Augmenting Data Warehouses with Big Data

Abstract

In the past decade, corporations are increasingly engaging in efforts whose aim is the analysis and wide-ranging use of big data. The majority of academic big data articles have been focused on methods, approaches, opportunities, and organizational impact of big data analytics. In this article, the focus is on the ability of big data (while acting as a direct source for impactful analysis) to also augment and enrich the analytical power of data warehouses.

Keywords:

• big data
• databases
• data warehouses
• MapReduce

Additional information

Notes on contributors

Nenad Jukić

Nenad Jukić is a professor of Information Systems at the Quinlan School of Business at Loyola University Chicago. He conducts research in various information management-related areas, including database modeling and management, data warehousing, business intelligence, data mining, business analytics, big data, e-business, and IT strategy. His work has been published in numerous information systems and computer science academic journals, conference publications, and books. In addition to his academic work, he provides expertise to database, data warehousing, business intelligence, and big data projects for corporations and organizations that vary from startups to Fortune 500 companies and U.S. government agencies.

Abhishek Sharma

Abhishek Sharma is a database/business intelligence consultant and the founder of an IT consulting company, Awishkar, Inc. He is also an adjunct professor of Information Systems at the Quinlan School of Business at Loyola University Chicago. He has worked at various information technology positions in fields such as information management, banking/quantitative finance and instrumentation, process control, and statistical analysis in manufacturing environment. Parallel with his consulting work and teaching, he conducts research in a variety of fields, including database modeling and management, data warehousing, business intelligence, data mining, very large databases (VLDBs)/big data, and IT strategy.

Svetlozar Nestorov

Svetlozar Nestorov is an assistant professor of Information Systems at the Quinlan School of Business at Loyola University Chicago. Previously he worked at the University of Chicago as a senior research associate at the Computation Institute, an assistant professor of computer science, and a leader of the data warehouse project at the Nielsen Data Center at the Kilts Center for Marketing at the Booth School of Business. He is a co-founder of Mobissimo, a venture-backed travel search engine that was chosen as one of the 50 coolest web sites by Time magazine in 2004. His research interests include data mining, high-performance computing, and web technologies.

Boris Jukić

Boris Jukić is a professor of Information Systems and the Director of The Masters of Data Analytics Program at Clarkson University School of Business. Previously he was also an associate dean of graduate programs at Clarkson University School of Business. He conducts active research in various information technology related areas including e-business, data warehousing, data analytics, computing resource pricing and management, process and applications modeling, as well as IT strategy. His work has been published in a number of management information systems and computer science academic journals, conference publications, and books.