Overview

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.

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9781799857822

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Professor Ana Azevedo holds a PhD in Information Systems and Technologies from the University of Minho, Portugal. She is an integrated member of the CEOS.PP research center and was member of its Directive Board. She is a senior lecture in the Information Systems Department, School of Business, Polytechnic of Porto, Portugal teaching courses on Analytics, Business Intelligence, Research Methodologies, and E-Commerce, and is member of the Scientific Board of the Master in E-Business. She has published articles in both journals and conference proceedings, and she collaborates in the editorial teams of several journals. She has served as chair for several conferences as well as special sessions in conferences. She has been guest editor for a number of books and special journals issues. She regularly participates as a member of the program committee for conferences and is a regular reviewer for journals and conferences.

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