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Integration challenges for analytics, business intelligence, and data mining / Ana Azevedo and Manuel Filipe Santos, editors. — 1 online resource — <URL:http://elib.fa.ru/ebsco/2690793.pdf>.

Record create date: 5/21/2020

Subject: Business enterprises — Data processing.; Business intelligence.; Data mining.; Business enterprises — Data processing; Business intelligence; Data mining

Collections: EBSCO

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Group: Anonymous

Network: Internet

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"This book provides insights concerning the integration of data mining in business intelligence and analytics systems, increasing the understanding of using data mining in the context of business intelligence and analytics"--.

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Table of Contents

  • Cover
  • Title Page
  • Copyright Page
  • Book Series
  • Table of Contents
  • Detailed Table of Contents
  • Preface
  • Acknowledgment
  • Section 1: Background and Literature Review
    • Chapter 1: Data Mining and Business Intelligence
    • Chapter 2: Integration of Data Mining and Business Intelligence in Big Data Analytics
    • Chapter 3: From Business Intelligence to Big Data
  • Section 2: Big Data Issues
    • Chapter 4: Big Data Quality for Data Mining in Business Intelligence Applications
    • Chapter 5: Enterprise Data Lake Management in Business Intelligence and Analytics
  • Section 3: Modelling Issues
    • Chapter 6: Modelling in Support of Decision Making in Business Intelligence
    • Chapter 7: Causal Feature Selection
    • Chapter 8: K-Nearest Neighbors Algorithm (KNN)
  • Section 4: Software and Security
    • Chapter 9: A Framework to Evaluate Big Data Fabric Tools
    • Chapter 10: A Novel Approach Using Steganography and Cryptography in Business Intelligence
  • Compilation of References
  • About the Contributors
  • Index

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