Computing Predictive Analytics, Business Intelligence, and Economics

Computing Predictive Analytics, Business Intelligence, and Economics
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.

E-Business

E-Business
Author: Robert M.X. Wu
Publisher: BoD – Books on Demand
Total Pages: 172
Release: 2021-05-19
Genre: Business & Economics
ISBN: 1789846846

This book provides the latest viewpoints of scientific research in the field of e-business. It is organized into three sections: “Higher Education and Digital Economy Development”, “Artificial Intelligence in E-Business”, and “Business Intelligence Applications”. Chapters focus on China’s higher education in e-commerce, digital economy development, natural language processing applications in business, Information Technology Governance, Risk and Compliance (IT GRC), business intelligence, and more.

Business Intelligence Strategy and Big Data Analytics

Business Intelligence Strategy and Big Data Analytics
Author: Steve Williams
Publisher: Morgan Kaufmann
Total Pages: 241
Release: 2016-04-08
Genre: Computers
ISBN: 0128094893

Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like "big data and "big data analytics have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. - Provides ideas for improving the business performance of one's company or business functions - Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies - Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans

Computational Intelligence and Predictive Analysis for Medical Science

Computational Intelligence and Predictive Analysis for Medical Science
Author: Poonam Tanwar
Publisher: de Gruyter
Total Pages: 280
Release: 2021-10-25
Genre:
ISBN: 9783110714982

THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.

Data Analysis for Business, Economics, and Policy

Data Analysis for Business, Economics, and Policy
Author: Gábor Békés
Publisher: Cambridge University Press
Total Pages: 741
Release: 2021-05-06
Genre: Business & Economics
ISBN: 1108483011

A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

Artificial Intelligence and Computing Logic

Artificial Intelligence and Computing Logic
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.

Internet of Things in Business Transformation

Internet of Things in Business Transformation
Author: Parul Gandhi
Publisher: John Wiley & Sons
Total Pages: 320
Release: 2021-02-03
Genre: Computers
ISBN: 1119711126

The objective of this book is to teach what IoT is, how it works, and how it can be successfully utilized in business. This book helps to develop and implement a powerful IoT strategy for business transformation as well as project execution. Digital change, business creation/change and upgrades in the ways and manners in which we work, live, and engage with our clients and customers, are all enveloped by the Internet of Things which is now named "Industry 5.0" or "Industrial Internet of Things." The sheer number of IoT(a billion+), demonstrates the advent of an advanced business society led by sustainable robotics and business intelligence. This book will be an indispensable asset in helping businesses to understand the new technology and thrive.

Big Data Analytics Techniques for Market Intelligence

Big Data Analytics Techniques for Market Intelligence
Author: Darwish, Dina
Publisher: IGI Global
Total Pages: 536
Release: 2024-01-04
Genre: Computers
ISBN:

The ever-expanding realm of Big Data poses a formidable challenge for academic scholars and professionals due to the sheer magnitude and diversity of data types, along with the continuous influx of information from various sources. Extracting valuable insights from this vast and complex dataset is crucial for organizations to uncover market intelligence and make informed decisions. However, without the proper guidance and understanding of Big Data analytics techniques and methodologies, scholars may struggle to navigate this landscape and maximize the potential benefits of their research. In response to this pressing need, Professor Dina Darwish presents Big Data Analytics Techniques for Market Intelligence, a groundbreaking book that addresses the specific challenges faced by scholars and professionals in the field. Through a comprehensive exploration of various techniques and methodologies, this book offers a solution to the hurdles encountered in extracting meaningful information from Big Data. Covering the entire lifecycle of Big Data analytics, including preprocessing, analysis, visualization, and utilization of results, the book equips readers with the knowledge and tools necessary to unlock the power of Big Data and generate valuable market intelligence. With real-world case studies and a focus on practical guidance, scholars and professionals can effectively leverage Big Data analytics to drive strategic decision-making and stay at the forefront of this rapidly evolving field.

Big Data Computing

Big Data Computing
Author: Tanvir Habib Sardar
Publisher: CRC Press
Total Pages: 397
Release: 2024-02-27
Genre: Computers
ISBN: 100382272X

This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in big data computing applications such as machine learning, deep learning, graph processing, and many others. Features: Provides comprehensive analysis of advanced aspects of big data challenges and enabling technologies. Explains computing models using real-world examples and dataset-based experiments. Includes case studies, quality diagrams, and demonstrations in each chapter. Describes modifications and optimization of existing technologies along with the novel big data computing models. Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high-performance computing, data mining, knowledge discovery, and distributed computing.