Stephen H. Kaisler – författare

Software Paradigms provides the first complete compilation of software paradigms commonly used to develop large software applications, with coverage ranging from discrete problems to full-scale applications. The book focuses on providing a structure for understanding a hierarchy of software development approaches, and showing the relationships between the different models. Coverage includes paradigms in design patterns, software components, software architectures, and frameworks. Chapters within each of these sections include design issues related to building and using the paradigm as well as numerous real world applications. A practical overview of the hierarchy of development paradigms, Software Paradigms is an excellent teaching tool for undergraduates and graduates, and a comprehensive and reliable reference for software engineers.

Software Paradigms provides the first complete compilation of software paradigms commonly used to develop large software applications, with coverage ranging from discrete problems to full-scale applications. The book focuses on providing a structure for understanding a hierarchy of software development approaches, and showing the relationships between the different models. Coverage includes paradigms in design patterns, software components, software architectures, and frameworks. Chapters within each of these sections include design issues related to building and using the paradigm as well as numerous real world applications. A practical overview of the hierarchy of development paradigms, Software Paradigms is an excellent teaching tool for undergraduates and graduates, and a comprehensive and reliable reference for software engineers.

Big data is an emerging phenomenon that has enormous implications and impacts upon business strategy, profitability, and process improvements. All service systems generate big data these days, especially human-centered service systems. It has been characterized as the collection, analysis and use of data characterized by the five Vs: volume, velocity, variety, veracity, and value (of data). This booklet will help middle, senior, and executive managers to understand what big data is; how to recognize, collect, process, and analyze it; how to store and manage it; how to obtain useful information from it; and how to assess its contribution to operational, tactical, and strategic decision-making in service-oriented organizations.

Volume I of this two-volume series focuses on the role of big data in service delivery systems. It discusses the definition and orientation to big data, applications of it in service delivery systems, how to obtain results that can affect/enhance service delivery, and how to build an effective big data organization.This volume will assist readers in fitting big data analysis into their service-based organizations. It will also help readers understand how to improve the use of big data to enhance their service-oriented organizations.

This volume will assist readers in fitting big data analysis into their service-based organizations.

Volume I of this two-volume series focuses on the role of big data in service delivery systems. It discusses the definition and orientation to big data, applications of it in service delivery systems, how to obtain results that can affect/enhance service delivery, and how to build an effective big data organization.

This volume will assist readers in fitting big data analysis into their service-based organizations. It will also help readers understand how to improve the use of big data to enhance their service-oriented organizations.

Volume II of this series discusses the technology used to implement a big data analysis capability within a service-oriented organization. It discusses the technical architecture necessary to implement a big data analysis capability, some issues and challenges in big data analysis and utilization that an organization will face, and how to capture value from it.It will help readers understand what technology is required for a basic capability and what the expected benefits are from establishing a big data capability within their organization.