Computing Predictive Analytics Business Intelligence And Economics
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| Author | : Cyrus F. Nourani |
| Publisher | : CRC Press |
| Total Pages | : 313 |
| Release | : 2019-06-26 |
| Genre | : Computers |
| ISBN | : 0429878710 |
This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling. Applications for management science and IT have been of interest areas for business schools and computing experts during recent years. Among the areas that are being treated are modern analytics, heterogeneous computing, business intelligence, ERP (enterprise resource planning), and decision science. Consumers have been pledging their love for data visualizations for a while now, and data is the area being explored, such as B2B and EC (E-commerce), E-business and the Intelligent Web, CRM (customer relationship management), infrastructures, and more. The digitization implications of these many new applications are described and explored in this informative volume.
| Author | : Cyrus F. Nourani |
| Publisher | : CRC Press |
| Total Pages | : 286 |
| Release | : 2021-12-22 |
| Genre | : Business & Economics |
| ISBN | : 1000400654 |
Focusing on the cutting-edge applications of AI cognitive computing from neuromorphic to quantum cognition as applied to AI business analytics, this new volume explores AI’s importance in managing cognitive processes along with ontological modeling concepts for venturing into new business frontiers. The volume presents a selection of significant new accomplishments in the areas of AI cognitive computing ranging from neurocognition perception and decision-making in the human brain—combining neurocognitive techniques and effective computing—to basic facial recognition computing models. Topics include: Agent neurocomputing techniques for facial expression recognition Computing haptic motion and ontology epistemic Characterizations of morph schemas for visual analytics Learning and perceptive computing Functional and structural neuroimaging modeling Observed links between facial recognition and affective emotional processes Interaction of cognitive and emotional processes during social decision-making Neurocognitive processing of emotional facial expressions in individuals Neurocognitive affective system for emotive robot androids Virtual reality-based affect adaptive neuromorphic computing Executive surveys indicate that cognitive adoption is very important in business strategy for success and to remain competitive. Employing cognitive-based processes provides the way to get the right information in the right hands at the right time, which is the key to winning in the digital era and to driving business value that emphasizes competitive differentiation. Several chapters of the volume address the goal of using cognitive technology to improve search capabilities, to provide personalized customer service in business and in health and wellness, and to create better workflow management. Key features: Looks at the newest frontiers on very popular AI and analytics topics Discusses new techniques for visual analytics and data filtering Shows how AI and cognitive science merges with quantum neurocognitive computing Presents ontology models with ontology preservation data filtering techniques Provides a cross-transposition on AI and digitizations for business model innovations Artificial Intelligence and Computing Logic: Cognitive Technology for AI Business Analytics is a valuable resource that informs businesses and other enterprises the value of artificial intelligence and computing logic applications.
| Author | : Subrata Das |
| Publisher | : CRC Press |
| Total Pages | : 517 |
| Release | : 2013-12-14 |
| Genre | : Business & Economics |
| ISBN | : 1439890706 |
Learn How to Properly Use the Latest Analytics Approaches in Your Organization Computational Business Analytics presents tools and techniques for descriptive, predictive, and prescriptive analytics applicable across multiple domains. Through many examples and challenging case studies from a variety of fields, practitioners easily see the connections to their own problems and can then formulate their own solution strategies. The book first covers core descriptive and inferential statistics for analytics. The author then enhances numerical statistical techniques with symbolic artificial intelligence (AI) and machine learning (ML) techniques for richer predictive and prescriptive analytics. With a special emphasis on methods that handle time and textual data, the text: Enriches principal component and factor analyses with subspace methods, such as latent semantic analyses Combines regression analyses with probabilistic graphical modeling, such as Bayesian networks Extends autoregression and survival analysis techniques with the Kalman filter, hidden Markov models, and dynamic Bayesian networks Embeds decision trees within influence diagrams Augments nearest-neighbor and k-means clustering techniques with support vector machines and neural networks These approaches are not replacements of traditional statistics-based analytics; rather, in most cases, a generalized technique can be reduced to the underlying traditional base technique under very restrictive conditions. The book shows how these enriched techniques offer efficient solutions in areas, including customer segmentation, churn prediction, credit risk assessment, fraud detection, and advertising campaigns.
| Author | : Cyrus F. Nourani |
| Publisher | : CRC Press |
| Total Pages | : 282 |
| Release | : 2017-01-06 |
| Genre | : Business & Economics |
| ISBN | : 1771885084 |
Ecosystems and Technology: Idea Generation and Content Model Processing, presents important new innovations in the area of management and computing. Innovation is the generation and application of new ideas and skills to produce new products, processes, and services that improve economic and social prosperity. This includes management and design policy decisions and encompasses innovation research, analysis, and best practice in enterprises, public and private sector service organizations, government, regional societies and economies. The book, the first volume in the Innovation Management and Computing book series, looks at technology that improves efficiency and idea generation, including systems for business, medical/health, education, and more. The book provides detailed examples to provide readers with current issues, including Venture planning for innovations New technologies supporting innovations systems Competitive business modeling Context-driven innovation modeling The generation of ideas faster The measurement of relevant data Virtual interfaces Business intelligence and content processing Predictive modeling Haptic expression and emotion recognition innovations, with applications to neurocognitive medical science This book provides a wealth of information that will be useful for IT and business professionals, educators, and students in many fields.
| Author | : Michael Minelli |
| Publisher | : John Wiley & Sons |
| Total Pages | : 230 |
| Release | : 2013-01-22 |
| Genre | : Business & Economics |
| ISBN | : 111814760X |
Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.
| Author | : Gupta, Brij B. |
| Publisher | : IGI Global |
| Total Pages | : 361 |
| Release | : 2019-09-27 |
| Genre | : Computers |
| ISBN | : 1799810844 |
In today’s modern age of information, new technologies are quickly emerging and being deployed into the field of information technology. Cloud computing is a tool that has proven to be a versatile piece of software within IT. Unfortunately, the high usage of Cloud has raised many concerns related to privacy, security, and data protection that have prevented cloud computing solutions from becoming the prevalent alternative for mission critical systems. Up-to-date research and current techniques are needed to help solve these vulnerabilities in cloud computing. Modern Principles, Practices, and Algorithms for Cloud Security is a pivotal reference source that provides vital research on the application of privacy and security in cloud computing. While highlighting topics such as chaos theory, soft computing, and cloud forensics, this publication explores present techniques and methodologies, as well as current trends in cloud protection. This book is ideally designed for IT specialists, scientists, software developers, security analysts, computer engineers, academicians, researchers, and students seeking current research on the defense of cloud services.
| Author | : Lawrence Maisel |
| Publisher | : John Wiley & Sons |
| Total Pages | : 276 |
| Release | : 2013-09-26 |
| Genre | : Business & Economics |
| ISBN | : 1118240154 |
Discover the breakthrough tool your company can use to make winning decisions This forward-thinking book addresses the emergence of predictive business analytics, how it can help redefine the way your organization operates, and many of the misconceptions that impede the adoption of this new management capability. Filled with case examples, Predictive Business Analytics defines ways in which specific industries have applied these techniques and tools and how predictive business analytics can complement other financial applications such as budgeting, forecasting, and performance reporting. Examines how predictive business analytics can help your organization understand its various drivers of performance, their relationship to future outcomes, and improve managerial decision-making Looks at how to develop new insights and understand business performance based on extensive use of data, statistical and quantitative analysis, and explanatory and predictive modeling Written for senior financial professionals, as well as general and divisional senior management Visionary and effective, Predictive Business Analytics reveals how you can use your business's skills, technologies, tools, and processes for continuous analysis of past business performance to gain forward-looking insight and drive business decisions and actions.
| Author | : Eunika Mercier-Laurent |
| Publisher | : Springer Nature |
| Total Pages | : 166 |
| Release | : 2020-07-15 |
| Genre | : Computers |
| ISBN | : 3030529037 |
This book features a selection of extended papers presented at the 6th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2018, held in Stockholm, Sweden, in July 2018, in the framework of the International Joint Conference on Artificial Intelligence, IJCAI 2018. The 11 revised and extended papers were carefully reviewed and selected for inclusion in this volume. They present new research and innovative aspects in the field of knowledge management such as machine learning, knowledge models, KM and Web, knowledge capturing and learning, and KM and AI intersections.
| Author | : Mert Damlapinar |
| Publisher | : NLITX |
| Total Pages | : 311 |
| Release | : 2022-10-07 |
| Genre | : Business & Economics |
| ISBN | : |
While you work hard building your startup, one of the biggest challenges you’ll face will be around your product’s ability to solve a big enough problem and its success in the market. Agile Analytics for Startups will help you navigate the complexity of early-stage business analytics, performance measurement, and the metrics that matter to your company. You can use the proven frameworks in this book to validate your product idea and the product/market fit, and understand your customers more granularly while you scale your business for automation. You can test and use many tools and solutions provided in the book and interact with different features of those solutions as you engage with other users of those products. This book will provide you with a step-by-step framework, examples and powerful solutions, from ideation to growth and all the way to scaling your business as you build your company with the power of analytics. -Agility is your advantage over large companies -Understand business analytics essentials and define how you will measure the success of your business early -Once you define your solution for “the problem” you tackle, validate your customer -Keep a short list of KPIs for the success of your product -Engage your customers throughout the development cycle -Product/market fit should happen before you go to market big -Keep testing your product, reiterate continuously -Know when to pivot as you modify and optimize your roadmap Be ready to speed up and maximize your output before the significant funding milestone(s)
| Author | : Ludovit Garzik |
| Publisher | : Springer Nature |
| Total Pages | : 351 |
| Release | : 2021-11-26 |
| Genre | : Business & Economics |
| ISBN | : 3030806391 |
This book places a central question: why are some regions in the world more successful in innovation than others? It aims to increase readers ́ understanding of how innovation processes are accelerated or hindered by regional characteristics. A deep dive into differences of innovation ecosystems across global regions will provide a detailed mosaic of strengths and weaknesses. The audience will also learn to assess the resources and elements of regional innovation systems and to compare and contrast structures and processes in innovation management in Africa, Asia, Europe, and the Americas. The speciality of the book lies in its focus on the patterns that are behind the development of many successful innovation regions and it defines the ingredients for right planning and policy development.
