Data-Driven Business Intelligence Systems for Socio-Technical Organizations

Offers an academic exploration of the tools, strategies, and methodologies that propel enterprises toward data-driven decision-making excellence. From user behaviour to social interactions, technological systems to environmental factors, this work sheds light on the multifaceted sources of information that inform organisational strategies.

---

The convergence of modern technology and social dynamics have shaped the very fabric of today's organizations, making the role of Business Intelligence (BI) profoundly significant. Data-Driven Business Intelligence Systems for Socio-Technical Organizations delves into the heart of this transformative realm, offering an academic exploration of the tools, strategies, and methodologies that propel enterprises toward data-driven decision-making excellence. Socio-technical organizations, with their intricate interplay between human and technological components, require a unique approach to BI. This book embarks on a comprehensive journey, revealing how BI tools empower these entities to decipher the complexities of their data landscape. From user behavior to social interactions, technological systems to environmental factors, this work sheds light on the multifaceted sources of information that inform organizational strategies. Decision-makers within socio-technical organizations leverage BI insights to discern patterns, spot trends, and uncover correlations that influence operations and the intricate social dynamics within their entities. Research covering real-time monitoring and predictive analytics equips these organizations to respond swiftly to demands and anticipate future trends, harnessing the full potential of data. Nevertheless, this book goes beyond theoretical discourse; it is a pragmatic guide. With a multidisciplinary approach that integrates artificial intelligence, data analytics, and behavioral analysis, readers will be introduced to the methodologies, tools, and life-cycles underpinning effective decision-making within socio-technical organizations. The pages within explore AI techniques, recommender systems, machine learning, and deep learning applications in BI, offering a blueprint for leveraging cutting-edge technology. Moreover, this work addresses the critical issue of behavioral analytics, a cornerstone in understanding customer satisfaction, opinion mining, sentiment analysis, and product reviews. Readers will learn how to navigate the challenges of big data management and database design, unlocking the potential of colossal datasets within the socio-technical landscape. As socio-technical organizations continue to evolve, real-time BI systems emerge as the linchpin of success. The book delves into their design, development, and architectural nuances, illuminating these concepts through case studies. This book is ideal for business executives, entrepreneurs, data analysts, marketers, government officials, educators, and researchers.