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001 978-3-031-40956-1
003 DE-He213
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020 _a9783031409561
_9978-3-031-40956-1
024 7 _a10.1007/978-3-031-40956-1
_2doi
050 4 _aTK5101-5105.9
072 7 _aTJK
_2bicssc
072 7 _aTEC041000
_2bisacsh
072 7 _aTJK
_2thema
245 1 0 _aDevelopment Methodologies for Big Data Analytics Systems
_h[electronic resource] :
_bPlan-driven, Agile, Hybrid, Lightweight Approaches /
_cedited by Manuel Mora, Fen Wang, Jorge Marx Gomez, Hector Duran-Limon.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2024.
300 _aXVI, 280 p. 68 illus., 22 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTransactions on Computational Science and Computational Intelligence,
_x2569-7080
505 0 _aIntroduction -- Section I – Foundations on Big Data Analytics Systems -- Big Data Analytics foundations -- Big Data Science foundations -- Big Data Analytics Systems Frameworks -- Big Data Analytics Systems Architectures -- Big Data Analytics Tools and Platforms -- Big Data Analytics Computational Techniques -- Section II – Plan-Driven Development Methodologies for Big Data Analytics Systems -- CRISP-DM -- SEMMA -- KDD -- Section III – Emergent Agile and Hybrid Lightweight Development -- Methodologies for Big Data Analytics Systems -- Scrum -- ISO/IEC 29110 -- Microsoft TDSP -- Section IV – Cases Studies of Big Data Analytics Systems Projects -- Applications in Healthcare -- Applications in Marketing -- Applications in Financial -- Applications in Education -- Applications in Sports -- Section V – Challenges and Future Directions on Big Data Analytics Systems Projects -- Review of challenges -- Current problems and limitations -- Future directions -- Conclusion.
520 _aThis 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. 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 Software perspective; Presents successful BDA systems applied in diverse domains such as Healthcare, Logistics, Finance, Marketing, Retail, and Education.
650 0 _aTelecommunication.
650 0 _aData mining.
_96941
650 0 _aBig data.
_957216
650 0 _aQuantitative research.
650 1 4 _aCommunications Engineering, Networks.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aBig Data.
_957216
650 2 4 _aData Analysis and Big Data.
700 1 _aMora, Manuel.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_966988
700 1 _aWang, Fen.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_966989
700 1 _aMarx Gomez, Jorge.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_966990
700 1 _aDuran-Limon, Hector.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_966991
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031409554
776 0 8 _iPrinted edition:
_z9783031409578
776 0 8 _iPrinted edition:
_z9783031409585
830 0 _aTransactions on Computational Science and Computational Intelligence,
_x2569-7080
_966992
856 4 0 _uhttps://doi.org/10.1007/978-3-031-40956-1
912 _aZDB-2-ENG
912 _aZDB-2-SXE
999 _c56497
_d56497