Knowledge Management in the Development of Data-Intensive Systems Knowledge Management in the Development of Data-Intensive Systems

Knowledge Management in the Development of Data-Intensive Systems

Ivan Mistrík その他
    • ¥9,800
    • ¥9,800

発行者による作品情報

Data-intensive systems are software applications that process and generate Big Data. Data-intensive systems support the use of large amounts of data strategically and efficiently to provide intelligence. For example, examining industrial sensor data or business process data can enhance production, guide proactive improvements of development processes, or optimize supply chain systems. Designing data-intensive software systems is difficult because distribution of knowledge across stakeholders creates a symmetry of ignorance, because a shared vision of the future requires the development of new knowledge that extends and synthesizes existing knowledge.

Knowledge Management in the Development of Data-Intensive Systems addresses new challenges arising from knowledge management in the development of data-intensive software systems. These challenges concern requirements, architectural design, detailed design, implementation and maintenance. The book covers the current state and future directions of knowledge management in development of data-intensive software systems. The book features both academic and industrial contributions which discuss the role software engineering can play for addressing challenges that confront developing, maintaining and evolving systems;data-intensive software systems of cloud and mobile services; and the scalability requirements they imply. The book features software engineering approaches that can efficiently deal with data-intensive systems as well as applications and use cases benefiting from data-intensive systems.

Providing a comprehensive reference on the notion of data-intensive systems from a technical and non-technical perspective, the book focuses uniquely on software engineering and knowledge management in the design and maintenance of data-intensive systems. The book covers constructing, deploying, and maintaining high quality software products and software engineering in and for dynamic and flexible environments. This book provides a holistic guide for those who need to understand the impact of variability on all aspects of the software life cycle. It leverages practical experience and evidence to look ahead at the challenges faced by organizations in a fast-moving world with increasingly fast-changing customer requirements and expectations.

ジャンル
コンピュータ/インターネット
発売日
2021年
6月15日
言語
EN
英語
ページ数
342
ページ
発行者
CRC Press
販売元
Taylor & Francis Group
サイズ
15
MB
Software Technology Software Technology
2018年
Big Data Analytics with Applications in Insider Threat Detection Big Data Analytics with Applications in Insider Threat Detection
2017年
Applications of Machine Learning in Big-Data Analytics and Cloud Computing Applications of Machine Learning in Big-Data Analytics and Cloud Computing
2022年
Enterprise Interoperability: Smart Services and Business Impact of Enterprise Interoperability Enterprise Interoperability: Smart Services and Business Impact of Enterprise Interoperability
2018年
Research and Evidence in Software Engineering Research and Evidence in Software Engineering
2021年
Big Data Analytics Big Data Analytics
2017年