Exploring how virtual machines boost decision support systems
This work explains using virtual machines as a practical software engineering tool to rapidly integrate data, models, and analytical facilities. The focus is on making systems that mix different programs and databases work together smoothly, even when they run on different operating systems. The approach helps teams build, test, and adapt decision support tools faster and more cost-effectively.
The book outlines a flexible GMIS architecture that connects modelling, analysis, and data management through dedicated virtual machines. It shows how interface machines link modelling environments to database systems, enabling rapid reconfiguration as needs change. Real-world examples illustrate how a relational database like SEQUEL can pair with analytical packages such as APL/EPLAN and econometric tools to support decision making.
- How multiple virtual machines can share databases while keeping each environment distinct
- Ways to connect modelling, analytics, and data management for quick experimentation
- Practical considerations for communication mechanisms and synchronization between VMs
- Insights into performance trade-offs and strategies to improve responsiveness
Ideal for readers of software engineering and management information systems who want concrete methods for building adaptable, cost-efficient decision support tools.