Obtaining Value from Big Data for Service Systems: Big Data Technology (2)

Volume II of this series discusses the technology used to implement a big data analysis capability within a service-oriented organization. It discusses the technical architecture necessary to implement a big data analysis capability, some issues and challenges in big data analysis and utilization that an organization will face, and how to capture value from it.

It will help readers understand what technology is required for a basic capability and what the expected benefits are from establishing a big data capability within their organization.

Stephen H. Kaisler is consultant at SHK & Associates and adjunct professor of engineering at George Washington University. He has focused his efforts on Big Data and analytics, and enterprise architecture. He has published over 45 papers and 11 books on varied subjects such as Big Data and Historical Computing Machines.

Frank Armour is assistant professor in the Kogod School of Business at the American University and the faculty program director for the MS degree program in analytics. He has over 25 years of extensive experience in both the practical and academic aspects of applying advanced information technology.

J. Alberto Espinosa is professor and former chair of information technology in the Kogod School of Business at the American University. His research focuses on coordination in global technical projects across global boundaries, particularly distance and time. He published in various journals including IEEE Transactions on Software Engineering and IEEE Transactions on Engineering Management.