Engineering and Management of Data Science, Analytics, and AI/ML Projects : Foundations, Models, Frameworks, Architectures, Standards, Processes, Practices, Platforms and Tools for Small and Big Data / edited by Manuel Mora, Jorge Marx Gómez, Fen Wang, Hector A. Duran-Limon.

Format:

Book

Author/Creator:

Mora Valverde, Manuel.

Series:

Intelligent Systems Reference Library, 1868-4408 ; 282

Language:

English

Subjects (All):

Engineering--Data processing.

Engineering.

Automatic control.

Robotics.

Automation.

Computational intelligence.

Big data.

Data Engineering.

Control, Robotics, Automation.

Computational Intelligence.

Big Data.

Local Subjects:

Data Engineering.

Control, Robotics, Automation.

Computational Intelligence.

Big Data.

Physical Description:

1 online resource (186 pages)

Edition:

1st ed. 2026.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2026.

Summary:

This book presents a dual perspective on modern research and praxis on Data Science, Analytics, and AI/Machine Learning (DSA-AI/ML) system with small or big data. Consequently, potential readers—academics, researchers and practitioners interested in the systematic development and implementation of DSA-AI/ML systems—can be benefited with the high-quality conceptual and empirical research chapters focused on: Foundations, Development Platforms, and Tools on Engineering and Management of DSA-AI/ML Projects: DSA-AI/ML reference architectures. Data visualization principles for DSA-AI/ML. Federated Learning in large-scale DSA-AI/ML systems. Achievements, Challenges, Trends, and Future Research Directions on DSA-AI/ML Projects: Large multimodal model-based simulation game for DSA-AI/ML systems. Value stream analysis and design applied to DSA-AI/ML systems. Quality management 4.0 and AI for DSA-AI/ML systems. Hence, this research-oriented co-edited book contributes to achieve the systematic development and implementation of Data Science, Analytics, and AI/ML systems.

Contents:

1.A Review of Main Non-Proprietary Domain- Independent Data Science Analytics AI/ML Reference Architectures – a dual ISO/IEC/IEEE 42010 and IT Service Design Approach

2.Data Visualization in the Era of Data Science: a review

3.Requirements for using Federated Learning in Manufacturing Supply Chains

4.Large Multimodal Model-Based Simulation Game as a Socio-Technical System for Value Stream Analysis and Design

5.A Data-driven Clustering Approach for Assessing Service Performance of Brand Chains' Branches in the Food Service Industry Data Analytics Systems

6.Integrating Quality Management 4.0 with AI and Machine Learning.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9783032068897

OCLC:

1564414602