Driving Modern Business Intelligence Architecture for Operational Efficiency (Paperback)

"This book assists both the theoretical and practical understanding of current Business Intelligence (BI) architectures"-- Provided by publisher.

Dr. Abdelraouf M. Ishtaiwi is an Associate Professor of Artificial Intelligence and Data Science at the University of Petra, Jordan, with over 22 years of academic and research experience in AI. He earned his Master’s and Ph.D. degrees in Artificial Intelligence from Griffith University, Australia, where he focused on heuristic optimization techniques for satisfiability problems. His research expertise spans machine learning, hybrid metaheuristic optimization, associative classification, and AI applications in cybersecurity and emerging technologies like the metaverse. Dr. Ishtaiwi has developed innovative AI algorithms, such as ACRIPPER and hybrid crayfish-DE models, and contributed significantly to areas like phishing detection, blockchain security, and smart IoT defense. As a former Head of the Department of Data Science and AI at Petra University, he led academic reforms and accreditation initiatives. He has also been a visiting scholar at Griffith University and Universitat Pompeu Fabra, reflecting his international academic engagement.

Ahmad Al-Qerem graduated in applied mathematics and M.Sc. in Computer Science at the Jordan University of Science and Technology and Jordan University in 1997 and 2002, respectively. After that, he was appointed as full-time lecturer at the Zarqa University. He was a visiting professor at Princess Sumaya University for Technology (PSUT). He obtained a Ph.D. from Loughborough University, UK. His research interests are in performance and analytical modeling, mobile computing environments, protocol engineering, communication networks, transition to IPv6, machine learning and transaction processing. He has published several papers in various areas of computer science. Currently, he has a full academic post as a full professor at computer science department at Zarqa University-Jordan.

Dr. Mohammad Alkhaldy is an accomplished Assistant Professor and researcher specializing in Artificial Intelligence, Data Science, and Business Intelligence, currently serving at the University of Petra in Jordan. With a PhD from the University of Hull (UK), and a strong academic foundation in computer science, he has held various academic and leadership roles across institutions in Jordan, Saudi Arabia, and the UK. Dr. Alkhaldy is recognized for his contributions to cutting-edge research in AI, cybersecurity, blockchain, and digital finance, with numerous peer-reviewed publications and conference presentations. He is also an active member of academic committees and professional societies, playing a vital role in curriculum development, student mentorship, and institutional research strategy. His work reflects a passion for innovation, interdisciplinary collaboration, and empowering students through research and experiential learning.

Dr. Mohammad Alauthman (contacted at email: mohammad.alauthman@uop.edu.jo) He is an associate professor and chair of the Information Security Department at the Faculty of Information Technology, University of Petra inAmman, Jordan. His research interests lie in network security, intrusion detection systems,and the application of artificial intelligence techniques like machine learning and deep learning for botnet detection, DDoS detection, spam email filtering, IoT security, and network traffic classification. He obtained his Ph.D. in computer science with a focus on network security from Northumbria University in the UK in 2016. Alauthman has been awarded several research grants in the field of network security, supporting his work on advanced intrusion detection systems and the development of AI-driven security solutions. These grants have enabled him to conduct extensive research and collaborate with international experts. His funded projects have focused on enhancing the resilience of network infrastructures against emerging threats and improving the accuracy of threat detection mechanisms.