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.

Increasingly India, with its expertise in communication technology, is becoming the "global back office" to international supply chains. Many international companies (and examples are legion, but a few examples are IBM, Sony, Exxon/Mobil, etc.) have employed Indian resources to help them with their data, their computerized decision support and their knowledge management. With large corporations opening the path to India, it has allowed a substantial communications and decision-support infrastructure to develop in a number of Indian cities. Therefore, opportunities have emerged for both large and small enterprises in the global market place to utilize these developing Indian resources.

DECISION SUPPORT FOR GLOBAL ENTERPRISES is a volume of a mixture of peer-reviewed and invited papers. The volume will have two primary goals: (1) Stimulate creative and thoughtful discussion between academic research leaders and the practitioner information systems community that will improve both the research and practice in the area. (2) Increase the awareness of the problems and challenges faced by global enterprises that can be met with innovative computerized decision support systems. In addition to the positive aspects, the limitations of these systems and technologies are also explored. Emphasized in the book will be research on the following topics: (1) the emerging enterprise decision making processes and technologies; (2) decision making in uncertain, rapidly 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 in making decisions.

For courses on Business Intelligence or Decision Support Systems. A managerial approach to understanding business intelligence systems. To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice.

For courses on Business Intelligence or Decision Support Systems. A managerial approach to understanding business intelligence systems. To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice.

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:

• What will information systems-based decision support entail in twenty years?
• What research is needed to realize the envisioned future of information systems-based decision support?
• How will the teaching of information systems-based decision support change over the next twenty years?
• What are the best practices of teaching in the decision support area that can be leveraged to best disseminate DSS knowledge advances to students and practitioners?