This textbook provides guidance to both students and practitioners of enterprise architecture (EA) on how to develop and maintain enterprise models. Rather than providing yet another list of EA notations and frameworks from A to Z, it focuses on methods to perform such tasks. The problem of EA maintenance, named Enterprise Cartography, is an important aspect addressed in this book because EA is a never ending challenge that increases as the organization transformations pace also increases. The long time perspective also entails the evolution of architectural frameworks and notations, something that does not occur when developing new models. Thus, a catalogue of patterns, principles and methods is presented to develop and maintain EA models and views. After a general introduction to the book in chapter 1, chapter 2 presents basic concepts for EA modeling. Chapter 3 further details the set of EA concepts needed to present the patterns, and principles, which are subsequently introduced in chapter 4. Next, chapter 5 describes enterprise cartography concepts and principles. The remaining book then turns to techniques and methodologies. In chapter 6 an EA development method is summarized. In chapter 7 an enterprise strategy design approach is proposed, while in chapter 8 a business process design methodology is described. Chapters 9 and 10 focus on information architecture and information systems architecture design approaches, including information systems architecture planning and application portfolio management. Eventually, chapter 11 describes a method for enterprise cartography (EC) design. Last not least, several case studies on EA and EC are proposed in the last chapter.

While good data is an enterprise asset, bad data is an enterprise liability. Data governance enables you to effectively and proactively manage data assets throughout the enterprise by providing guidance in the form of policies, standards, processes and rules and defining roles and responsibilities outlining who will do what, with respect to data. While implementing data governance is not rocket science, it is not a simple exercise. There is a lot confusion around what data governance is, and a lot of challenges in the implementation of data governance. Data governance is not a project or a one-off exercise but a journey that involves a significant amount of effort, time and investment and cultural change and a number of factors to take into consideration to achieve and sustain data governance success. Data Governance Success: Growing and Sustaining Data Governance is the third and final book in the Data Governance series and discusses the following: * Data governance perceptions and challenges * Key considerations when implementing data governance to achieve and sustain success* Strategy and data governance* Different data governance maturity frameworks* Data governance - people and process elements* Data governance metrics This book shares the combined knowledge related to data and data governance that the author has gained over the years of working in different industrial and research programs and projects associated with data, processes, and technologies and unique perspectives of Thought Leaders and Data Experts through Interviews conducted. This book will be highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge to support and succeed in data governance implementations. This book is technology agnostic and contains a balance of concepts and examples and illustrations making it easy for the readers to understand and relate to their own specific data projects.

Software systems that used to be relatively autonomous entities such as e.g. accounting systems, order-entry systems etc. are now interlinked in large networks comprising extensive information infrastructures. What earlier used to be stand-alone proprietary systems are now for the most part replaced by more or less standardized interdependent systems that form large networks of production and use. Organizations have to make decisions about what office suite to purchase? The easiest option is to continuously upgrade the existing office suite to the latest version, but the battle between WordPerfect and Microsoft Word demonstrated that the choice is not obvious. What instant messenger network to join for global communication? Preferably the one most colleagues and friends use; AOL Instant Messenger, Microsoft Messenger, and ICQ represent three satisfactory, but disjunctive alternatives. Similarly organizations abandon their portfolio of homegrown IT systems and replace them with a single Enterprise Resource Planning (ERP) system. Several ERP alternatives exist on the market, but which is the right one for you? The argumentation and rationale behind these considerations are obviously related to the technological and social networks we are embedded in, but it is not always easy to specify how.
Networked Information Technologies: Diffusion and Adoption offers contributions from academics and practitioners who study networked information systems from a diffusion and adoption point of view. Themes related to the conceptualisation of diffusion and adoption of networked information systems are discussed along with studies of the diffusion of networked information systems in public sector institutions and private businesses.
This volume contains the edited proceedings of the IFIP Conference on The Diffusion and Adoption of Networked Information Technologies, which was sponsored by the International Federation for Information Processing (IFIP) Working Group 8.6 and held in Copenhagen, Denmark in October 2003.

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

This book offers state-of-the-art descriptions of intelligent service innovations in industry, supported by novel scientific approaches. It gathers findings presented at the 3rd Intelligent Services Summit, which took place in Zurich in September 2020, and chiefly focused on the design and application of Digital Twin as an enabler for business development in the field of smart services. Divided into three parts, the book addresses the challenges involved in the successful development and implementation of smart services for industry and science, ranging from data management to product design and lifecycle management. The four main aspects covered are industrial challenges, value system design (how to integrate resources into service ecosystems to create value), value creation through value proposition (how to create value for ecosystem actors), and value capture (how to create value for ecosystem businesses). Given its scope, the book offers an essential guide for practitioners and advanced students alike.

This book addresses many of the gaps in how industry and academia are currently tackling problems associated with big data. It introduces novel concepts, describes the end-to-end process, and connects the various pieces of the puzzle to offer a holistic view. In addition, it explains important concepts for a wide audience, using accessible language, diagrams, examples and analogies to do so. The book is intended for readers working in industry who want to expand their knowledge or pursue a related degree, and employs an industry-centered perspective.

O'Brien's Introduction to Information Systems 16e reflects the contemporary use of enterprise-wide business systems. New real-world case studies continue to correspond with this industry reality. The text's focus is on teaching the future manager the potential effect on business of the most current IT technologies such as the Internet, Intranets, and Extranets for enterprise collaboration, and how IT contributes to competitive advantage, reengineering business processes, problem solving, and decision-making. The benchmark text for the syllabus organized by technology (a week on databases, a week on networks, a week on systems development, etc.) taught from a managerial perspective. O'Brien defines technology and then explains how companies use the technology to improve performance. Real world cases finalize the explanation.

Professional data management is the foundation for the successful digital transformation of traditional companies. Unfortunately, many companies fail to implement data governance because they do not fully understand the complexity of the challenge (organizational structure, employee empowerment, change management, etc.) and therefore do not include all aspects in the planning and implementation of their data governance. This book explains the driving role that a responsive data organization can play in a company's digital transformation. Using proven process models, the book takes readers from the basics, through planning and implementation, to regular operations and measuring the success of data governance. All the important decision points are highlighted, and the advantages and disadvantages are discussed in order to identify digitization potential, implement it in the company, and develop customized data governance. The book will serve as a useful guide for interested newcomers as well as for experienced managers.

Sustainability requires companies to develop in an economically, environmentally and socially sustainable manner. Corporate sustainable development in turn requires movement towards cleaner production. In order to recognize the potential from cleaner production reduced costs and fewer environmental impacts through the reduced use of materials environmental management accounting (EMA) is a necessary information management tool.

Environmental Management Accounting for Cleaner Production reveals a set of tools for companies to collect, evaluate and interpret the information they need to estimate their potential to use cleaner production to realize cost savings and to make the best decisions about the available cleaner production options. EMA is therefore the key for driving environmental progress, cost savings, increased competitiveness and corporate sustainability through the means of cleaner production."

This book constitutes a selection of the best papers from the 15th International Conference on Business Excellence, Digital Economy and New Value Creation, ICBE 2021, held in Bucharest, Romania, in March 2021. This book is a collection of research findings and perspectives related to the digital economy and new value creation, led by the set of improvements and changes in the economic, societal and technological structures and processes towards the effort of reaching the sustainability goals.

This book is a review of the analytical methods required in most of the quantitative courses taught at MBA programs. Students with no technical background, or who have not studied mathematics since college or even earlier, may easily feel overwhelmed by the mathematical formalism that is typical of economics and finance courses. These students will benefit from a concise and focused review of the analytical tools that will become a necessary skill in their MBA classes. The objective of this book is to present the essential quantitative concepts and methods in a self-contained, non-technical, and intuitive way.

This book projects a futuristic scenario that is more existent than they have been at any time earlier. To be conscious of the bursting prospective of IoT, it has to be amalgamated with AI technologies. Predictive and advanced analysis can be made based on the data collected, discovered and analyzed. To achieve all these compatibility, complexity, legal and ethical issues arise due to automation of connected components and gadgets of widespread companies across the globe. While these are a few examples of issues, the authors' intention in editing this book is to offer concepts of integrating AI with IoT in a precise and clear manner to the research community. In editing this book, the authors' attempt is to provide novel advances and applications to address the challenge of continually discovering patterns for IoT by covering various aspects of implementing AI techniques to make IoT solutions smarter. The only way to remain pace with this data generated by the IoT and acquire the concealed acquaintance it encloses is to employ AI as the eventual catalyst for IoT. IoT together with AI is more than an inclination or existence; it will develop into a paradigm. It helps those researchers who have an interest in this field to keep insight into different concepts and their importance for applications in real life. This has been done to make the edited book more flexible and to stimulate further interest in topics. All these motivated the authors toward integrating AI in achieving smarter IoT. The authors believe that their effort can make this collection interesting and highly attract the student pursuing pre-research, research and even master in multidisciplinary domain.

Were you looking for the book with access to MyLab Math Global? This product is the book alone and does NOT come with access to MyLab Math Global. Students, if MyLab Math Global is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyLab Math Global should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. There's no doubt that a manager's job is getting tougher. Do it better, do it faster, do it cheaper are the pressures every manager faces. And at the heart of every manager's job is decision-making: deciding what to do and how to do it. This well-respected text looks at how quantitative analysis techniques can be used effectively to support such decision making. As a manager, developing a good understanding of the quantitative analysis techniques at your disposal is crucial. Knowing how, and when, to use them and what their results really mean can be the difference between making a good or bad decision and, ultimately, between business success and failure. Appealing both to students on introductory-level courses and to MBA and postgraduate students, this internationally successful text provides an accessible introduction to a subject area that students often find difficult. Quantitative Analysis for Decision Makers (formerly known as Quantitative Methods for Decision Makers) helps students to understand the relevance of quantitative methods of analysis to management decision-making by relating techniques directly to real-life business decisions in public and private sector organisations and focuses on developing appropriate skills and understanding of how the techniques fit into the wider management process. Key features: The use of real data sets to show how analytical techniques are used in practice "QADM in Action" case studies illustrating how organisations benefit from the use of analytical techniques Articles from the Financial Times illustrating the use of such techniques in a variety of business settings Fully worked examples and exercises supported by Excel data sets Student Progress Check activities in each chapter with solutions A 300+ page Tutors Solutions Manual

Cases on Information Technology and Organizational Politics and Culture documents real-life cases describing issues, challenges, and solutions related to information technology, and how it affects organizational politics and culture. The cases included in this book cover a wide variety of topics, such as: an integrated online library resources automation project, IT within a government agency, the politics of information management, and many others. ""Cases on Information Technology and Organizational Politics and Culture"" provides a much needed understanding of how management can deal with the impact of politics and culture on the overall utilization of information technology within an organization. Lessons learned from these cases are very instrumental in providing a better understanding of the issues and challenges involved in managing information technology, and its impact on organizational politics and cultures.

This book examines strategic executive decision-making. Using data collected over a seven-year period, the author describes how some 1,500 executives actually do make strategic decisions--and how reality differs substantially from theories about executive decision-making. The author identifies and explains the limitations of much of the current research in strategic decision-making. He then offers a rigorous alternative that reflects what actually happens when executives grapple with strategic decisions involving joint ventures, market entry, diversification, acquisitions, project selection, and long-term goals. Management Review This groundbreaking contribution to business literature examines executive decisionmaking behavior concerning corporate and competitive business strategy. In contrast to previous studies, Strategic Executive Decisions does not offer a prescription for executive decisionmaking. Rather, with the help of extensive data collected over a seven-year period, Stahl describes how some 1500 executives actually do make strategic decisions from the executives' self reports of their own priorities, showing how reality differs substantially from existing theories widely used to explain executive decisionmaking behavior. Required reading for students of management and finance, this book offers an important new methodological alternative to existing theoretical explanations of executive decisionmaking behavior. Based on the observed difference between theory and actual practice, Stahl identifies and explains the limitations of much of the current research in strategic decisionmaking. He goes on to offer a methodologically rigorous alternative that more closely reflects what actually happens when executives grapple with key decisions involving joint ventures, market entry, diversification, acquisitions, project selection, and long-term strategic goals. The bulk of the study is devoted to a detailed analysis of executive decisionmaking in practice. Stahl shows that the only reliable means of determining how strategic decisions are made is unbiased observation of several decisions followed by calculation of what is really important to the decisionmaker. Questionnaires or interviews with the executives, Stahl demonstrates, will often produce misleading information about how a particular decision was made.

The chief financial officer (CFO) is critical to a company’s financial success. In Masters of Money, chartered accountant and entrepreneur KC Rottok Chesaina interviews 31 CFOs from South Africa’s top companies, most JSE-listed, to uncover their strategies for success.

Masters of Money goes behind the scenes and allows students, professionals, entrepreneurs and managers to learn from the best. In sharing valuable lessons – learnt over many years – these finance leaders give readers the inside track to make it in the world of business. They share insights on the key elements of an effective strategy, the power of good communication, how to lead teams effectively, why values are important in the workplace, and how to deal with crises. Their stories show the human face behind the number cruncher and give readers a glimpse of the X-factor needed to rise to the top.

Featured companies include MTN South Africa, JSE, Old Mutual, FirstRand, Capitec, Nedbank, Investec, Sanlam, Redefine Properties, Liberty, Discovery, Aspen Pharmacare, Life Healthcare, Woolworths, Pick n Pay, Massmart, Nampak, Sasol, Impala Platinum, Barloworld, Anglo American Platinum, Harmony Gold, Kumba Iron Ore, PPC, Exxaro, Tourvest, Mr Price and Nando’s.

This book presents a comprehensive collection of case studies on augmented reality and virtual realty (AR/VR) applications in various industries. Augmented reality and virtual reality are changing the business landscape, providing opportunities for businesses to offer unique services and experiences to their customers. The case studies provided in this volume explore business uses of the technology across multiple industries such as healthcare, tourism, hospitality, events, fashion, entertainment, retail, education and video gaming. The book includes solutions of different maturities as well as those from startups to large enterprises thereby providing a thorough view of how augmented reality and virtual reality can be used in business.

Enterprise Information Systems Assurance and System Security: Managerial and Technical Issues brings together authoritative authors to address one of the most pressing challenges in the IT field - how to create secure environments for the application of technology to serve future needs. This book bridges the gap between theory and practice, academia and industry, computer science and MIS. The chapters provide an integrated, holistic perspective on this complex set of challenges, supported with practical experiences of leading figures from all realms. ""Enterprise Information Systems Assurance and System Security: Managerial and Technical Issues"" provides an excellent collection for corporate executives who are charged with securing their systems and data, students studying the topic of business information security, and those who simply have an interest in this exciting topic.

With this textbook, Vaisman and Zimanyi deliver excellent coverage of data warehousing and business intelligence technologies ranging from the most basic principles to recent findings and applications. To this end, their work is structured into three parts. Part I describes "Fundamental Concepts" including conceptual and logical data warehouse design, as well as querying using MDX, DAX and SQL/OLAP. This part also covers data analytics using Power BI and Analysis Services. Part II details "Implementation and Deployment," including physical design, ETL and data warehouse design methodologies. Part III covers "Advanced Topics" and it is almost completely new in this second edition. This part includes chapters with an in-depth coverage of temporal, spatial, and mobility data warehousing. Graph data warehouses are also covered in detail using Neo4j. The last chapter extensively studies big data management and the usage of Hadoop, Spark, distributed, in-memory, columnar, NoSQL and NewSQL database systems, and data lakes in the context of analytical data processing. As a key characteristic of the book, most of the topics are presented and illustrated using application tools. Specifically, a case study based on the well-known Northwind database illustrates how the concepts presented in the book can be implemented using Microsoft Analysis Services and Power BI. All chapters have been revised and updated to the latest versions of the software tools used. KPIs and Dashboards are now also developed using DAX and Power BI, and the chapter on ETL has been expanded with the implementation of ETL processes in PostgreSQL. Review questions and exercises complement each chapter to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available online and includes electronic versions of the figures, solutions to all exercises, and a set of slides accompanying each chapter. Overall, students, practitioners and researchers alike will find this book the most comprehensive reference work on data warehouses, with key topics described in a clear and educational style. "I can only invite you to dive into the contents of the book, feeling certain that once you have completed its reading (or maybe, targeted parts of it), you will join me in expressing our gratitude to Alejandro and Esteban, for providing such a comprehensive textbook for the field of data warehousing in the first place, and for keeping it up to date with the recent developments, in this current second edition." From the foreword by Panos Vassiliadis, University of Ioannina, Greece.

This book defines and develops the concept of data capital. Using an interdisciplinary perspective, this book focuses on the key features of the data economy, systematically presenting the economic aspects of data science. The book (1) introduces an alternative interpretation on economists' observation of which capital has changed radically since the twentieth century; (2) elaborates on the composition of data capital and it as a factor of production; (3) describes morphological changes in data capital that influence its accumulation and circulation; (4) explains the rise of data capital as an underappreciated cause of phenomena from data sovereign, economic inequality, to stagnating productivity; (5) discusses hopes and challenges for industrial circles, the government and academia when an intangible wealth brought by data (and information or knowledge as well); (6) proposes the development of criteria for measuring regulating data capital in the twenty-first century for regulatory purposes by looking at the prospects for data capital and possible impact on future society. Providing the first a thorough introduction to the theory of data as capital, this book will be useful for those studying economics, data science, and business, as well as those in the financial industry who own, control, or wish to work with data resources.

This open access book provides an in-depth description of the EU project European Language Grid (ELG). Its motivation lies in the fact that Europe is a multilingual society with 24 official European Union Member State languages and dozens of additional languages including regional and minority languages. The only meaningful way to enable multilingualism and to benefit from this rich linguistic heritage is through Language Technologies (LT) including Natural Language Processing (NLP), Natural Language Understanding (NLU), Speech Technologies and language-centric Artificial Intelligence (AI) applications. The European Language Grid provides a single umbrella platform for the European LT community, including research and industry, effectively functioning as a virtual home, marketplace, showroom, and deployment centre for all services, tools, resources, products and organisations active in the field. Today the ELG cloud platform already offers access to more than 13,000 language processing tools and language resources. It enables all stakeholders to deposit, upload and deploy their technologies and datasets. The platform also supports the long-term objective of establishing digital language equality in Europe by 2030 - to create a situation in which all European languages enjoy equal technological support. This is the very first book dedicated to Language Technology and NLP platforms. Cloud technology has only recently matured enough to make the development of a platform like ELG feasible on a larger scale. The book comprehensively describes the results of the ELG project. Following an introduction, the content is divided into four main parts: (I) ELG Cloud Platform; (II) ELG Inventory of Technologies and Resources; (III) ELG Community and Initiative; and (IV) ELG Open Calls and Pilot Projects.

This book provides an understanding of innovation models and why they are important in the business context, and considers sources of innovation and how to apply business frameworks using real-world examples of innovation-led businesses. After providing a solid background to the key concepts related to innovation models, the book looks at why innovation takes place and where the sources of innovation lie, from corporate research to crowd-sourced and government-funded initiatives. Innovation models across manufacturing, services and government are explored, as well as measuring innovation, and the impact of design thinking and lean enterprise principles on innovation and sustainability-driven imperatives. Offering a truly comprehensive and global approach, Business Innovation should be core or recommended reading for advanced undergraduate, postgraduate, MBA and Executive Education students studying Innovation Management, Strategic Management and Entrepreneurship.

Agile/virtual enterprise (A/VE) is seen as a new and most advanced organizational paradigm, and is expected to serve as a vehicle towards a seamless perfect alignment of the enterprise within the market. ""Agile Virtual Enterprises: Implementation and Management Support"" addresses A/VE as a highly dynamic, reconfigurable agile network of independent enterprises sharing all resources, including knowledge, market, and customers; using specific organizational architectures that introduce the enterprises' true virtual environments.

This book explores the diverse roles that marketing can, and should, play in modern, twenty-first century technology transfer in university-industry collaborations. Using various marketing lenses, it takes readers through the challenges of technology transfer and commercialization of science-based innovations. It presents research based, but practice-focused, conclusions relating to marketing implementation at different stages of the commercialization process. The author suggests that marketing's strategic role spans the whole process from idea generation, development, valuation, customer matching and marketization. Such approaches can improve the effectiveness of public money spent on research, university-industry cooperation, and research commercialization. The book will appeal to students, university teachers and researchers in a wide range of fields including: technology management, innovation, marketing, and science commercialization. It will also be of interest to those concerned directly with the practices of university technology transfer and commercialization, such as the employees, and leaders of technology transfer offices and researcher-entrepreneurs.