The significance of big data can be observed in any decision-making process as it is often used for forecasting and predictive analytics. Additionally, big data can be used to build a holistic view of an enterprise through a collection and analysis of large data sets retrospectively. As the data deluge deepens, new methods for analyzing, comprehending, and making use of big data become necessary.
Enterprise Big Data Engineering, Analytics, and Management presents novel methodologies and practical approaches to engineering, managing, and analyzing large-scale data sets with a focus on enterprise applications and implementation. Featuring essential big data concepts including data mining, artificial intelligence, and information extraction, this publication provides a platform for retargeting the current research available in the field. Data analysts, IT professionals, researchers, and graduate-level students will find the timely research presented in this publication essential to furthering their knowledge in the field.
Edited by:
Martin Atzmueller, Samia Oussena, Thomas Roth-Berghofer Imprint: Information Science Reference Country of Publication: United States Dimensions:
Height: 229mm,
Width: 152mm,
Spine: 18mm
Weight: 1.006kg ISBN:9781522502937 ISBN 10: 1522502939 Series:Advances in Business Information Systems and Analytics Pages: 300 Publication Date:01 June 2016 Audience:
Professional and scholarly
,
Undergraduate
Format:Hardback Publisher's Status: Active
Martin Atzmueller, University of Kassel, Germany. Samia Oussena, University of West London, UK. Thomas Roth-Berghofer, University of West London, UK.