Low Latency Big Data Visualisation


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Low-latency big data visualisation


Low-latency big data visualisation

Author: Tan Jerome, Nicholas

language: en

Publisher: KIT Scientific Publishing

Release Date: 2019-11-20


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Research Methodology Tools and Techniques


Research Methodology Tools and Techniques

Author: Dr. T. Vasanthi

language: en

Publisher: CiiT Publications

Release Date: 2025-02-14


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The book entitled Research Methodology: Tools and Techniques is a multidisciplinary comprehensive and cutting edge explorative advancement in resilience of modern research. The technical content of the book is divided into multiple Chapters, each meticulously crafted to address the key challenges and methodologies relevant to the present scenario. The contributions by the authors include What is research?, Why research?, How to research?, When and where to research?, Existing and emerging research tools and techniques, Role of AI in research, Project grant supports and the directions of project proposal writing. This edited volume envisioned the top-down investigative approach in the arena of research. This book will serve as a valuable resource for academicians, researchers, and the graduate students to enrich their research knowledge. We acknowledge the contribution of authors to this book would be of great value.

The Elements of Big Data Value


The Elements of Big Data Value

Author: Edward Curry

language: en

Publisher: Springer Nature

Release Date: 2021-06-30


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This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.


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