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  • VUCA and Other Analytics in Business Resilience
    VUCA and Other Analytics in Business Resilience

    Company executives need strategic flexibility in VUCA to maintain an advantage alongside business analytics, helping them achieve a competitive edge by providing timely insights, optimizing business processes, and generating growth and innovation opportunities. Strategic questions arise as firms begin their business analytics programmes, and VUCA and Other Analytics in Business Resilience brings together specialists from different disciplines and continents to provide answers.The chapters discuss organizational justice, sustainable HR, machine learning, and more, providing future roadmaps to minimise disruption during occurrences like the COVID-19-related worldwide catastrophe and the ramifications for managers and policymakers. Emerald Studies in Finance, Insurance, And Risk Management provides a platform for authors to explore, analyse and discuss current and new financial models and theories, and engage with innovative research on an international scale.Subjects of interest may include banking, accounting, auditing, compliance, sustainability, behaviour, management, and business economics.

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  • VUCA and Other Analytics in Business Resilience
    VUCA and Other Analytics in Business Resilience

    Company executives need strategic flexibility in VUCA to maintain an advantage alongside business analytics, helping them achieve a competitive edge by providing timely insights, optimizing business processes, and generating growth and innovation opportunities. Strategic questions arise as firms begin their business analytics programmes, and VUCA and Other Analytics in Business Resilience brings together specialists from different disciplines and continents to provide answers.The chapters discuss descriptive/diagnostic, predictive, and prescriptive analytics tools and how they might be used to investigate 'black swan' occurrences like the COVID-19-related worldwide catastrophe and the ramifications for managers and policymakers. Emerald Studies in Finance, Insurance, And Risk Management provides a platform for authors to explore, analyse and discuss current and new financial models and theories, and engage with innovative research on an international scale.Subjects of interest may include banking, accounting, auditing, compliance, sustainability, behaviour, management, and business economics.

    Price: 85.00 £ | Shipping*: 0.00 £
  • Data Analytics in Marketing, Entrepreneurship, and Innovation
    Data Analytics in Marketing, Entrepreneurship, and Innovation

    Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences.Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics.It features case studies that provide realistic examples of applications.This multifaceted examination of data analytics looks at: Business analyticsApplying predictive analytics Using discrete choice analysis for decision-making Marketing and customer analyticsDeveloping new productsTechnopreneurshipDisruptive versus incremental innovationThe book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing.Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery.Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques.Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.

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  • Business Models : Innovation, Digital Transformation, and Analytics
    Business Models : Innovation, Digital Transformation, and Analytics

    Since the beginning of time, running a business has involved using logic by which the business operates.This logic is called the business model in management science, which increasingly is focusing on issues surrounding business models.Research trends related to business models include value creation, value chain operationalization, and social and ecological aspects, as well as innovation and digital transformation.Business Models: Innovation, Digital Transformation, and Analytics examines how innovation, digital transformation, and the composition of value affect the existence and development of business models.The book starts by addressing the conceptual development of business models and by discussing the essence of innovation in those models.Chapters in the book investigate how: Business models can analyze digital transformation scenarios Individual business model elements effect selected performance measures as well as how the elements are significant for the enterprise value composition The environment effects the profitability of the high-growth enterprise business models Employer branding business models are perceived by the generation Z workforce To implement responsible business models in the enterprise Cyber risk is captured in business models Decision algorithms are important to business analyticsThis book is a compendium of knowledge about the use of business models in the context of innovative activities, digital transformation, and value composition.It attempts to combine the theory and practice and offers a look at business models currently used in companies, especially high-growth enterprises, in various countries of the world and indicates the prospects for their development.

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  • Are Instagram analytics apps legal?

    Yes, Instagram analytics apps are legal as long as they comply with Instagram's terms of service and data privacy regulations. These apps provide users with insights and data about their Instagram account performance, such as follower growth, engagement metrics, and audience demographics. It is important to choose a reputable analytics app that prioritizes user privacy and data security to ensure compliance with legal requirements.

  • Where can one study Biomedical Analytics?

    One can study Biomedical Analytics at various universities and colleges that offer programs in health informatics, bioinformatics, or biomedical data science. Some well-known institutions that offer programs in Biomedical Analytics include Stanford University, Harvard University, Johns Hopkins University, and the University of California, Los Angeles. Additionally, there are online programs and professional certifications available for those looking to specialize in Biomedical Analytics.

  • How can I access external YouTube analytics?

    To access external YouTube analytics, you can use YouTube's Analytics API. This API allows you to retrieve data and metrics from your YouTube channel and videos programmatically. You will need to set up a project in the Google Developers Console, obtain API credentials, and then use these credentials to make requests to the Analytics API. This will allow you to access detailed analytics data such as views, watch time, and audience demographics for your YouTube content.

  • What is the question for evaluation in Google Analytics?

    The question for evaluation in Google Analytics is typically focused on understanding user behavior and website performance. It could be something like "What are the top pages on my website in terms of traffic and engagement?" or "How are users finding my website and what are the most effective acquisition channels?" These questions help businesses and website owners to analyze and optimize their online presence for better performance and user experience.

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  • Advances in Cyber Security and Intelligent Analytics
    Advances in Cyber Security and Intelligent Analytics

    We live in a digital world, where we use digital tools and smart devices to communicate over the Internet.In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data.Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers.Therefore, we need modern systems capable of handling and managing data efficiently.In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms.Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second.However, the distributed computing paradigms face critical challenges, including network management and cyber security.We have witnessed the development of various networking models—IoT, SDN, and ICN—to support modern systems requirements.However, they are undergoing rapid changes and need special attention.The main issue faced by these paradigms is that traditional solutions cannot be directly applied to address the challenges.Therefore, there is a significant need to develop improved network management and cyber security solutions.To this end, this book highlights the challenges faced by emerging paradigms and presents the recent developments made to address the challenges.More specifically, it presents a detailed study on security issues in distributed computing environments and their possible solutions, followed by applications of medical IoT, deep learning, IoV, healthcare, etc.

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  • Supply Chain Finance : Mechanisms, Risk Analytics, and Technology
    Supply Chain Finance : Mechanisms, Risk Analytics, and Technology

    As global supply chains become more complex, the need for expertise in their financial aspects grows.This book aims to equip students and professionals with the knowledge to navigate these complexities, ensuring efficient and resilient financial supply chain operations.It provides an in-depth exploration into the intricate and constantly evolving realm of supply chain finance.By merging key concepts, major mechanisms, hands-on risk analytics, and the latest technology trends, this book offers a seamless and comprehensive examination of the topic, grounded in the author's twenty years of academic research and hands-on experience.Students in supply chain management will gain a thorough understanding of the financial elements that are integral to modern supply chains, including the importance of liquidity, the role of financial institutions, and the optimization of cash flows within the supply chain ecosystem.Definitions will be used throughout the text to elucidate financial terminology that may be unfamiliar to management students.The instructor’s manual will include PowerPoint slides, exercises, and quizzes to assess student comprehension and progress. This textbook will serve as the primary resource for understanding the financial dimensions of supply chains.

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  • Inventory Analytics : Prescriptive Analytics in Supply Chains
    Inventory Analytics : Prescriptive Analytics in Supply Chains

    This textbook provides a practice-oriented introduction into Analytics-based inventory management in complex supply chains.In the context of Business Analytics, we concentrate on Prescriptive Analytics.In addition to standard single-level inventory models also multi-level approaches for the optimal allocation of safety inventory are presented.Moreover, dynamic lot sizing problems under random demand and random yield and their relationship to Material Requirements Planning (MRP) are discussed.The models and algorithms are illustrated with the help of numerous examples. The book has been written for students of Supply Chain Management and Operations Management as well as for practitioners who are confronted with inventory management in their daily work.

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  • Data Analytics Initiatives : Managing Analytics for Success
    Data Analytics Initiatives : Managing Analytics for Success

    The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives.But how can this complex work be categorized? What makes it so complex?Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different.At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects.Describing these commonalities helps to develop a conceptual understanding of analytical work.However, features specific to each initiative affects the entire analytics project lifecycle.Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure. In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges.The book also presents examples of questions that could be asked of relevant people to analyse an analytics project.These questions help to position properly the project and to find commonalities and general project challenges.

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  • Can someone explain to me what Google Analytics is?

    Google Analytics is a web analytics service offered by Google that allows website owners to track and analyze their website traffic. It provides valuable insights into how users interact with a website, including information about the number of visitors, their demographics, the pages they visit, and how they found the website. This data can help website owners make informed decisions about their marketing strategies, content, and user experience to improve their website's performance. Overall, Google Analytics is a powerful tool for understanding and optimizing website traffic.

  • How can the Google Analytics cookie be a first-party cookie?

    The Google Analytics cookie can be a first-party cookie because it is set by the website domain that the user is visiting. When a user visits a website that uses Google Analytics, the website sets the Google Analytics cookie on the user's browser. This means that the cookie is considered a first-party cookie because it is set by the same domain that the user is interacting with. As a result, the cookie can be used to track and analyze user behavior on that specific website.

  • How can one use plausible analytics with a web app on a server?

    Plausible analytics can be used with a web app on a server by integrating the Plausible tracking code into the web app's codebase. This tracking code will then collect data on user interactions and behavior on the web app. The data collected can be analyzed to gain insights into user engagement, popular features, and areas for improvement. By using Plausible analytics, developers can make data-driven decisions to optimize the web app for better user experience and performance.

  • Do you know what the difference is between the study programs Biomedical Analytics and Medical Biology?

    The study program Biomedical Analytics focuses on the use of data analysis and technology to understand biological systems and medical processes. It involves the application of computational and statistical methods to analyze biological data and make informed decisions in healthcare and biomedical research. On the other hand, Medical Biology is a broader field that encompasses the study of living organisms, their functions, and interactions at the molecular, cellular, and organismal levels. It also includes the study of diseases, genetics, and the development of new medical treatments. In summary, Biomedical Analytics is more focused on data analysis and technology in the context of biomedical research and healthcare, while Medical Biology covers a wider range of biological and medical topics.

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