Ramesh Sharda – författare

Business Intelligence, Analytics, Data Science, and AI is your guide to the business-related impact of artificial intelligence, data science and analytics, designed to prepare you for a managerial role. The text's vignettes and cases feature modern companies and non-profit organizations and illustrate capabilities, costs and justifications of BI across various business units. With coverage of many data science/AI applications, you'll explore tools, then learn from various organizations' experiences employing such applications. Ample hands-on practice is provided, can be completed with a range of software, and will help you use analytics as a future manager.

The 5th Edition integrates the fully updated content of Analytics, Data Science, and Artificial Intelligence, 11/e and Business Intelligence, Analytics, and Data Science, 4/e into one textbook, strengthened by 4 new chapters that will equip you for today's analytics and AI tech, such as ChatGPT. Examples explore analytics in sports, gaming, agriculture and “data for good.”

Data-driven decision-making is now a core capability for organisations across every industry. Business Intelligence, Analytics, Data Science, and AI introduces the concepts, technologies, and methods that help organisations transform data into actionable insights. Designed to help learners understand the business impact of analytics and artificial intelligence, the content explores descriptive, predictive, and prescriptive analytics alongside emerging AI technologies. Through real-world examples, practical applications, and contemporary business scenarios, learners gain insight into how organisations use analytics to improve performance, support strategy, and address complex challenges.

Learners develop the knowledge required to evaluate and apply business intelligence, analytics, data science, and AI in organisational settings. Coverage spans data management, statistical modelling, visualisation, data mining, deep learning, optimisation, simulation, and AI-driven technologies, helping learners understand how different approaches support decision-making. Practical exercises, cases, and assignments reinforce learning while exposing learners to common analytics tools and techniques. The content also explores ethical, privacy, managerial, and governance considerations, preparing learners to engage with analytics and AI responsibly in professional environments.

Who It's For

Designed for one- or two-semester courses in business intelligence, data science, business analytics, and management information systems (MIS).

India is becoming the "global back office" to international supply chains, creating a substantial communications and decision-support infrastructure for large and small enterprises in the global market place to utilize these resources. Decision Support for Global Enterprises consists of peer-reviewed and invited papers with two primary goals: (1) Stimulate creative discussion between academic researchers and the practitioner IS community to improve the research and practice in the area. (2) Increase awareness of the problems and challenges faced by global enterprises that can be met with innovative decision support systems. Limitations are also explored, covering the following topics: (1) the emerging enterprise decision making processes and technologies; (2) decision making in uncertain, changing conditions; (3) the changing infrastructure in organizations and society; (4) the expanding role of web technologies; and (5) emerging theories and practices for managing knowledge and making decisions.

For courses in decision support systems, computerised decision-making tools, and management support systems. Market-leading guide to modern analytics, for better business decisions Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organisations that have employed analytics to make decisions. With six new chapters, the 11th edition marks a major reorganisation reflecting a new focus — analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT.

For courses in decision support systems, computerized decision-making tools, and management support systems.

Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organizations that have employed analytics to make decisions, while leveraging the resources of a companion website. With six new chapters, the 11th edition marks a major reorganization reflecting a new focus — analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT.

This volume of Annals of Information Systems will acknowledge the twentieth anniversary of the founding of the International Society for Decision Support Systems (ISDSS) by documenting some of the current best practices in teaching and research and envisioning the next twenty years in the decision support systems field. The volume is intended to complement existing DSS literature by offering an outlet for thoughts and research particularly suited to the theme of describing the next twenty years in the area of decision support.

Several subthemes are planned for the volume. One subtheme draws on the assessments of internationally known DSS researchers to evaluate where the field has been and what has been accomplished. A second subtheme of the volume will be describing the current best practices of DSS research and teaching efforts. A third subtheme will be an assessment by top DSS scholars on where the DSS discipline needs to focus in the future. The tone of this volume is one of enthusiasm for the potential contributions to come in the area of DSS; contributions that must incorporate an understanding of what has been accomplished in the past, build on the best practices of today, and be be integrated into future decision making practices.

The primary questions raised by this volume are:

Los datos se han convertido en un recurso estratégico para las organizaciones que buscan tomar mejores decisiones, identificar oportunidades y responder a entornos cada vez más dinámicos. Inteligencia de Negocios, Analítica, Ciencia de Datos e IA: Una Perspectiva Gerencial ofrece una visión clara y actual de cómo las organizaciones utilizan la analítica, la ciencia de datos y la inteligencia artificial para transformar datos en información útil para la gestión y la toma de decisiones.

Con un enfoque orientado a la gestión, el contenido explora conceptos fundamentales y tecnologías emergentes que apoyan el análisis de datos en distintos contextos organizacionales. A través de ejemplos reales, herramientas actuales y aplicaciones prácticas, los estudiantes desarrollan una comprensión de cómo la analítica y la IA pueden utilizarse para abordar desafíos empresariales y respaldar iniciativas de innovación y mejora organizacional.

Desarrolla la capacidad de interpretar datos, evaluar información y comprender cómo distintas formas de analítica pueden apoyar la toma de decisiones. Fortalece tu comprensión de la analítica descriptiva, predictiva y prescriptiva, así como de tecnologías relacionadas con la inteligencia artificial y la ciencia de datos. Al conectar conceptos, herramientas y aplicaciones empresariales, el contenido ayuda a desarrollar una perspectiva informada sobre el uso de datos para resolver problemas, identificar patrones y apoyar objetivos organizacionales.

Características Principales

Los datos se han convertido en un recurso estratégico para las organizaciones que buscan tomar mejores decisiones, identificar oportunidades y responder a entornos cada vez más dinámicos. Inteligencia de Negocios, Analítica, Ciencia de Datos e IA: Una Perspectiva Gerencial ofrece una visión clara y actual de cómo las organizaciones utilizan la analítica, la ciencia de datos y la inteligencia artificial para transformar datos en información útil para la gestión y la toma de decisiones.

Con un enfoque orientado a la gestión, el contenido explora conceptos fundamentales y tecnologías emergentes que apoyan el análisis de datos en distintos contextos organizacionales. A través de ejemplos reales, herramientas actuales y aplicaciones prácticas, los estudiantes desarrollan una comprensión de cómo la analítica y la IA pueden utilizarse para abordar desafíos empresariales y respaldar iniciativas de innovación y mejora organizacional.

Desarrolla la capacidad de interpretar datos, evaluar información y comprender cómo distintas formas de analítica pueden apoyar la toma de decisiones. Fortalece tu comprensión de la analítica descriptiva, predictiva y prescriptiva, así como de tecnologías relacionadas con la inteligencia artificial y la ciencia de datos. Al conectar conceptos, herramientas y aplicaciones empresariales, el contenido ayuda a desarrollar una perspectiva informada sobre el uso de datos para resolver problemas, identificar patrones y apoyar objetivos organizacionales.

Características Principales