Manuel Mora – författare

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.

This book presents research in big data analytics (BDA) for business of all sizes.

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.

This edited volume covers essential and recent development in the engineering and management of data centers.  Data centers are complex systems requiring ongoing support, and their high value for keeping business continuity operations is crucial. The book presents core topics on the planning, design, implementation, operation and control, and sustainability of a data center from a didactical and practitioner viewpoint. Chapters include:·         Foundations of data centers: Key Concepts and Taxonomies·         ITSDM: A Methodology for IT Services Design·         Managing Risks on Data Centers through Dashboards·         Risk Analysis in Data Center Disaster Recovery Plans·         Best practices in Data Center Management  Case: KIO Networks·         QoS in NaaS (Network as a  Service) using Software Defined Networking·         Optimization of Data Center Fault-Tolerance Design·         Energetic Data Centre Design Considering Energy Efficiency Improvements During Operation·         Demand-side Flexibility and Supply-side  Management: The Use Case of Data Centers and Energy Utilities ·         DevOps: Foundations and its Utilization in Data Centers·         Sustainable and Resilient Network Infrastructure Design for Cloud Data Centres·         Application Software in Cloud-Ready Data Centers This book bridges the gap between academia and the industry, offering essential reading for practitioners in data centers, researchers in the area, and faculty teaching related courses on data centers. The book can be used as a complementary text for traditional courses on Computer Networks, as well as  innovative courses on IT Architecture, IT Service Management, IT Operations, and Data Centers.

This edited volume covers essential and recent development in the engineering and management of data centers.  Data centers are complex systems requiring ongoing support, and their high value for keeping business continuity operations is crucial. The book presents core topics on the planning, design, implementation, operation and control, and sustainability of a data center from a didactical and practitioner viewpoint. Chapters include:·         Foundations of data centers: Key Concepts and Taxonomies·         ITSDM: A Methodology for IT Services Design·         Managing Risks on Data Centers through Dashboards·         Risk Analysis in Data Center Disaster Recovery Plans·         Best practices in Data Center Management  Case: KIO Networks·         QoS in NaaS (Network as a  Service) using Software Defined Networking·         Optimization of Data Center Fault-Tolerance Design·         Energetic Data Centre Design Considering Energy Efficiency Improvements During Operation·         Demand-side Flexibility and Supply-side  Management: The Use Case of Data Centers and Energy Utilities ·         DevOps: Foundations and its Utilization in Data Centers·         Sustainable and Resilient Network Infrastructure Design for Cloud Data Centres·         Application Software in Cloud-Ready Data Centers This book bridges the gap between academia and the industry, offering essential reading for practitioners in data centers, researchers in the area, and faculty teaching related courses on data centers. The book can be used as a complementary text for traditional courses on Computer Networks, as well as  innovative courses on IT Architecture, IT Service Management, IT Operations, and Data Centers.

Intelligent Decision-Making Support Systems (i-DMSS) are specialized IT-based systems that support some or several phases of the individual, team, organizational or inter-organizational decision making process by deploying some or several intelligent mechanisms. This book pursues the following academic aims: (i) generate a compendium of quality theoretical and applied contributions in Intelligent Decision-Making Support Systems (i-DMSS) for engineering and management IT-based service systems (ITSS); (ii)  diffuse scarce knowledge about foundations, architectures and effective and efficient methods and strategies for successfully planning, designing, building, operating, and evaluating i-DMSS for ITSS, and (iii) create an awareness of, and a bridge between ITSS and i-DMSS academicians and practitioners in the current complex and dynamic engineering and management ITSS organizational. The book presents a collection of 11 chapters referring to relevant topics for both IT service systems and i-DMSS including: problems of selection of IT service providers, optimization of supply chain systems, IT governance decisions, clinical decision support, dynamic user-interface adaptation, re-engineering of processes, and generic decision problems. Advanced IT technologies used in some chapters are:  fuzzy multi-criteria mechanisms, semantic processing, data mining processing, and rough sets. Other chapters report traditional DSS mechanisms but used or suggested to be used in innovative mode for IT service engineering and management tasks.