This handbook collects the most up-to-date scholarship, knowledge, and new developments of big data and data analytics by bringing together many strands of contextual and disciplinary research. In recent times, while there has been considerable research in exploring the role of big data, data analytics, and textual analytics in accounting, and auditing, we still lack evidence on what kinds of best practices academics, practitioners, and organizations can implement and use. To achieve this aim, the handbook focuses on both conventional and contemporary issues facing by academics, practitioners, and organizations particularly when technology and business environments are changing faster than ever. All the chapters in this handbook provide both retrospective and contemporary views and commentaries by leading and knowledgeable scholars in the field, who offer unique insights on the changing role of accounting and auditing in today’s data and analytics driven environment. Aimed at academics, practitioners, students, and consultants in the areas of accounting, auditing, and other business disciplines, the handbook provides high-level insight into the design, implementation, and working of big data and data analytics practices for all types of organizations worldwide. The leading scholars in the field provide critical evaluations and guidance on big data and data analytics by illustrating issues related to various sectors such as public, private, not-for-profit, and social enterprises. The handbook’s content will be highly desirable and accessible to accounting and non-accounting audiences across the globe.

TOPICS IN THE BOOK Predicting Purchasing Probability of E-Commerce Customers Mobile Money and SME Growth: A Zambian Perspective Enhancing Financial Stability in Ghana’s Universal Banking Sector: A Governance Perspective and Practical Insights Impact of Innovation on Adoption of Block Chain Technology with the Moderating Role of Digital Marketing The Mediating Effect of Employee Outcomes on the Relationship between Green Human Resource Management Practices and Firm Performance

TOPICS IN THE BOOK Decoding Lambda API Architectures: Analyzing Monolithic Lambda Functions versus Fine-Grained Single-Purpose Functions Driver Safety High Cabin and Chassis Design in Diesel Forklifts Enhanced Network Reliability Following Emergency (E911) Calls Artificial Intelligence and Energy Efficiency of 5G Radio Access Network Demystifying AI: Navigating the Balance between Precision and Comprehensibility with Explainable Artificial Intelligence

TOPICS IN THE BOOK Effect of Tangibility on Customer Satisfaction among Micro Finance Banks Customers in Kenya Effect of Information Technology Infrastructure on Customer Relationship Management in Private Hospitals in Kenya Challanges Facing the Emerging Economy during Covid-19: The Case of Jordan Effect of Product Innovation on Performance of Printing SMEs in Kampala Central District Challenges Facing Insurance Brokers in Kenya

The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.

Discusses the main issues, challenges, opportunities, and trends related to this explosive range of new developments and applications, in constant evolution, and impacting every organization and society as a whole. This two volume handbook supports post-graduate students, teachers, and researchers, as well as IT professionals and managers.

"This book is a comprehensive reference on concepts, algorithms, theories, applications, software, and visualization of data mining, text mining, Web mining and computing/supercomputing, covering state-of-the-art of the theory and applications of mining"--

In today’s data-driven business landscape, the ability to extract insights and communicate complex information effectively is paramount. Data visualization has emerged as a powerful tool for businesses to make informed decisions, uncover patterns, and present findings in a compelling manner. From executives seeking strategic insights to analysts delving into operational data, the demand for intuitive and informative visualizations spans across all levels of an organization. Data Visualization Tools for Business Applications comprehensively equips professionals with the knowledge and skills necessary to leverage data visualization tools effectively. Through a blend of theory and hands-on case studies, this book explores a wide range of data visualization tools, techniques, and methodologies. Covering topics such as business analytics, cyber security, and financial reporting, this book is an essential resource for business executives and leaders, marketing professionals, data scientists, entrepreneurs, academicians, educators, students, decision-makers and stakeholders, and more.