Development Methodologies for Big Data Analytics Systems Plan-driven, Agile, Hybrid, Lightweight Approaches
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. Th...
| Other Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2024, 2024
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| Edition: | 1st ed. 2024 |
| Series: | Transactions on Computational Science and Computational Intelligence
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Introduction
- 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