He is currently serving as a Research Fellow in the Training with Industry program, during which he works with IBM for one year before returning to the Army, including time with the Center for The Business of Government. His fellowship is intended to help him learn how industry applies big data and analytics to healthcare challenges in order to take this knowledge back to the Army.
Submitted by rgordon on Tue, 10/04/2016 - 09:44
Professor Ho conducted a survey and phone interviews with city officials responsible for Big Data initiatives. Based on his research, the report presents a framework for Big Data initiatives which consists of two major cycles: the data cycle and the decision-making cycle. Each cycle is described in the report.
Submitted by rgordon on Thu, 04/09/2015 - 12:09
Over the last decade, a major trend in government management has involved the increased use of data by government executives. The “data” movement has many names. In Robert Behn’new book, The PerformanceStat 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.
Submitted by rgordon on Wed, 01/29/2014 - 15:17
Professor Desouza provides a clear and useful introduction to the concept of big data, which is receiving increasing attention as a term but also lacks a commonly understood definition. In describing big data, Desouza writes, “Big data is an evolving concept that refers to the growth of data and how it is used to optimize business processes, create customer value, and mitigate risks.” Desouza also describes the differences in the use of big data in the public and private sectors.
Submitted by rgordon on Mon, 11/11/2013 - 15:04
Today’s senior managers are tempted to begin analytics programs before determining the mission-essential questions they are seeking data to answer. Older data-based analytics efforts often grew out of the discoveries of line employees who made connections and saw patterns in data after receiving new software or hardware that helped them make sense of what they were studying.