Computing Predictive Analytics Business Intelligence And Economics
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Computing Predictive Analytics, Business Intelligence, and Economics by Cyrus F. Nourani Pdf
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.
Computing Predictive Analytics, Business Intelligence, and Economics by Cyrus F. Nourani Pdf
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.
Machine Learning Techniques for Improved Business Analytics by G., Dileep Kumar Pdf
Analytical tools and algorithms are essential in business data and information systems. Efficient economic and financial forecasting in machine learning techniques increases gains while reducing risks. Providing research on predictive models with high accuracy, stability, and ease of interpretation is important in improving data preparation, analysis, and implementation processes in business organizations. Machine Learning Techniques for Improved Business Analytics is a collection of innovative research on the methods and applications of artificial intelligence in strategic business decisions and management. Featuring coverage on a broad range of topics such as data mining, portfolio optimization, and social network analysis, this book is ideally designed for business managers and practitioners, upper-level business students, and researchers seeking current research on large-scale information control and evaluation technologies that exceed the functionality of conventional data processing techniques.
Business Intelligence in Economic Forecasting: Technologies and Techniques by Wang, Jue,Wang, Shouyang Pdf
With the rapid development of economic globalization and information technology, the field of economic forecasting continues its expeditious advancement, providing business and government with applicable technologies. This book discusses various business intelligence techniques including neural networks, support vector machine, genetic programming, clustering analysis, TEI@I, fuzzy systems, text mining, and many more. It serves as a valuable reference for professionals and researchers interested in BI technologies and their practical applications in economic forecasting, as well as policy makers in business organizations and governments.
Computational Intelligence for Business Analytics by Witold Pedrycz,Luis Martínez,Rafael Alejandro Espin-Andrade,Gilberto Rivera,Jorge Marx Gómez Pdf
Corporate success has been changed by the importance of new developments in Business Analytics (BA) and furthermore by the support of computational intelligence- based techniques. This book opens a new avenues in these subjects, identifies key developments and opportunities. The book will be of interest for students, researchers and professionals to identify innovative ways delivered by Business Analytics based on computational intelligence solutions. They help elicit information, handle knowledge and support decision-making for more informed and reliable decisions even under high uncertainty environments.Computational Intelligence for Business Analytics has collected the latest technological innovations in the field of BA to improve business models related to Group Decision-Making, Forecasting, Risk Management, Knowledge Discovery, Data Breach Detection, Social Well-Being, among other key topics related to this field.
Recent Developments in Data Science and Business Analytics by Madjid Tavana,Srikanta Patnaik Pdf
This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.
Artificial Intelligence and Computing Logic by Cyrus F. Nourani Pdf
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.
If you want to learn about business intelligence and predictive analytics, then keep reading... Two manuscripts in one book: Business Intelligence: An Essential Beginner's Guide to BI, Big Data, Artificial Intelligence, Cybersecurity, Machine Learning, Data Science, Data Analytics, Social Media and Internet Marketing Predictive Analytics: The Secret to Predicting Future Events Using Big Data and Data Science Techniques Such as Data Mining, Predictive Modelling, Statistics, Data Analysis, and Machine Learning In the modern business world, the pace of action continues to quicken. Businesses need to be able to get actionable insights from their data in order to make the right decisions to act rapidly and effectively. In this book, you will be introduced to the concept of business intelligence. Business intelligence is closely connected to data, and so as part of our journey, we are going to see how modern companies are using big data, together with artificial intelligence, machine learning, and pattern recognition in order to build systems of data-driven decision making. After we get a handle on what business intelligence is, we will learn how it ties together with the next computer revolution (happening right before our eyes). We will discuss the use of artificial intelligence, machine learning, and pattern recognition to retrieve insights from the large amounts of data that companies are routinely collecting, storing, and using. We will also explore the roles that social media and internet marketing are playing in the growth of business intelligence, and how companies like Facebook are helping other companies act on data in powerful ways. Some of the topics covered in part 1 of this book include: An Introduction to BI, Big Data, AI, and More An Overview of Business Intelligence BI and AI BI and Big Data BI And Machine Learning Data Science Cybersecurity BI and Data Mining BI and Social Media BI and Internet Marketing And much much more! Some of the topics covered in part 2 of this book include: The basics of predictive analysis. How to predict events that are going to happen in the future with big data and data mining. How to predict events that are going to happen in the future with the help of data analysis and statistics. A look at machine learning and how this process can help make predictions. How to avoid prediction traps, avoid bias, and make the best decisions with this analysis. Some of the top reasons to implement this kind of analysis in your business. The steps you can take to create your own predictive analysis model. And much, much more! So if you want to learn more about business intelligence and predictive analytics, click the "add to cart" button!
Together, Big Data, high-performance computing, and complex environments create unprecedented opportunities for organizations to generate game-changing insights that are based on hard data. Business Analytics: An Introduction explains how to use business analytics to sort through an ever-increasing amount of data and improve the decision-making capabilities of an organization. Covering the key areas of business analytics, the book explores the concepts, techniques, applications, and emerging trends that professionals across a wide range of industries need to be aware of. Better detection of fraud through visual analytics or better prediction of the likelihood of someone getting an infection while in the hospital are just a few examples of where analytics can play a positive role. As the field of business analytics continues to emerge rapidly, there is a need for a reliable textbook and reference on the subject. Filling this need, this book is suitable for graduate-level students and undergraduate seniors. It maintains a focus on only the key areas so the material can be covered adequately in a one-semester or one-quarter course. Each chapter includes software-generic exercises, labs, and associated answers to the exercises/labs. Author Jay Liebowitz recently had an article published in The World Financial Review. www.worldfinancialreview.com/?p=1904
Big Data, Big Analytics by Michael Minelli,Michele Chambers,Ambiga Dhiraj Pdf
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.
Mastering Business Intelligence with MicroStrategy by Dmitry Anoshin,Himani Rana,Ning Ma Pdf
Build world-class enterprise Business Intelligence solutions with MicroStrategy 10 About This Book Fix the gap between BI tools and implementation/integration processes with big data and predictive analytics using this comprehensive guide to MicroStrategy 10 Highly practical, example-rich guide that lets you implement business intelligence with MicroStrategy 10 in your organization Create the best user experience with BI dashboards using MicroStrategy using this up-to-date, comprehensive guide Who This Book Is For This book is intended for BI, DWH, ETL developers, BI/DWH/Analytics managers, analysts, and business users who already have MicroStrategy in their organization and want to take it to the next level in order to increase performance and improve user experience. In addition, it helps the reader to migrate from MicroStrategy 9 to MicroStrategy 10 and to start using the new capabilities. What You Will Learn Explore various visualization techniques for presenting analyzed data Customize MicroStrategy in order to meet your business requirements Develop and design mobile dashboards Use the advanced techniques such as designing reports, documents and interactive dashboards for building dashboards Understand the concepts of data discovery and Desktop capabilities Explore the best practices for Microstrategy system administration Find and fix issues based on connections, environment or documents Integrate third party ESRI map tools with MicroStrategy to create geo based reports In Detail Business intelligence is becoming more important by the day, with cloud offerings and mobile devices gaining wider acceptance and achieving better market penetration. MicroStrategy Reporting Suite is an absolute leader in the BI market and offers rich capabilities from basic data visualizations to predictive analytics. It lets you various delivery methods such as the Web, desktops, and mobiles. Using real-world BI scenarios, this book helps you to implement Business Analytics solutions in big e-commerce companies. It kicks off with MicroStrategy 10 features and then covers schema design models and techniques. Building upon your existing knowledge, the book will teach you advanced techniques for building documents and dashboards. It further teaches various graphical techniques for presenting data for analysis using maps, graphs, and advanced charts. Although MicroStrategy has rich functionality, the book will show how to customize it in order to meet your business requirements. You will also become familiar with the native analytical functions that will help you to maximize the impact of BI solutions with powerful predictive analytics. Furthermore, the book will focus on MicroStrategy Mobile Analytics along with data discovery and desktop capabilities such as connecting various data sources and building interactive dashboards. The book will also uncover best practices, troubleshooting techniques for MicroStrategy system administration, and also security and authentication techniques. Lastly, you will learn to use Hadoop for MicroStrategy reporting. By the end of the book, you will become proficient in evaluating any BI software in order to choose the best one that meets all business requirements. Style and approach This book will be focusing on providing extensive guide to plan how to design and develop complex BI architecture for real world scenario, using Microstrategy 10, best practices and collected experience working with BI, predictive analytics, and Microstrategy and big data.
Use Predictive Analytics to Uncover Hidden Patterns and Correlations and Improve Decision-Making Using predictive analytics techniques, decision-makers can uncover hidden patterns and correlations in their data and leverage these insights to improve many key business decisions. In this thoroughly updated guide, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for both business professionals and students. Delen's holistic approach covers key data mining processes and methods, relevant data management techniques, tools and metrics, advanced text and web mining, big data integration, and much more. Balancing theory and practice, Delen presents intuitive conceptual illustrations, realistic example problems, and real-world case studies—including lessons from failed projects. It's all designed to help you gain a practical understanding you can apply for profit. * Leverage knowledge extracted via data mining to make smarter decisions * Use standardized processes and workflows to make more trustworthy predictions * Predict discrete outcomes (via classification), numeric values (via regression), and changes over time (via time-series forecasting) * Understand predictive algorithms drawn from traditional statistics and advanced machine learning * Discover cutting-edge techniques, and explore advanced applications ranging from sentiment analysis to fraud detection
Sustainable Development Through Data Analytics and Innovation by Jorge Marx Gómez,Lawal O. Yesufu Pdf
Sustainable development is based on the idea that societies should advance without compromising their future development requirements. This book explores how the application of data analytics and digital technologies can ensure that development changes are executed on the basis of factual data and information. It addresses how innovations that rely on digital technologies can support sustainable development across all sectors and all social, economic, and environmental aspects and help us achieve the Sustainable Development Goals (SDGs). The book also highlights techniques, processes, models, tools, and practices used to achieve sustainable development through data analysis. The various topics covered in this book are critically evaluated, not only theoretically, but also from an application perspective. It will be of interest to researchers and students, especially those in the fields of applied data analytics, business intelligence and knowledge management.
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.
Business Analytics by Thomas W. Jackson,Steven Lockwood Pdf
This innovative new textbook, co-authored by an established academic and a leading practitioner, is the first to bring together issues of cloud computing, business intelligence and big data analytics in order to explore how organisations use cloud technology to analyse data and make decisions. In addition to offering an up-to-date exploration of key issues relating to data privacy and ethics, information governance, and the future of analytics, the text describes the options available in deploying analytic solutions to the cloud and draws on real-world, international examples from companies such as Rolls Royce, Lego, Volkswagen and Samsung. Combining academic and practitioner perspectives that are crucial to the understanding of this growing field, Business Analytics acts an ideal core text for undergraduate, postgraduate and MBA modules on Big Data, Business and Data Analytics, and Business Intelligence, as well as functioning as a supplementary text for modules in Marketing Analytics. The book is also an invaluable resource for practitioners and will quickly enable the next generation of 'Information Builders' within organisations to understand innovative cloud based-analytic solutions.
