About the Book
Driving modern business intelligence (BI) architecture is essential for organizations to enhance operational efficiency and make data-driven decisions. As businesses accumulate large amounts of data from diverse sources, traditional BI tools struggle to deliver real-time insights and agility. Modern BI architecture leverages cloud-based platforms, data lakes, AI-driven analytics, and self-service capabilities to unify data access and accelerate decision-making. This empowers stakeholders across departments with actionable intelligence and streamline operations by identifying inefficiencies, predicting trends, and automating analysis. Further research into an adaptive BI framework may assist with future business strategies. Driving Modern Business Intelligence Architecture for Operational Efficiency explores the evolving landscape of data management within BI systems, addressing organizations' critical challenges in managing, processing, and utilizing vast amounts of data for strategic decision-making. It offers insights into cutting-edge tools, methodologies, and best practices for effective data management in BI environments. This book covers topics such as data governance, predictive security, and machine learning, and is a useful resource for computer engineers, business owners, economists, academicians, researchers, and data scientists.
About the Author :
Dr. Abdelraouf M. Ishtaiwi is a highly knowledge-achieving academic with over 22 years of experience in teaching and research in artificial intelligence (AI). He obtained a First-Class Honor and a Master's degree from a well-reputed university, Griffith University in Brisbane, in 2001 and 2007, respectively. He contribution to the AI field is enormous. 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. Mohammad Ali Al Khaldy is Assistant professor in Business Intelligence and Data Analytics at University of Petra. He earned his B.Sc. in Computer Science from Al-al-Bayt University in 2003, followed by an M.Sc. in Computer Science from Amman Arab University in 2005, then in 2017 he earned a Ph.D. from Hull University, U.K., in the field of AI and Data Science. His research interests include data analytics, machine learning, predictive analytics, NLP, and decision support systems. His work has been published in toptier journals. Dr Alkhaldy taught a variety of courses in artificial intelligence and business intelligence, including data mining, business analytics, computer programming, intelligent business systems, data visualization, and machine learning. He is a member of Jordan Computers Society, and Arab Robotics and AI Association. He also serves on the Editorial Board of International Journal of Engineering and Artificial Intelligence (IJEA) and is an occasional reviewer for several other academic conferences and journals such as the International Conference on Information Technology (ICIT). Mohammad Alauthman is an Associate Professor in the Information Security Department at the Faculty of Information Technology, University of Petra, Amman, Jordan. His research interests include network security, intrusion detection systems, and applying AI techniques—such as machine learning and deep learning—for botnet and DDoS detection, spam filtering, IoT security, and network traffic classification. He earned his Ph.D. in Computer Science from Northumbria University, UK, in 2016. Dr. Alauthman has received multiple research grants supporting advanced AI-driven intrusion detection systems and international collaboration. He is also actively involved in Erasmus+ projects, including BITTCOIN-JO (technology transfer), RL4Eng (remote engineering labs), Pro-GREEN LABs (green competences in education), and COMMO (mobility and cooperation across Mediterranean and Balkan institutions), contributing to innovation, sustainability, and cross-border academic development.
