| business analytics is interdisciplinary involving: International Journal of Business Analytics (IJBAN). John Wang, 2015 |
| business analytics is interdisciplinary involving: Interdisciplinary Research in Technology and Management Satyajit Chakrabarti, Ashiq A. Sakib, Souti Chattopadhyay, Sanghamitra Poddar, Anupam Bhattacharya, Malay Gangopadhyaya, 2024-05-30 IRTM 2023 We live in an inter-connected world. In the era of Industry 5.0, technology is getting embedded more and more in the way ‘we learn, live, work and play’. This progression is accelerating at a pace never seen before. Inter disciplinary and collaborative research across disciplines within the Technology domain and Management domain, and across the Technology — Management interface is opening up exciting new possibilities for solving problems whose solutions are beyond the scope of a single discipline, domain or practice, and helping to create a brave, new world. We are living in an incredible time of change. Our effort to hold such an interdisciplinary conference, in the virtual mode, apparently resonated across the academic community, as was evident from the huge response that the first ever conference on “Interdisciplinary Research in Technology and Management”, (IRTM) held in February 2021 had received from participants across many countries. This has encouraged the organizers to hold the next edition of the conference physically in Kolkata on a larger scale in the online mode. The pandemic unleashed by Covid 19 in the last two years has shaken the socio-economic foundations of countries and societies to a point where the world cannot be the same as before the pandemic. It has re-focused the world’s attention on the priority of healthcare, and healthcare infrastructure and its innovative management. Inevitably, questions have again been raised more vehemently on what kind of a world we want to live in. Environmental concerns are being pursued with renewed vigour, The urgency of developing new, robust infrastructure relevant for the new world is gaining wider consensus. By 2030, as reports suggest, cyber – physical systems, internet of things and wearable technology will be everywhere and in everything, renewable energy will power the world, and digital entertainment will take centre stage among other developments. The third edition of the conference on “Interdisciplinary Research in Technology and Management” attempts to spotlight the above concerns. The number of tracks on which papers are invited from scholars, researchers, consultants and practitioners to share their interdisciplinary research and consultative work has been enlarged. As before, the papers will be peer reviewed and authors of the selected papers will be invited to present their papers in the IRTM conference. The presentation of papers will be interspersed with Keynote Talks by eminent experts on the theme of the conference or individual domains. |
| business analytics is interdisciplinary involving: Encyclopedia of Organizational Knowledge, Administration, and Technology Khosrow-Pour D.B.A., Mehdi, 2020-09-29 For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication. |
| business analytics is interdisciplinary involving: ABNORMAL PSYCHOLOGY NARAYAN CHANGDER, 2023-12-09 THE ABNORMAL PSYCHOLOGY MCQ (MULTIPLE CHOICE QUESTIONS) SERVES AS A VALUABLE RESOURCE FOR INDIVIDUALS AIMING TO DEEPEN THEIR UNDERSTANDING OF VARIOUS COMPETITIVE EXAMS, CLASS TESTS, QUIZ COMPETITIONS, AND SIMILAR ASSESSMENTS. WITH ITS EXTENSIVE COLLECTION OF MCQS, THIS BOOK EMPOWERS YOU TO ASSESS YOUR GRASP OF THE SUBJECT MATTER AND YOUR PROFICIENCY LEVEL. BY ENGAGING WITH THESE MULTIPLE-CHOICE QUESTIONS, YOU CAN IMPROVE YOUR KNOWLEDGE OF THE SUBJECT, IDENTIFY AREAS FOR IMPROVEMENT, AND LAY A SOLID FOUNDATION. DIVE INTO THE ABNORMAL PSYCHOLOGY MCQ TO EXPAND YOUR ABNORMAL PSYCHOLOGY KNOWLEDGE AND EXCEL IN QUIZ COMPETITIONS, ACADEMIC STUDIES, OR PROFESSIONAL ENDEAVORS. THE ANSWERS TO THE QUESTIONS ARE PROVIDED AT THE END OF EACH PAGE, MAKING IT EASY FOR PARTICIPANTS TO VERIFY THEIR ANSWERS AND PREPARE EFFECTIVELY. |
| business analytics is interdisciplinary involving: Encyclopedia of Business Analytics and Optimization Wang, John, 2014-02-28 As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal. |
| business analytics is interdisciplinary involving: Applied Health Analytics and Informatics Using SAS Joseph M. Woodside, 2018-11-08 Leverage health data into insight! Applied Health Analytics and Informatics Using SAS describes health anamatics, a result of the intersection of data analytics and health informatics. Healthcare systems generate nearly a third of the world’s data, and analytics can help to eliminate medical errors, reduce readmissions, provide evidence-based care, demonstrate quality outcomes, and add cost-efficient care. This comprehensive textbook includes data analytics and health informatics concepts, along with applied experiential learning exercises and case studies using SAS Enterprise MinerTM within the healthcare industry setting. Topics covered include: Sampling and modeling health data – both structured and unstructured Exploring health data quality Developing health administration and health data assessment procedures Identifying future health trends Analyzing high-performance health data mining models Applied Health Analytics and Informatics Using SAS is intended for professionals, lifelong learners, senior-level undergraduates, graduate-level students in professional development courses, health informatics courses, health analytics courses, and specialized industry track courses. This textbook is accessible to a wide variety of backgrounds and specialty areas, including administrators, clinicians, and executives. This book is part of the SAS Press program. |
| business analytics is interdisciplinary involving: Competing on Analytics Thomas H. Davenport, Jeanne G. Harris, 2007-03-06 You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics. |
| business analytics is interdisciplinary involving: The Future of Management Education Martin R. Fellenz, Sabine Hoidn, Mairead Brady, 2022-04-07 To remain relevant, management education must reflect the realities that influence its subject matter, management, while at the same time addressing societal needs and expectations. Faced by powerful drivers of change, many of which are amplified by the immense turbulence caused by the COVID-19 pandemic in early 2020, an assessment of where management education stands and where it is going is timely. This book brings together management education scholars, practitioners, and stakeholders to identify trends and to critically analyse key challenges from their respective perspectives. They consider the requirements for providing relevant management education in the future and explore changes and opportunities around themes such as responsibility, sustainability, innovation, competitive strategy, and technological change. The different perspectives of the authors contribute distinct insights and form a fascinating kaleidoscope of reflections on the present and predictions and prescriptions for the future of management education. The result is a comprehensive volume that will be essential reading for scholars and administrators committed to the growth and development of management education. It also will be of keen interest to management educators as well as management learners who will shape and be shaped by the management education of the future. |
| business analytics is interdisciplinary involving: Application of Intelligent Systems in Multi-modal Information Analytics Vijayan Sugumaran, A. G. Sreedevi, Zheng Xu, 2022-05-07 This book provides comprehensive coverage of the latest advances and trends in information technology, science, and engineering. Specifically, it addresses a number of broad themes, including multimodal informatics, data mining, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics such as AI applications and innovations in health and education informatics; data and knowledge management; multimodal application management; and web/social media mining for multimodal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers, and professionals and a useful reference guide for newcomers to the field. This book is a compilation of the papers presented in the 4th International Conference on Multi-modal Information Analytics, held online, on April 23, 2022. |
| business analytics is interdisciplinary involving: The Support of Decision Processes with Business Intelligence and Analytics Martin Kowalczyk, 2017-08-22 In his research, Martin Kowalczyk empirically investigates the challenges of designing and establishing successful decision support with Business Intelligence and Analytics (BI&A). The results from his work elucidate organizational and individual perspectives of BI&A support in decision processes. The organizational perspective considers the processual aspects of decision making and addresses process phases, roles and their interactions. The individual perspective reflects upon decision making of human individuals including their cognition and behaviors involved in decision making. The support of managerial decision making with BI&A gains increasing priority for many businesses in their desire to achieve better decision outcomes and improved organizational performance. |
| business analytics is interdisciplinary involving: The Complete Guide to Business Analytics (Collection) Thomas H. Davenport, Babette E. Bensoussan, Craig S. Fleisher, 2012-10-14 A brand new collection of business analytics insights and actionable techniques… 3 authoritative books, now in a convenient e-format, at a great price! 3 authoritative eBooks deliver comprehensive analytics knowledge and tools for optimizing every critical business decision! Use business analytics to drive maximum value from all your business data! This unique 3 eBook package will help you harness your information, discover hidden patterns, and successfully act on what you learn. In Enterprise Analytics, analytics pioneer Tom Davenport and the world-renowned experts at the International Institute for Analytics (IIA) bring together the latest techniques, best practices, and research on large-scale analytics strategy, technology, implementation, and management. Using real-world examples, they cover everything from building better analytics organizations to gathering data; implementing predictive analytics to linking analysis with organizational performance. You'll find specific insights for optimizing supply chains, online services, marketing, fraud detection, and many other business functions; plus chapter-length case studies from healthcare, retail, and financial services. Next, in the up-to-the-minute Analysis Without Paralysis, Second Edition, Babette E. Bensoussan and Craig S. Fleisher help you succeed with analysis without getting mired in advanced math or arcane theory. They walk you through the entire business analysis process, and guide you through using 12 core tools for making better decisions about strategy and operations -- including three powerful tools covered for the first time in this new Second Edition. Then, in Business and Competitive Analysis, Fleisher and Bensoussan help you apply 24 leading business analysis models to gain deep clarity about your business environment, answer tough questions, and make tough choices. They first walk you through defining problems, avoiding pitfalls, choosing tools, and communicating results. Next, they systematically address both “classic” techniques and the most promising new approaches from economics, finance, sociology, anthropology, and the intelligence and futurist communities. For the first time, one book covers Nine Forces, Competitive Positioning, Business Model, Supply Chain Analyses, Benchmarking, McKinsey 7S, Shadowing, Product Line, Win/Loss, Strategic Relationships, Corporate Reputation, Critical Success Factors, Driving Forces, Country Risk, Technology Forecasting, War Gaming, Event/Timeline, Indications, Warning Analyses, Competitor Cash Flow, ACH, Linchpin Analyses, and more. Whether you're an executive, strategist, analyst, marketer, or operations professional, this eBook collection will help you make more effective, data-driven, profitable decisions! From world-renowned analytics and competitive/business intelligence experts Thomas H. Davenport, Babette E. Bensoussan, and Craig S. Fleisher |
| business analytics is interdisciplinary involving: Data and Analytics in Accounting Ann C. Dzuranin, Guido Geerts, Margarita Lenk, 2023-12-25 |
| business analytics is interdisciplinary involving: Applying Interdisciplinarity to Globalization, Management, Marketing, and Accountancy Science Pavlát, Vladislav, Knihová, Ladislava, Civín, Lubomír, Halík, Jaroslav, MacGregor Pelikánová, Radka, 2023-10-16 With the world becoming increasingly interconnected and complex, traditional means are no longer sufficient to address complex global issues. Scholars often struggle to navigate the intricate web of interdisciplinary research and theory. This gap in understanding leaves many academics feeling adrift in their pursuit of knowledge, unable to harness the full potential of interdisciplinary collaboration. Applying Interdisciplinarity to Globalization, Management, Marketing, and Accountancy Science offers a comprehensive and up-to-date solution to the obstacles of interdisciplinarity. It meticulously analyzes the theory and methodology of interdisciplinarity as it exists in the most relevant literature, and through a detailed examination of four vital disciplines in the applied economy, it compares and contrasts the dynamics of globalization and its reflections within these fields. Furthermore, it uncovers the hidden infrastructures supporting these disciplines and offers practical insights into applying this knowledge in research and practice. This book is an indispensable resource for scholars and educators across diverse disciplines, empowering them to embrace interdisciplinarity with confidence. |
| business analytics is interdisciplinary involving: Operations and Service Management: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2017-11-30 Organizations of all types are consistently working on new initiatives, product lines, and workflows as a way to remain competitive in the modern business environment. No matter the type of project at hand, employing the best methods for effective execution and timely completion of the task is essential to business success. Operations and Service Management: Concepts, Methodologies, Tools, and Applications is a comprehensive reference source for the latest research on business operations and production processes. It examines the need for a customer focus and highlights a range of pertinent topics such as financial performance measures, human resource development, and business analytics, this multi-volume book is ideally designed for managers, professionals, students, researchers, and academics interested in operations and service management. |
| business analytics is interdisciplinary involving: Essentials of Health Information Systems and Technology Jean A Balgrosky, 2014-08-11 As health care and public health continue to evolve, the field of Health Information Systems (HIS) has revealed an overwhelming universe of new, emerging, competing, and conflicting technologies and services. Even seasoned HIS professionals, as well as those new to the field, are often confounded by these myriad systems. Essentials of Health Information Systems and Technology unravels the mysteries of HIS by breaking these technologies down to their component parts, while articulating intricate concepts clearly and carefully in simple, reader-friendly language. The book provides a thorough yet unintimidating introduction to this complex and fascinating field. This book will provide undergraduate and early graduate students with a solid understanding not only of what is needed for a successful healthcare career in HIS, but also of the vast frontier that lies before us as we develop new tools to support improved methods of care, analytics, policy, research, and public health. Contents Include: • HIS overview • Systems and management • Biomedical informatics • Data and analytics • Research, policy, and public health • Future directions of HIS |
| business analytics is interdisciplinary involving: Business Intelligence Carlo Vercellis, 2011-08-10 Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide. |
| business analytics is interdisciplinary involving: Building a Data Culture in the Ministry of Finance Dody Dharma Hutabarat, Canrakerta, Lazuardi Zulfikar Wicaksana, Dimas Rahadian, Lysa Novita Sirait, 2022-03-02 The book is prepared as a general guide for stakeholders in the Ministry of Finance, especially the leaders, on how to lead their working units to be data-driven. In the Ministry of Finance, the volume of data grows massively. The data grow so rapidly that the Minister of Finance illustrates the condition by stating that “We, at the Ministry of Finance, are actually sitting on a large pile of data. This is a new type of mine. In digital era, the mine refers to the mine of data. However, of course they have to be the data we process and understand.” Ideally, the availability of data will encourage better formulation of policies and decision making. However, such effort is not an easy task, it is a challenging one instead. One of the main challenges in data utilization is that data culture has not been developed yet. The opportunity to optimize data utilization gets fresh air as awareness and understanding of data start to grow in some internal areas of the Ministry of Finance. Starting from the background, the book is compiled to become a guide for leaders and employees of the Ministry of Finance in building data culture in the Ministry of Finance. The book introduces cultural approach to develop and utilize data analytics skills in the Ministry of Finance. Hopefully, the book will keep being renewed in accordance with the development of science, technology, needs, and public discussion. |
| business analytics is interdisciplinary involving: Big Data Analytics Arun K. Somani, Ganesh Chandra Deka, 2017-10-30 The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers. |
| business analytics is interdisciplinary involving: Risks and Challenges of AI-Driven Finance: Bias, Ethics, and Security Kunjumuhammed, Siraj Kariyilaparambu, Madi, Hisham, Abouraia, Mahmoud, 2024-08-01 Integrating Artificial Intelligence (AI) presents immense opportunities and daunting challenges in the rapidly evolving finance landscape as AI-driven algorithms and models revolutionize decision-making and enhance efficiency, concerns about bias, ethics, and security loom. Financial institutions must navigate these complexities responsibly while leveraging AI's potential to innovate and thrive. Risks and Challenges of AI-Driven Finance: Bias, Ethics, and Security guides this dynamic environment. Written for professionals, researchers, policymakers, and students, this book comprehensively explores AI's impact on finance. It delves into the intricacies of bias in algorithms, ethical frameworks, cybersecurity, and regulatory compliance, offering actionable insights to address these critical issues. |
| business analytics is interdisciplinary involving: Essentials of Business Analytics Bhimasankaram Pochiraju, Sridhar Seshadri, 2019-07-10 This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners. The book has contributions from experts in top universities and industry. The editors have taken extreme care to ensure continuity across the chapters. The material is organized into three parts: A) Tools, B) Models and C) Applications. In Part A, the tools used by business analysts are described in detail. In Part B, these tools are applied to construct models used to solve business problems. Part C contains detailed applications in various functional areas of business and several case studies. Supporting material can be found in the appendices that develop the pre-requisites for the main text. Every chapter has a business orientation. Typically, each chapter begins with the description of business problems that are transformed into data questions; and methodology is developed to solve these questions. Data analysis is conducted using widely used software, the output and results are clearly explained at each stage of development. These are finally transformed into a business solution. The companion website provides examples, data sets and sample code for each chapter. |
| business analytics is interdisciplinary involving: Adoption of Data Analytics in Higher Education Learning and Teaching Dirk Ifenthaler, David Gibson, 2020-08-10 The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education. |
| business analytics is interdisciplinary involving: Understanding Health Information Systems for the Health Professions Jean A Balgrosky, 2019-03-19 Covering the principles of HIS planning, cost effectiveness, waste reduction, efficiency,population health management, patient engagement, and prevention, this text is designed for those who will be responsible for managing systems and information in health systems and provider organizations. |
| business analytics is interdisciplinary involving: Business Intelligence Ramesh Sharda, Dursun Delen, Efraim Turban, 2017-01-13 For courses on Business Intelligence or Decision Support Systems. A managerial approach to understanding business intelligence systems. To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice. |
| business analytics is interdisciplinary involving: Decision Intelligence Miriam O'Callaghan, 2023-04-26 Revealing the limitations of human decision-making, this book explores how Artificial Intelligence (AI) can be used to optimize decisions for improved business outcomes and efficiency, as well as looking ahead to the significant contributions Decision Intelligence (DI) can make to society and the ethical challenges it may raise. From the theories and concepts used to design autonomous intelligent agents to the technologies that power DI systems and the ways in which companies use decision-making building blocks to build DI solutions that enable businesses to democratize AI, this book presents an impressive framework to integrate artificial and human intelligence for the success of different types of business decisions. Replete with case studies on DI applications, as well as wider discussions on the social implications of the technology, Decision Intelligence: Human–Machine Integration for Decision Making appeals to both students of AI and data sciences and businesses considering DI adoption. |
| business analytics is interdisciplinary involving: Strategic System Assurance and Business Analytics P. K. Kapur, Ompal Singh, Sunil Kumar Khatri, Ajit Kumar Verma, 2020-06-19 This book systematically examines and quantifies industrial problems by assessing the complexity and safety of large systems. It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues. Through contributions from researchers working in the area of performance, management, and business analytics, it explores the development of new methods and approaches to improve business by gaining knowledge from bulk data. With system performance analytics, companies are now able to drive performance and provide actionable insights for each level and for every role using key indicators, generate mobile-enabled scorecards, time series-based analysis using charts, and dashboards. In the current dynamic environment, a viable tool known as multi-criteria decision analysis (MCDA) is increasingly being adopted to deal with complex business decisions. MCDA is an important decision support tool for analyzing goals and providing optimal solutions and alternatives. It comprises several distinct techniques, which are implemented by specialized decision-making packages. This book addresses a number of important MCDA methods, such as DEMATEL, TOPSIS, AHP, MAUT, and Intuitionistic Fuzzy MCDM, which make it possible to derive maximum utility in the area of analytics. As such, it is a valuable resource for researchers and academicians, as well as practitioners and business experts. |
| business analytics is interdisciplinary involving: Business Intelligence Success Factors Olivia Parr Rud, 2009-06-02 Over the last few decades, the growth of Business Intelligence has enabled companies to streamline many processes and expand into new markets on an unprecedented scale. New BI technologies are also enabling mass collaboration and innovation. However, implementation of these BI solutions often gives rise to new challenges. Business Intelligence Success Factors shows you how to turn those challenges into opportunities by mastering five key skills. Olivia Parr Rud shares insights gained from her two decades of experience in Business Intelligence to offer the latest practices that are emerging in organizational development. Written to help enhance your understanding of the current business climate and to provide the tools necessary to thrive in this new global economy, Business Intelligence Success Factors examines the components of chaos theory, complex adaptive systems, quantum physics, and evolutionary biology. A scientific framework for these new corporate issues helps explain why developing these key competencies are critical, given the speed of change, globalization, as well as advancements in technology and Business Intelligence. Divided into four cohesive parts, Business Intelligence Success Factors explores: The current business landscape as well as the latest scientific research: today's business realities and how and why they can lead to chaos New scientific models for viewing the global economy The five essential competencies—Communication, Collaboration, Innovation, Adaptability, and Leadership—that improve an organization's ability to leverage the new opportunities in a volatile global economy Profiles of several amazing leaders who are working to make a difference Cutting-edge research and case studies via invited contributors offering a wealth of knowledge and experience Move beyond mere survival to realize breakaway success in the global economy with the practical guidance found in Business Intelligence Success Factors. |
| business analytics is interdisciplinary involving: Interactive Visual Data Analysis Christian Tominski, Heidrun Schumann, 2020-04-01 In the age of big data, being able to make sense of data is an important key to success. Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and automatic computation to facilitate insight generation and knowledge crystallization from large and complex data. The book provides a systematic and comprehensive overview of visual, interactive, and analytical methods. It introduces criteria for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes. The reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal data, geo-spatial data, and graph data. A dedicated chapter introduces general concepts for interacting with visualizations and illustrates how modern interaction technology can facilitate the visual data analysis in many ways. Addressing today’s large and complex data, the book covers relevant automatic analytical computations to support the visual data analysis. The book also sheds light on advanced concepts for visualization in multi-display environments, user guidance during the data analysis, and progressive visual data analysis. The authors present a top-down perspective on interactive visual data analysis with a focus on concise and clean terminology. Many real-world examples and rich illustrations make the book accessible to a broad interdisciplinary audience from students, to experts in the field, to practitioners in data-intensive application domains. Features: Dedicated to the synthesis of visual, interactive, and analysis methods Systematic top-down view on visualization, interaction, and automatic analysis Broad coverage of fundamental and advanced visualization techniques Comprehensive chapter on interacting with visual representations Extensive integration of automatic computational methods Accessible portrayal of cutting-edge visual analytics technology Foreword by Jack van Wijk For more information, you can also visit the author website, where the book's figures are made available under the CC BY Open Access license. |
| business analytics is interdisciplinary involving: Data Mining and Decision Support Dunja Mladenic, Nada Lavrač, Marko Bohanec, Steve Moyle, 2012-12-06 Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area involving databases, machine learning, pattern recognition, statistics, visualization and others. Decision support focuses on developing systems to help decision-makers solve problems. Decision support provides a selection of data analysis, simulation, visualization and modeling techniques, and software tools such as decision support systems, group decision support and mediation systems, expert systems, databases and data warehouses. Independently, data mining and decision support are well-developed research areas, but until now there has been no systematic attempt to integrate them. Data Mining and Decision Support: Integration and Collaboration, written by leading researchers in the field, presents a conceptual framework, plus the methods and tools for integrating the two disciplines and for applying this technology to business problems in a collaborative setting. |
| business analytics is interdisciplinary involving: Aligning Business Strategies and Analytics Murugan Anandarajan, Teresa D. Harrison, 2018-09-27 This book examines issues related to the alignment of business strategies and analytics. Vast amounts of data are being generated, collected, stored, processed, analyzed, distributed and used at an ever-increasing rate by organizations. Simultaneously, managers must rapidly and thoroughly understand the factors driving their business. Business Analytics is an interactive process of analyzing and exploring enterprise data to find valuable insights that can be exploited for competitive advantage. However, to gain this advantage, organizations need to create a sophisticated analytical climate within which strategic decisions are made. As a result, there is a growing awareness that alignment among business strategies, business structures, and analytics are critical to effectively develop and deploy techniques to enhance an organization’s decision-making capability. In the past, the relevance and usefulness of academic research in the area of alignment is often questioned by practitioners, but this book seeks to bridge this gap. Aligning Business Strategies and Analytics: Bridging Between Theory and Practice is comprised of twelve chapters, divided into three sections. The book begins by introducing business analytics and the current gap between academic training and the needs within the business community. Chapters 2 - 5 examines how the use of cognitive computing improves financial advice, how technology is accelerating the growth of the financial advising industry, explores the application of advanced analytics to various facets of the industry and provides the context for analytics in practice. Chapters 6 - 9 offers real-world examples of how project management professionals tackle big-data challenges, explores the application of agile methodologies, discusses the operational benefits that can be gained by implementing real-time, and a case study on human capital analytics. Chapters 10 - 11 reviews the opportunities and potential shortfall and highlights how new media marketing and analytics fostered new insights. Finally the book concludes with a look at how data and analytics are playing a revolutionary role in strategy development in the chemical industry. |
| business analytics is interdisciplinary involving: Decision Intelligence For Dummies Pamela Baker, 2022-02-08 Learn to use, and not be used by, data to make more insightful decisions The availability of data and various forms of AI unlock countless possibilities for business decision makers. But what do you do when you feel pressured to cede your position in the decision-making process altogether? Decision Intelligence For Dummies pumps the brakes on the growing trend to take human beings out of the decision loop and walks you through the best way to make data-informed but human-driven decisions. The book shows you how to achieve maximum flexibility by using every available resource, and not just raw data, to make the most insightful decisions possible. In this timely book, you’ll learn to: Make data a means to an end, rather than an end in itself, by expanding your decision-making inquiries Find a new path to solid decisions that includes, but isn’t dominated, by quantitative data Measure the results of your new framework to prove its effectiveness and efficiency and expand it to a whole team or company Perfect for business leaders in technology and finance, Decision Intelligence For Dummies is ideal for anyone who recognizes that data is not the only powerful tool in your decision-making toolbox. This book shows you how to be guided, and not ruled, by the data. |
| business analytics is interdisciplinary involving: Applied Data Science Martin Braschler, Thilo Stadelmann, Kurt Stockinger, 2019-06-13 This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry. |
| business analytics is interdisciplinary involving: The Internet of Things in the Cloud Honbo Zhou, 2012-10-29 Although the Internet of Things (IoT) is a vast and dynamic territory that is evolving rapidly, there has been a need for a book that offers a holistic view of the technologies and applications of the entire IoT spectrum. Filling this void, The Internet of Things in the Cloud: A Middleware Perspective provides a comprehensive introduction to the Io |
| business analytics is interdisciplinary involving: Data Science Thinking Longbing Cao, 2018-08-17 This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective. |
| business analytics is interdisciplinary involving: Responsible AI and Analytics for an Ethical and Inclusive Digitized Society Denis Dennehy, Anastasia Griva, Nancy Pouloudi, Yogesh K. Dwivedi, Ilias Pappas, Matti Mäntymäki, 2021-08-25 This volume constitutes the proceedings of the 20th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2021, held in Galway, Ireland, in September 2021.* The total of 57 full and 8 short papers presented in these volumes were carefully reviewed and selected from 141 submissions. The papers are organized in the following topical sections: AI for Digital Transformation and Public Good; AI & Analytics Decision Making; AI Philosophy, Ethics & Governance; Privacy & Transparency in a Digitized Society; Digital Enabled Sustainable Organizations and Societies; Digital Technologies and Organizational Capabilities; Digitized Supply Chains; Customer Behavior and E-business; Blockchain; Information Systems Development; Social Media & Analytics; and Teaching & Learning. *The conference was held virtually due to the COVID-19 pandemic. |
| business analytics is interdisciplinary involving: Multivariate Analysis Jude May, 2018-07-22 When measuring a few factors on a complex test unit, it is frequently important to break down the factors all the while, as opposed to separate them and think of them as independently. This book Multivariate investigation empowers analysts to investigate the joint execution of such factors and to decide the impact of every factor within the sight of the others. This book gives understudies of every single measurable foundation with both the major and more modern aptitudes important to ace the train. To represent multivariate applications, the creator gives cases and activities in light of fifty-nine genuine informational collections from a wide assortment of logical fields. Here takes a e;strategiese; way to deal with his subject, with an accentuation on how understudies and professionals can utilize multivariate investigation, all things considered, circumstances. This book sections like: Cluster analysis; Multidimensional scaling; Correspondence analysis; Biplots. |
| business analytics is interdisciplinary involving: Analytics, Data Science, and Artificial Intelligence Ramesh Sharda, Dursun Delen, Efraim Turban, 2020-03-06 For courses in decision support systems, computerized decision-making tools, and management support systems. Market-leading guide to modern analytics, for better business decisionsAnalytics, Data Science, & Artificial Intelligence: Systems for Decision Support is the most comprehensive introduction to technologies collectively called analytics (or business analytics) and the fundamental methods, techniques, and software used to design and develop these systems. Students gain inspiration from examples of organisations that have employed analytics to make decisions, while leveraging the resources of a companion website. With six new chapters, the 11th edition marks a major reorganisation reflecting a new focus -- analytics and its enabling technologies, including AI, machine-learning, robotics, chatbots, and IoT. |
| business analytics is interdisciplinary involving: Encyclopedia of Data Science and Machine Learning Wang, John, 2023-01-20 Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians. |
| business analytics is interdisciplinary involving: Data Mining and Exploration Chong Ho Alex Yu, 2022-10-27 This book introduces both conceptual and procedural aspects of cutting-edge data science methods, such as dynamic data visualization, artificial neural networks, ensemble methods, and text mining. There are at least two unique elements that can set the book apart from its rivals. First, most students in social sciences, engineering, and business took at least one class in introductory statistics before learning data science. However, usually these courses do not discuss the similarities and differences between traditional statistics and modern data science; as a result learners are disoriented by this seemingly drastic paradigm shift. In reaction, some traditionalists reject data science altogether while some beginning data analysts employ data mining tools as a “black box”, without a comprehensive view of the foundational differences between traditional and modern methods (e.g., dichotomous thinking vs. pattern recognition, confirmation vs. exploration, single method vs. triangulation, single sample vs. cross-validation etc.). This book delineates the transition between classical methods and data science (e.g. from p value to Log Worth, from resampling to ensemble methods, from content analysis to text mining etc.). Second, this book aims to widen the learner's horizon by covering a plethora of software tools. When a technician has a hammer, every problem seems to be a nail. By the same token, many textbooks focus on a single software package only, and consequently the learner tends to fit the problem with the tool, but not the other way around. To rectify the situation, a competent analyst should be equipped with a tool set, rather than a single tool. For example, when the analyst works with crucial data in a highly regulated industry, such as pharmaceutical and banking, commercial software modules (e.g., SAS) are indispensable. For a mid-size and small company, open-source packages such as Python would come in handy. If the research goal is to create an executive summary quickly, the logical choice is rapid model comparison. If the analyst would like to explore the data by asking what-if questions, then dynamic graphing in JMP Pro is a better option. This book uses concrete examples to explain the pros and cons of various software applications. |
| business analytics is interdisciplinary involving: Genetics and Breeding for Disease Resistance of Livestock Aruna Pal, A. K. Chakravarty, 2019-10-22 Genetics and Breeding for Disease Resistance of Livestock is a solid resource that combines important information on the underlying genetic causes and governing factors for disease resistance in food animals and applications for breeding purposes. It describes genomics at each species level to help researchers and students understand disease resistance and immunology using genomics and its application in breeding for disease resistance. This useful reference makes it easy for readers to understand and undergo further research in immunology and disease resistance for livestock. It includes novel applications and research material that is ideal for students, teachers, academicians and researchers. - Presents basic principles and protocols to describe research methodologies through diagrammatic illustrations with figures, flow charts, examples, and references - Covers various disease occurrences in livestock and the methodologies available to identify the various pathogens responsible for these diseases - Includes advanced breeding techniques and practical applications |
| business analytics is interdisciplinary involving: Cognitive Social Mining Applications in Data Analytics and Forensics Haldorai, Anandakumar, Ramu, Arulmurugan, 2018-12-14 Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data. Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals. |
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
