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| asset management data model: Practical Cloud Security Chris Dotson, 2019-03-04 With their rapidly changing architecture and API-driven automation, cloud platforms come with unique security challenges and opportunities. This hands-on book guides you through security best practices for multivendor cloud environments, whether your company plans to move legacy on-premises projects to the cloud or build a new infrastructure from the ground up. Developers, IT architects, and security professionals will learn cloud-specific techniques for securing popular cloud platforms such as Amazon Web Services, Microsoft Azure, and IBM Cloud. Chris Dotson—an IBM senior technical staff member—shows you how to establish data asset management, identity and access management, vulnerability management, network security, and incident response in your cloud environment. |
| asset management data model: Asset Management for Infrastructure Systems Gerd Balzer, Christian Schorn, 2015-05-18 The book offers a broad overview of asset management processes for different utilities, with a special emphasis on energy and water. It provides readers with important practical considerations concerning the development of new competitive structures and procedures for guaranteeing a sufficient supply of energy and water in a regulated environment, using clearly defined technical and economic cornerstones. On the one hand asset owners expect suitable interests from their investment and business growth; on the other hand regulators focus more on a reliable and cost-effective customer supply. This book shows how to take into consideration these different perspectives in the process of designing new structures and how to guarantee organizational transparency. Based on the major tasks of an asset manager, it describes essential principles and boundary conditions for ensuring the optimal use of resources in a network, such as investment and maintenance strategies, equipment service life, investment and operational costs, etc. Moreover, it points out their impact on the organization of the company, including the necessary IT landscape and computer programs. The book is the English translation of Asset Management für Infrastrukturanlagen - Energie und Wasser1, written by the same authors and published by Springer in 2014. |
| asset management data model: The Data Model Resource Book, Volume 2 Len Silverston, 2001-03-21 A quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful First Edition, while adding a companion volume to take care of more specific requirements of different businesses. Each volume is accompanied by a CD-ROM, which is sold separately. Each CD-ROM provides powerful design templates discussed in the books in a ready-to-use electronic format, allowing companies and individuals to develop the databases they need at a fraction of the cost and a third of the time it would take to build them from scratch. With each business function boasting its own directory, this CD-ROM provides a variety of data models for specific implementations in such areas as financial services, insurance, retail, healthcare, universities, and telecom. |
| asset management data model: AASHTO Transportation Asset Management Guide American Association of State Highway and Transportation Officials, 2011 Aims to encourage transportation agencies to address strategic questions as they confront the task of managing the surface transportation system. Drawn form both national and international knowledge and experience, it provides guidance to State Department of Transportation (DOT) decision makers, as well as county and municipal transportation agencies, to assist them in realizing the most from financial resources now and into the future, preserving highway assets, and providing the service expected by customers. Divided into two parts, Part one focuses on leadership and goal and objective setintg, while Part two is more technically oriented. Appendices include work sheets and case studies. |
| asset management data model: Transportation Asset Management Zongzhi Li, 2018-08-31 Transportation asset management delivers efficient and cost-effective investment decisions to support transportation infrastructure and system usage performance measured in economic, social, health, and environmental terms. It can be applied at national, state, and local levels. This distinctive book addresses asset management for multimodal transportation, taking account of system component interdependency, integration, and risk and uncertainty. It sets out rigorous quantitative and qualitative methods for addressing system goals, performance measures, and needs; data collection and management; performance modeling; project evaluation, selection, and trade-off analysis; innovative financing; and institutional issues. It applies as easily to static traffic and time-dependent or dynamic traffic which exists on a more local level. It is written for transportation planners, engineers, and academia, as well as a growing number of graduate students taking transportation asset management courses. |
| asset management data model: Engineering Asset Management Joseph Mathew, Lin Ma, Andy Tan, Deryk Anderson, 2008-02-06 It is with great pleasure that we welcome you to the inaugural World Congress on Engineering Asset Management (WCEAM) being held at the Conrad Jupiters Hotel on the Gold Coast from July 11 to 14, 2006. More than 170 authors from 28 countries have contributed over 160 papers to be presented over the first three days of the conference. Day four will be host to a series of workshops devoted to the practice of various aspects of Engineering Asset Management. WCEAM is a new annual global forum on the various multidisciplinary aspects of Engineering Asset Management. It deals with the presentation and publication of outputs of research and development activities as well as the application of knowledge in the practical aspects of: strategic asset management risk management in asset management design and life-cycle integrity of physical assets asset performance and level of service models financial analysis methods for physical assets reliability modelling and prognostics information systems and knowledge management asset data management, warehousing and mining condition monitoring and intelligent maintenance intelligent sensors and devices regulations and standards in asset management human dimensions in integrated asset management education and training in asset management and performance management in asset management. We have attracted academics, practitioners and scientists from around the world to share their knowledge in this important emerging transdiscipline that impacts on almost every aspect of daily life. |
| asset management data model: Digital Built Asset Management Qiuchen Lu, Michael Pitt, 2024-10-03 This insightful book presents a comprehensive understanding of the new technologies impacting the digital era of built asset and facility management. Informative and accessible, it illustrates how the concepts, principles, strategies and applications of digital built asset management can be improved and implemented in real-life practice. |
| asset management data model: Engineering Asset Management Dimitris Kiritsis, Christos Emmanouilidis, Andy Koronios, Joseph Mathew, 2011-02-03 Engineering Asset Management discusses state-of-the-art trends and developments in the emerging field of engineering asset management as presented at the Fourth World Congress on Engineering Asset Management (WCEAM). It is an excellent reference for practitioners, researchers and students in the multidisciplinary field of asset management, covering such topics as asset condition monitoring and intelligent maintenance; asset data warehousing, data mining and fusion; asset performance and level-of-service models; design and life-cycle integrity of physical assets; deterioration and preservation models for assets; education and training in asset management; engineering standards in asset management; fault diagnosis and prognostics; financial analysis methods for physical assets; human dimensions in integrated asset management; information quality management; information systems and knowledge management; intelligent sensors and devices; maintenance strategies in asset management; optimisation decisions in asset management; risk management in asset management; strategic asset management; and sustainability in asset management. |
| asset management data model: Advanced Maintenance Modelling for Asset Management Adolfo Crespo Márquez, Vicente González-Prida Díaz, Juan Francisco Gómez Fernández, 2017-07-12 This book promotes and describes the application of objective and effective decision making in asset management based on mathematical models and practical techniques that can be easily implemented in organizations. This comprehensive and timely publication will be an essential reference source, building on available literature in the field of asset management while laying the groundwork for further research breakthroughs in this field. The text provides the resources necessary for managers, technology developers, scientists and engineers to adopt and implement better decision making based on models and techniques that contribute to recognizing risks and uncertainties and, in general terms, to the important role of asset management to increase competitiveness in organizations. |
| asset management data model: Global Asset Management M. Pinedo, I. Walter, 2013-08-29 This book focuses on all major aspects of the asset management industry including its regulations, strategies, processes, applied technologies and risks. It provides a serious resource for readers seeking greater depth and alternative opinions on specific industry developments, and breadth for specialists interested in the dynamics of the industry. |
| asset management data model: Research Companion to Building Information Modeling Lu, Weisheng, Anumba, Chimay J., 2022-03-22 Offering critical insights to the state-of-the-art in Building Information Modeling (BIM) research and development, this book outlines the prospects and challenges for the field in this era of digital revolution. Analysing the contributions of BIM across the construction industry, it provides a comprehensive survey of global BIM practices. |
| asset management data model: Information Asset Management James Price, Nina Evans, 2024-01-31 Organisations are using data, information and knowledge as a competitive weapon. Their data, information and knowledge are arguably their most valuable assets. Yet, this fourth asset is managed badly when compared to the other three assets, namely money, people and infrastructure with considerable risk to the organisation. Executives are accountable for the success of their organisations, and those who don’t manage this critical resource and business enabler effectively can be regarded as negligent. Information Assets carry enormous risk and value. Most boards and executives don’t know how to govern and manage IAs effectively and nobody is held accountable. Given this, organisations should govern and manage their Information Assets the way they manage their Financial Assets. The benefits of managing IAs well are compelling. These benefits include increased efficiency, productivity, employee satisfaction, improved decision-making, mitigating business risk and improving product, protecting corporate reputation and service delivery. Drawing on ground-breaking research, this book explains why Information Assets are so important to organisations and the barriers to managing them well. This book is unique in the sense that it takes a fresh look at this topic, is based on experience and research, and includes interviews from more than 70 industry leaders. In short, this book is written by executives and explains where to start. |
| asset management data model: Power and Gas Asset Management Miguel Moreira da Silva, 2020-01-01 This book offers meaningful insights into an impending challenge for the energy industry, namely the increasing role of asset management amongst the utilities’ core operations. In the aftermath of energy digitalization, power and gas companies will be able to seize asset productivity—through risk-based operation and maintenance—and better balance capital and operational expenditures. By addressing the asset management of both power and gas infrastructures, and by adopting a comprehensive approach—including regulation and business models, as well as a solid technology background—this book offers a unique perspective on the energy utilities’ transformation journey and the road to optimal decision-making for both asset portfolio expansion and replacement. The asset management end-to-end mission requires appropriate internal governance—depending on the business framework—and the development of decision aid models (for asset replacement and maintenance), supported on probabilistic risk and reliability indexes. This book advocates systematically digitalizing the power and gas assets, addressing both data governance and infrastructure, alongside real-time equipment condition monitoring. It also provides a meaningful methodology for designing data-centric asset management and predictive operation and maintenance, using artificial intelligence and engineering-based approaches. As such, it provides valuable strategy, methods and models—illustrated by case studies and proofs of concept—for a wide range of stakeholders, including utilities and industry professionals, regulators, policy-makers, researchers and students. |
| asset management data model: Advances in Production Management Systems. Production Management for the Factory of the Future Farhad Ameri, Kathryn E. Stecke, Gregor von Cieminski, Dimitris Kiritsis, 2019-08-23 The two-volume set IFIP AICT 566 and 567 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2019, held in Austin, TX, USA. The 161 revised full papers presented were carefully reviewed and selected from 184 submissions. They discuss globally pressing issues in smart manufacturing, operations management, supply chain management, and Industry 4.0. The papers are organized in the following topical sections: lean production; production management in food supply chains; sustainability and reconfigurability of manufacturing systems; product and asset life cycle management in smart factories of industry 4.0; variety and complexity management in the era of industry 4.0; participatory methods for supporting the career choices in industrial engineering and management education; blockchain in supply chain management; designing and delivering smart services in the digital age; operations management in engineer-to-order manufacturing; the operator 4.0 and the Internet of Things, services and people; intelligent diagnostics and maintenance solutions for smart manufacturing; smart supply networks; production management theory and methodology; data-driven production management; industry 4.0 implementations; smart factory and IIOT; cyber-physical systems; knowledge management in design and manufacturing; collaborative product development; ICT for collaborative manufacturing; collaborative technoloy; applications of machine learning in production management; and collaborative technology. |
| asset management data model: Machine Learning for Asset Managers Marcos M. López de Prado, 2020-04-22 Successful investment strategies are specific implementations of general theories. An investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset manager should concentrate her efforts on developing a theory rather than on backtesting potential trading rules. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. Some of ML's strengths include (1) a focus on out-of-sample predictability over variance adjudication; (2) the use of computational methods to avoid relying on (potentially unrealistic) assumptions; (3) the ability to learn complex specifications, including nonlinear, hierarchical, and noncontinuous interaction effects in a high-dimensional space; and (4) the ability to disentangle the variable search from the specification search, robust to multicollinearity and other substitution effects. |
| asset management data model: IBM Tivoli Change and Configuration Management Database (CCMDB) V7.2.1 Implementation Guide Yatresh Agarwal, Bill Cary, Sandy Cash, Leandro Cassa, Brian Demartini, Chris Duplantis, Alisson Negrisolo de Godoi, Douglas Barranqueiros Gomes, Vasfi Gucer, Murat Kipel, Antonio Orlando Neto, Caio Elias Saad, Ghufran Shah, Peterson Domingos Tamarindo, Krishnan Venkitasubramanian, IBM Redbooks, 2010-12-13 The IBM® Tivoli® Change and Configuration Management Database (CCMDB) is one of the key components of the IBM Service Management (ISM) strategy. It is the foundation for automating and supporting change and configuration management processes as described by the Information Technology Infrastructure Library (ITIL®). These process solutions provide best practice implementations of processes based not only on ITIL, but on the IBM Process Reference Model for ITTM and other standards as well. This IBM Redbooks® publication provides information that can be used by clients, partners, or IBM field personnel who are looking to engage in an effort to implement change and configuration management processes in an enterprise environment utilizing the IBM Tivoli Change and Configuration Management Database (CCMDB) V 7.2.1 product. It covers the new features available with CCMDB V7.2 and CCMDB V7.2.1, as well as details about the underlying components of the product and utilizing the product to support robust IT processes such as change and configuration management. It also focuses on the details of the data model, process engine, and the Change and Configuration management Process Management Programs (PMPs). This book provides a reference for IT Specialists and IT Architects working with the CCMDB V7.2.1 product. |
| asset management data model: Advances in Production Management Systems. Competitive Manufacturing for Innovative Products and Services Christos Emmanouilidis, Marco Taisch, Dimitris Kiritsis, 2013-08-13 The two volumes IFIP AICT 397 and 398 constitute the thoroughly refereed post-conference proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2012, held in Rhodes, Greece, in September 2012. The 182 revised full papers were carefully reviewed and selected for inclusion in the two volumes. They are organized in 6 parts: sustainability; design, manufacturing and production management; human factors, learning and innovation; ICT and emerging technologies in production management; product and asset lifecycle management; and services, supply chains and operations. |
| asset management data model: Engineering Asset Management - Systems, Professional Practices and Certification Peter W. Tse, Joseph Mathew, King Wong, Rocky Lam, C.N. Ko, 2014-12-09 This proceeding represents state-of-the-art trends and developments in the emerging field of engineering asset management as presented at the Eight World Congress on Engineering Asset Management (WCEAM). The Proceedings of the WCEAM 2013 is an excellent reference for practitioners, researchers and students in the multidisciplinary field of asset management, covering topics such as: Asset condition monitoring and intelligent maintenance, 2. Asset data warehousing, data mining and fusion, 3. Asset performance and level-of-service models, 4. Design and life-cycle integrity of physical assets, 5. Deterioration and preservation models for assets, 6. Education and training in asset management, 7. Engineering standards in asset management, 8. Fault diagnosis and prognostics, 9. Financial analysis methods for physical assets, 10. Human dimensions in integrated asset management, 11. Information quality management, 12. Information systems and knowledge management, 13. Intelligent sensors and devices, 14. Maintenance strategies in asset management, 15. Optimisation decisions in asset management, 16. Risk management in asset management, 17. Strategic asset management, 18. Sustainability in asset management. King WONG served as Congress Chair for WCEAM 2013 and ICUMAS 2013 is the President of the Hong Kong Institute of Utility Specialists (HKIUS) and Convener of International Institute of Utility Specialists (IIUS). Peter TSE is the Director of the Smart Engineering Asset Management laboratory (SEAM) at the City University of Hong Kong and served as the Chair of WCEAM 2013 Organising Committee. Joseph MATHEW served as the Co-Chair of WCEAM 2013 is also WCEAM’s General Chair. He is the Chief Executive Officer of Asset Institute, Australia. |
| asset management data model: Pavement Asset Management Ralph Haas, W. Ronald Hudson, 2015-04-30 Comprehensive and practical, Pavement Asset Management provides an essential resource for educators, students and those in public agencies and consultancies who are directly responsible for managing road and airport pavements. The book is comprehensive in the integration of activities that go into having safe and cost-effective pavements using the best technologies and management processes available. This is accomplished in seven major parts, and 42 component chapters, ranging from the evolution of pavement management to date requirements to determining needs and priority programming of rehabilitation and maintenance, followed by structural design and economic analysis, implementation of pavement management systems, basic features of working systems and finally by a part on looking ahead. The most current methodologies and practical applications of managing pavements are described in this one-of-a-kind book. Real world up-to-date examples are provided, as well as an extensive list of references for each part. |
| asset management data model: Geographic Information Systems and Science Paul Longley, 2005-04-15 Features a five part structure covering: Foundations; Principles; Techniques; Analysis; and Management and Policy. This book includes chapters on Distributed GIS, Map Production, Geovisualization, Modeling, and Managing GIS. It offers coverage of such topics as: GIS and the New World Order; security, health and well being; and the greening of GIS. |
| asset management data model: Digital Asset Management Elizabeth Keathley, 2014-03-31 Digital Asset Management: Content Architectures, Project Management, and Creating Order out of Media Chaos is for those who are planning a digital asset management system or interested in becoming digital asset managers. This book explains both the purpose of digital asset management systems and why an organization might need one. The text then walks readers step-by-step through the concerns involved in selecting, staffing, and maintaining a DAM. This book is dedicated to providing you with a solid base in the common concerns, both legal and technical, in launching a complex DAM capable of providing visual search results and workflow options. Containing sample job models, case studies, return on investment models, and quotes from many top digital asset managers, this book provides a detailed resource for the vocabulary and procedures associated with digital asset management. It can even serve as a field guide for system and implementation requirements you may need to consider. This book is not dedicated to the purchase or launch of a DAM; instead it is filled with the information you need in order to examine digital asset management and the challenges presented by the management of visual assets, user rights, and branded materials. It will guide you through justifying the cost for deploying a DAM and how to plan for growth of the system in the future. This book provides the most useful information to those who find themselves in the bewildering position of formulating access control lists, auditing metadata, and consolidating information silos into a very new sort of workplace management tool – the DAM. The author, Elizabeth Ferguson Keathley, is a board member of the DAM Foundation and has chaired both the Human Resources and Education committees. Currently Elizabeth is working with the University of British Columbia and the DAM Foundation to establish the first official certificate program for Digital Asset Managers. She has written, taught, and been actively a part of conferences related to the arrangement, description, preservation and access of information for over ten years. Her ongoing exploration of digital asset management and its relationship to user needs can be followed at her homepage for Atlanta Metadata Authority : atlantametadata.com. |
| asset management data model: Architecture and Patterns for IT Service Management, Resource Planning, and Governance Charles T. Betz, 2011-09-23 IT in a World of Continuous Improvement -- Architecture Approach -- Patterns for the IT Processes -- Patterns for the IT Lifecycles -- APPENDIX A: Extended Definitions for the IT Architectural -- APPENDIX B: Fundamentals of Computing for the Business -- APPENDIX C: Production and Services -- REFERENCES -- INDEX. |
| asset management data model: 16th WCEAM Proceedings Adolfo Crespo Márquez, Juan Francisco Gómez Fernández, Vicente González-Prida Díaz, Joe Amadi-Echendu, 2023-02-15 This book gathers selected peer-reviewed papers from the 16th World Congress on Engineering Asset Management (WCEAM), held in Seville from 5–7 October 2022. This book covers a wide range of topics in Engineering Asset Management, including: Asset management and decision support system Industry 4.0 tools and its impact on asset management Monitoring, diagnostics and prognostics for smart maintenance Asset life cycle management Asset management in the industrial sector Human dimensions and asset management performance Infrastructure Asset management Asset condition, risk, resilience, and vulnerability assessments Asset operations and maintenance strategies Reliability and resilience engineering Applications of international and local guidelines and standards The breadth and depth of this state-of-the-art, comprehensive proceedings make it an excellent resource for asset management practitioners, researchers and academics, as well as undergraduate and postgraduate students. |
| asset management data model: Model-Driven Engineering and Software Development Slimane Hammoudi, Luís Ferreira Pires, Bran Selić, 2021-02-01 This book constitutes thoroughly revised and selected papers from the 8th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2020, held in Valletta, Malta, in February 2020. The 15 revised and extended papers presented in this volume were carefully reviewed and selected from 66 submissions. They present recent research results and development activities in using models and model driven engineering techniques for software development. The papers are organized in topical sections on methodologies, processes and platforms; applications and software development; modeling languages, tools and architectures. |
| asset management data model: WealthTech Patrick Schueffel, 2019-10-01 The book “WealthTech: Wealth and Asset Management in the Fintech Age” is the primary resource for the wealth and asset management technology revolution. It examines the rise of financial technology and its growing impact on the wealth and asset management industry. Written by thought leaders in the global WealthTech space, this volume offers an analysis of the current tectonic shifts happening in wealth and asset management and aggregates diverse industry expertise into a single informative book. It provides practitioners such as wealth managers, bankers and investors with the answers they need to capitalize on this lucrative market. As a primer on WealthTech it offers academics clear insight into the repercussions of profoundly changing business models. It furthermore highlights the concept of the ongoing democratization of wealth management towards a more efficient and client-centric advisory process, free of entry hurdles. This book aggregates facts, expertise, insights and acumen from industry experts to provide answers on various questions including: Who are the key players in WealthTech? What is fueling its exponential growth? What are the key technologies behind WealthTech? How do regulators respond? What are the risks? What is the reaction of incumbent players? This book not only seeks to answer these questions but also touches on a series of related topics: • Get up to speed on the latest industry developments • Understand the driving forces behind the rise of WealthTech • Realize the depth and breadth of WealthTech • Discover how investors react to the growth in WealthTech • Learn how regulators influence the evolution of WealthTech business models • Examine the market dynamics of the WealthTech revolution • Grasp the industry’s potential and its effects on connected sectors • Build acumen on investment and entrepreneurial opportunities A unique product for the market place Digital transformation is creating game-changing opportunities and disruptions across industries and businesses. One industry where these game-changing opportunities will have profound impacts is wealth and asset management. For generations, wealth and asset management was a privileged service provided to co-operations and wealthy individuals. The informational advantages that wealth managers held vis-a -vis their clients provided a key competitive differentiator. In the current digital transformation climate, this differentiator is vanishing and the setting is changing. A top priority on the agenda for any wealth and asset manager must therefore be how to respond and prepare for the ramifications of this fast changing business environment. This book (one of the first to be published in this area) will provide the reader with a head start in adapting to this new digital environment. |
| asset management data model: Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023) Nadeem Akhtar, Azah Kamilah Draman, Mohd Faizal Abdollah, 2023-07-25 This is an open access book.The 3rd International Conference on Public Management and Intelligent Society(PMIS 2023) will be held on March 10-12, 2023 in Shanghai, China. PMIS 2021 and PMIS 2022 have been successfully held in the last 2 years, providing an academic exchange platform for participants from all over the world. The conference discussed the latest topics in the field of public management and intelligent society, and the wonderful presentations were given by invited distinguished speakers and praised by scholars. Building an intelligent society and studying public management have always been a leading and hot issue. PMIS 2023 will focus on public management in an intelligent society, technological innovation in an intelligent society and advanced intelligent transportation system to discuss further. The aim of PMIS 2023 is to bring together innovative academics and industrial experts in the field of Public Management and Intelligent Society to a common forum. The primary goal to promote research and developmental activities and another goal is to promote scientific information interchange between researchers, developers, students, and practitioners in related fields. |
| asset management data model: Data Modeling Essentials Graeme Simsion, Graham Witt, 2004-12-03 Data Modeling Essentials, Third Edition, covers the basics of data modeling while focusing on developing a facility in techniques, rather than a simple familiarization with the rules. In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice. This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises. This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective. - Thorough coverage of the fundamentals and relevant theory - Recognition and support for the creative side of the process - Expanded coverage of applied data modeling includes new chapters on logical and physical database design - New material describing a powerful technique for model verification - Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict |
| asset management data model: 15th WCEAM Proceedings João Onofre Pereira Pinto, Marcio Luiz Magri Kimpara, Renata Rezende Reis, Turuna Seecharan, Belle R. Upadhyaya, Joe Amadi-Echendu, 2022-03-24 This book gathers selected peer-reviewed papers from the 15th World Congress on Engineering Asset Management (WCEAM), which was hosted by The Federal University of Mato Grosso do Sul Campo Grande, Brazil, from 15–-18 August 2021 This book covers a wide range of topics in engineering asset management, including: strategy and standards; sustainability and resiliency; servitisation and Industry 4.0 business models; asset information systems; and asset management decision-making. The breadth and depth of these state-of-the-art, comprehensive proceedings make them an excellent resource for asset management practitioners, researchers, and academics, as well as undergraduate and postgraduate students. |
| asset management data model: Data Management courseware based on CDMP Fundamentals Alliance BV And More Group BV, 1970-01-01 Besides the courseware publication (ISBN: 9789401811491), you are advised to obtain the DAMA DMBOK publication (ISBN: 9781634622349). Optionally, you can use the publication Data management: a gentle introduction (ISBN: 9789401805506) as inspiration for examples and quotes about the field of data management. This material is intended to prepare participants for the CDMP exam by DAMA International. The courseware can only be ordered by partners and is based on the current version of the DAMA DMBOK. The material will be updated when new versions of DMBOK are published. DAMA DMBOK is the industry reference for data management. It is published by DAMA International and is currently in its second version. The DMBOK is developed by professionals and can be seen as a collection of best practices. The domain of data management is divided into functional areas which are discussed in terms of definitions (what is it), goals (what are we trying to achieve), steps (what are typical activities), inputs/outputs, and participating roles. Developing and sustaining an effective data management function is far from an easy task. The DMBOK framework is adopted by many organizations as the foundation for their data management function: standardized language and good practices speed up the learning process. After the training, you have an overview of the field of data management, its terminology, and current best practices. |
| asset management data model: Digital Asset Management David Austerberry, 2006 David Austerberry presents the business case for digital asset management systems, demystifies some assumptions regarding the technology and provides a thorough introduction to the system components required, such as indexing, searching, middleware, database and storage systems.--BOOK JACKET. |
| asset management data model: Life Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision Robby Caspeele, Luc Taerwe, Dan M. Frangopol, 2018-10-15 This volume contains the papers presented at IALCCE2018, the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE2018), held in Ghent, Belgium, October 28-31, 2018. It consists of a book of extended abstracts and a USB device with full papers including the Fazlur R. Khan lecture, 8 keynote lectures, and 390 technical papers from all over the world. Contributions relate to design, inspection, assessment, maintenance or optimization in the framework of life-cycle analysis of civil engineering structures and infrastructure systems. Life-cycle aspects that are developed and discussed range from structural safety and durability to sustainability, serviceability, robustness and resilience. Applications relate to buildings, bridges and viaducts, highways and runways, tunnels and underground structures, off-shore and marine structures, dams and hydraulic structures, prefabricated design, infrastructure systems, etc. During the IALCCE2018 conference a particular focus is put on the cross-fertilization between different sub-areas of expertise and the development of an overall vision for life-cycle analysis in civil engineering. The aim of the editors is to provide a valuable source of cutting edge information for anyone interested in life-cycle analysis and assessment in civil engineering, including researchers, practising engineers, consultants, contractors, decision makers and representatives from local authorities. |
| asset management data model: Innovations in Smart Cities Applications Volume 7 Mohamed Ben Ahmed, |
| asset management data model: Value Based and Intelligent Asset Management Adolfo Crespo Márquez, Marco Macchi, Ajith Kumar Parlikad, 2019-06-29 The fundamental motivation of this book is to contribute to the future advancement of Asset Management in the context of industrial plants and infrastructures. The book aims to foster a future perspective that takes advantage of value-based and intelligent asset management in order to make a step forward with respect to the evolution observed nowadays. Indeed, the current understanding of asset management is primarily supported by well-known standards. Nonetheless, asset management is still a young discipline and the knowledge developed by industry and academia is not set in stone yet. Furthermore, current trends in new organizational concepts and technologies lead to an evolutionary path in the field. Therefore, this book aims to discuss this evolutionary path, starting first of all from the consolidated theory, then moving forward to discuss: • The strategic understanding of value-based asset management in a company; • An operational definition of value, as a concept on the background of value-based asset management; • The identification of intelligent asset management, with the aim to frame a set of “tools” recommended to support the asset-related decision-making process over the asset lifecycle; • The emergence of new technologies such as cyber physical systems and digital twins, and the implications of this on asset management. |
| asset management data model: Proceedings of the 10th World Congress on Engineering Asset Management (WCEAM 2015) Kari T. Koskinen, Helena Kortelainen, Jussi Aaltonen, Teuvo Uusitalo, Kari Komonen, Joseph Mathew, Jouko Laitinen, 2016-03-25 This book comprises refereed papers from the 10th World Congress on Engineering Asset Management (WCEAM 2015), held in Tampere, Finland in September 2015. These proceedings include a compilation of state-of-the-art papers covering a comprehensive range of subjects equally relevant to business managers and engineering professionals alike. With a focus on various aspects of engineering asset management ranging from strategic level issues to detail-level machine health issues, these papers address both industry and public sector concerns and issues, as well as advanced academic research. Proceedings of the WCEAM 2015 is an excellent reference and resource for asset management practitioners, researchers and academics, as well as undergraduate and postgraduate students at tertiary institutions or in the industry. |
| asset management data model: Asset Intelligence through Integration and Interoperability and Contemporary Vibration Engineering Technologies Joseph Mathew, C.W. Lim, Lin Ma, Don Sands, Michael E. Cholette, Pietro Borghesani, 2018-11-11 These proceedings include a collection of papers on a range of topics presented at the 12th World Congress on Engineering Asset Management (WCEAM) in Brisbane, 2 – 4 August 2017. Effective strategies are required for managing complex engineering assets such as built environments, infrastructure, plants, equipment, hardware systems and components. Following the release of the ISO 5500x set of standards in 2014, the 12th WCEAM addressed important issues covering all aspects of engineering asset management across various sectors including health. The topics discussed by the congress delegates are grouped into a number of tracks, including strategies for investment and divestment of assets, operations and maintenance of assets, assessment of assets’ health conditions, risk and vulnerability, technologies, and systems for management of assets, standards, education, training and certification. |
| asset management data model: Big Data – BigData 2022 Bo Hu, Yunni Xia, Yiwen Zhang, Liang-Jie Zhang, 2022-12-09 This book constitutes the proceedings of the 11th International Conference on Big Data, BigData 2022, held as part of the Services Conference Federation, SCF 2022, held in Honolulu, HI, USA, in December 2022. The 4 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 16 submissions. The 2022 International Congress on Big Data (BigData 2022) aims to provide an international forum that formally explores various business insights of all kinds of value-added services. Big Data is a key enabler of exploring business insights and economics of services. |
| asset management data model: A Study Guide to Service Catalogue from the Principles of ITIL V3 Hank Marquis, APMG-International, 2010 IT services are prevalent throughout virtually all businesses. Most enterprises and many government functions are totally dependent upon reliable and responsive IT services to underpin vital business, community and social functions. IT services have become mainstream and managing them to deliver value it the core message of ITIL V3, and the emphasis in ITIL V3 on service catalogue management is a direct result of the growing requirement for business and IT to work together sharing data, information and knowledge about demand for services, service capabilities and patterns of business activity. The Service Catalogue Management process is now a very important management field complete with its own terminology and vital concepts. This study guide outlines the concepts and principles underlying the service catalogue; discusses a project plan approach and reporting considerations; describes the value of a sound business case and the key relationships and touch points in the service catalogue management process. |
| asset management data model: Engineering Asset Management and Infrastructure Sustainability Joseph Mathew, Lin Ma, Andy Tan, Margot Weijnen, Jay Lee, 2012-05-11 Engineering Asset Management 2010 represents state-of-the art trends and developments in the emerging field of engineering asset management as presented at the Fifth World Congress on Engineering Asset Management (WCEAM). The proceedings of the WCEAM 2010 is an excellent reference for practitioners, researchers and students in the multidisciplinary field of asset management, covering topics such as: Asset condition monitoring and intelligent maintenance Asset data warehousing, data mining and fusion Asset performance and level-of-service models Design and life-cycle integrity of physical assets Education and training in asset management Engineering standards in asset management Fault diagnosis and prognostics Financial analysis methods for physical assets Human dimensions in integrated asset management Information quality management Information systems and knowledge management Intelligent sensors and devices Maintenance strategies in asset management Optimisation decisions in asset management Risk management in asset management Strategic asset management Sustainability in asset management |
| asset management data model: AI Factory Ramin Karim, Diego Galar, Uday Kumar, 2023-05-24 Presents compendium of methodologies and technologies in industrial AI and digitalization Illustrates sensor to actuation approach showing complete cycle, that defines and differences AI and digitalization concept Covers a broad range of academic and industrial issues within the field of asset management Discusses impact of Industry 4.0 in other sectors Includes a dedicated chapter on real-time case studies |
| asset management data model: Optimum Decision Making in Asset Management Carnero, María Carmen, González-Prida, Vicente, 2016-08-24 Asset management is becoming increasingly important to an organization’s strategy, given its effects on cost, production, and quality. No matter the sector, important decisions are made based on techniques and theories that are thought to optimize results; asset management models and techniques could help maximize effectiveness while reducing risk. Optimum Decision Making in Asset Management posits that effective decision making can be augmented by asset management based on mathematical techniques and models. Resolving the problems associated with minimizing uncertainty, this publication outlines a myriad of methodologies, procedures, case studies, and management tools that can help any organization achieve world-class maintenance. This book is ideal for managers, manufacturing engineers, programmers, academics, and advanced management students. |
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