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Titlebook: Development Methodologies for Big Data Analytics Systems; Plan-driven, Agile, Manuel Mora,Fen Wang,Hector Duran-Limon Book 2024 The Editor

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書(shū)目名稱(chēng)Development Methodologies for Big Data Analytics Systems
副標(biāo)題Plan-driven, Agile,
編輯Manuel Mora,Fen Wang,Hector Duran-Limon
視頻videohttp://file.papertrans.cn/270/269867/269867.mp4
概述Addresses the mathematical, statistical and computational foundations and techniques of Big Data Analytics.Includes specific research problems in the development methodologies from a Systems and Softw
叢書(shū)名稱(chēng)Transactions on Computational Science and Computational Intelligence
圖書(shū)封面Titlebook: Development Methodologies for Big Data Analytics Systems; Plan-driven, Agile,  Manuel Mora,Fen Wang,Hector Duran-Limon Book 2024 The Editor
描述This book presents research in big data analytics (BDA) for business of all sizes. The authors analyze problems presented in the application of BDA in some businesses through the study of development methodologies based on the three approaches – 1) plan-driven, 2) agile and 3) hybrid lightweight. The authors first describe BDA systems and how they emerged with the convergence of Statistics, Computer Science, and Business Intelligent Analytics with the practical aim to provide concepts, models, methods and tools required for exploiting the wide variety, volume, and velocity of available business internal and external data - i.e. Big Data – and provide decision-making value to decision-makers. ?The book presents high-quality conceptual and empirical research-oriented chapters on plan-driven, agile, and hybrid lightweight development methodologies and relevant supporting topics for BDA systems suitable to be used for large-, medium-, and small-sized business organizations..
出版日期Book 2024
關(guān)鍵詞Big Data Analytics Systems; Big Data Development Methodologies; CRISP-DM; SEMMA and KDD; Scrum; Agile pra
版次1
doihttps://doi.org/10.1007/978-3-031-40956-1
isbn_softcover978-3-031-40958-5
isbn_ebook978-3-031-40956-1Series ISSN 2569-7072 Series E-ISSN 2569-7080
issn_series 2569-7072
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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A Selective Conceptual Review of CRISP-DM and DDSL Development Methodologies for Big Data Analyticsre still scarce in the literature. In this chapter, we address this knowledge gap, and using the ISO/IEC 29110 standard – Basic profile – as a theoretical expected lightweight development process, we report a selective conceptual review between CRISP-DM – the main rigor-oriented BDAS methodology – a
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Big Data Adoption Factors and Development Methodologies: A Multiple Case Study Analysis,m-size teams. They have used agile development methodology that enabled them to create rapid development, continuous improvement, increased stakeholder participation, and ability to develop with incomplete big data expertise. It also has some challenges that include repeated conflict, feature intera
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