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Integration Challenges for Analytics, Business Intelligence, and Data Mining

Integration Challenges for Analytics, Business Intelligence, and Data Mining

Ana Azevedo, Manuel Filipe Santos
Copyright: © 2021 |Pages: 250
ISBN13: 9781799857815|ISBN10: 1799857816|ISBN13 Softcover: 9781799857822|EISBN13: 9781799857839
DOI: 10.4018/978-1-7998-5781-5
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MLA

Azevedo, Ana, and Manuel Filipe Santos, editors. Integration Challenges for Analytics, Business Intelligence, and Data Mining. IGI Global, 2021. https://doi.org/10.4018/978-1-7998-5781-5

APA

Azevedo, A. & Santos, M. F. (Eds.). (2021). Integration Challenges for Analytics, Business Intelligence, and Data Mining. IGI Global. https://doi.org/10.4018/978-1-7998-5781-5

Chicago

Azevedo, Ana, and Manuel Filipe Santos, eds. Integration Challenges for Analytics, Business Intelligence, and Data Mining. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-5781-5

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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.

Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students.

Table of Contents

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Front Materials
Title Page
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Copyright Page
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Advances in Business Information Systems and Analytics (ABISA) Book Series
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Preface
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Acknowledgment
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Chapters
Chapter 1
Background and Literature Review
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Chapter 2
Big Data Issues  (pages 63-63)
Big Data Issues
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Chapter 3
Modelling Issues  (pages 114-114)
Modelling Issues
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Chapter 4
Software and Security  (pages 179-179)
Software and Security
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Back Materials
Compilation of References
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About the Contributors
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Index
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