Integration Challenges for Analytics, Business Intelligence, and Data Mining, 1 volume - PDF & ePUB Download

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Download Integration Challenges for Analytics, Business Intelligence, and Data Mining, 1 volume ebook
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  • eBook:
    Integration Challenges for Analytics, Business Intelligence, and Data Mining, 1 volume
  • Author:
    Ana Azevedo, Manuel Filipe Santos
  • Edition:
    -
  • Categories:
  • Data:
    November 24, 2020
  • ISBN:
    1799857816
  • ISBN-13:
    9781799857815
  • Language:
    English
  • Pages:
    250 pages
  • Format:
    PDF

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Description of Integration Challenges for Analytics, Business Intelligence, and Data Mining, 1 volume ebook

Download Integration Challenges for Analytics, Business Intelligence, and Data Mining, 1 volume, pdf, epub free. As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration.
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Content

Section 1 - Background and Literature Review
Chapter 1. Data Mining and Business Intelligence: A Bibliometric Analysis
Chapter 2. Integration of Data Mining and Business Intelligence in Big Data Analytics: A Research Agenda on Scholarly Publications
Chapter 3. From Business Intelligence to Big dаta: The Power of Analytics

Section 2 - Big Data Issues
Chapter 4. Big Data Quality for Data Mining in Business Intelligence Applications: Current State and Research Directions
Chapter 5. Enterprise Data Lake Management in Business Intelligence and Analytics: Challenges and Research Gaps in Analytics Practices and Integration 

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): An Approach to Detect Illicit Transaction in the Bitcoin Network

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

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