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Advances in business information systems and analytics (ABISA) book series.
Utilizing big data paradigms for business intelligence / Jérôme Darmont, Sabine Loudcher, [editors]. — 1 online resource (xxi, 313 pages) : illustrations. — (Advances in business information systems and alanlytics (ABISA) book series). — <URL:http://elib.fa.ru/ebsco/1851356.pdf>.

Record create date: 7/19/2018

Subject: Business intelligence — Data processing.; Big data.; Big data.; BUSINESS & ECONOMICS / Industrial Management; BUSINESS & ECONOMICS / Management; BUSINESS & ECONOMICS / Management Science; BUSINESS & ECONOMICS / Organizational Behavior

Collections: EBSCO

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"Because efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations, data analysis is an important part of modern business administration. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Utilizing Big Data Paradigms for Business Intelligence is a pivotal reference source that provides vital research on how to address the challenges of data extraction in business intelligence using the five 'Vs' of big data: velocity, volume, value, variety, and veracity. This book is ideally designed for business analysts, investors, corporate managers, entrepreneurs, and researchers in the fields of computer science, data science, and business intelligence."--.

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Table of Contents

  • Title Page
  • Copyright Page
  • Book Series
  • Editorial Advisory Board
  • Table of Contents
  • Detailed Table of Contents
  • Foreword
  • Foreword
  • Preface
  • Acknowledgment
  • Chapter 1: Applications of Artificial Intelligence in the Realm of Business Intelligence
  • Chapter 2: A Big Data Platform for Enhancing Life Imaging Activities
  • Chapter 3: A Survey of Parallel Indexing Techniques for Large-Scale Moving Object Databases
  • Chapter 4: Privacy and Security in Data-Driven Urban Mobility
  • Chapter 5: C-Idea
  • Chapter 6: Large Multivariate Time Series Forecasting
  • Chapter 7: Exploring Multiple Dynamic Social Networks in Computer-Mediated Communications
  • Chapter 8: Analysis of Operation Performance of Blast Furnace With Machine Learning Methods
  • Compilation of References
  • About the Contributors
  • Index

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