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AI-Based Data Analytics: Applications for Business Management
covers various topics related to marketing and business analytics.
It explores how organizations can increase their profits by making
better decisions in a timely manner through the use of data
analytics. This book is meant for students, practitioners, industry
professionals, researchers, and academics working in the field of
commerce and marketing, big data analytics, and organizational
decision-making. Highlights of the book include: The role of
Explainable AI in improving customer experiences in e-commerce
Sentiment analysis of social media Data analytics in business
intelligence Federated learning for business intelligence AI-based
planning of business management An AI-based business model
innovation in new technologies An analysis of social media
marketing and online impulse buying behaviour The book has two
primary focuses. The first is on analytics for decision-making and
covers big data analytics for market intelligence, data analytics
and consumer behavior, and the role of big data analytics in
organizational decision-making. The book’s second focus is on
digital marketing and includes the prediction of marketing by
consumer analytics, web analytics for digital marketing, smart
retailing, and leveraging web analytics for optimizing digital
marketing strategies.
1. Addresses a broad range of cyber security issues of modern
networks 2. The book will comprise state-of-the-art techniques,
methods and solutions for today's privacy / security issues. 3.
Interdisciplinary approaches for countering the latest attacks on
networks. 4. Will be excellent book for students, postgraduates and
professionals.
This book focuses on data analytics with machine learning using IoT
and blockchain technology. Integrating these three fields by
examining their interconnections, Intelligent Data Analytics, IoT,
and Blockchain examines the opportunities and challenges of
developing systems and applications exploiting these technologies.
Written primarily for researchers who are working in this
multi-disciplinary field, the book also benefits industry experts
and technology executives who want to develop their organizations'
decision-making capabilities. Highlights of the book include: Using
image processing with machine learning techniques A deep learning
approach for facial recognition A scalable system architecture for
smart cities based on cognitive IoT Source authentication of videos
shared on social media Survey of blockchain in healthcare Accident
prediction by vehicle tracking Big Data analytics in disaster
management An exploration of blockchain technology from the
perspective of applicability, limitations, and opportunities The
book presents novel ideas and insights on different aspects of data
analytics, blockchain technology, and IoT. It views these
technologies as interdisciplinary fields about processes and
systems that extract knowledge and insights from data. Focusing on
recent advancements, the book offers a variety of solutions to
real-life challenges with an emphasis on security.
Presents concepts of data for business decision making as well as
algorithms and models used to analyze data used to solve business
problems. Use data analytics to inform decisions related to product
price and possession utilities Market products on the basis of
consumer analytics
Big Data Analytics: Applications in Business and Marketing explores
the concepts and applications related to marketing and business as
well as future research directions. It also examines how this
emerging field could be extended to performance management and
decision-making. Investment in business and marketing analytics can
create value through proper allocation of resources and resource
orchestration process. The use of data analytics tools can be used
to diagnose and improve performance. The book is divided into five
parts. The first part introduces data science, big data, and data
analytics. The second part focuses on applications of business
analytics including: Big data analytics and algorithm Market basket
analysis Anticipating consumer purchase behavior Variation in
shopping patterns Big data analytics for market intelligence The
third part looks at business intelligence and features an
evaluation study of churn prediction models for business
Intelligence. The fourth part of the book examines analytics for
marketing decision-making and the roles of big data analytics for
market intelligence and of consumer behavior. The book concludes
with digital marketing, marketing by consumer analytics, web
analytics for digital marketing, and smart retailing. This book
covers the concepts, applications and research trends of marketing
and business analytics with the aim of helping organizations
increase profitability by improving decision-making through data
analytics.
Big Data Analytics: Applications in Business and Marketing explores
the concepts and applications related to marketing and business as
well as future research directions. It also examines how this
emerging field could be extended to performance management and
decision-making. Investment in business and marketing analytics can
create value through proper allocation of resources and resource
orchestration process. The use of data analytics tools can be used
to diagnose and improve performance. The book is divided into five
parts. The first part introduces data science, big data, and data
analytics. The second part focuses on applications of business
analytics including: Big data analytics and algorithm Market basket
analysis Anticipating consumer purchase behavior Variation in
shopping patterns Big data analytics for market intelligence The
third part looks at business intelligence and features an
evaluation study of churn prediction models for business
Intelligence. The fourth part of the book examines analytics for
marketing decision-making and the roles of big data analytics for
market intelligence and of consumer behavior. The book concludes
with digital marketing, marketing by consumer analytics, web
analytics for digital marketing, and smart retailing. This book
covers the concepts, applications and research trends of marketing
and business analytics with the aim of helping organizations
increase profitability by improving decision-making through data
analytics.
Extended Reality for Healthcare Systems: Recent Advances in
Contemporary Research focuses on real world applications in
medicine, also providing an overview of emerging technologies. The
book includes case studies that break down the ways in which this
technology has and can be used, while also taking readers through
evidence, best practices and obstacles. Sections emphasize
evidence, research-based practices and work. Content coverage
includes Enhancing Medical Education with AR/VR, and XR: The Future
of Surgery and Building Systems for Enhanced Health, and more.
Readers will learn how to use this technology to improve existing
systems by enhancing precision and reducing costs. Other sections
cover extended reality in elderly care and remote monitoring of
patients, building systems for enhanced health, including
telehealth and telepsychiatry, using AR and VR in medical
education, and designing technology for use in telesurgery.
This textbook covers contemporary topics in the field of digital
logic design, along with tools to design digital logic circuits. It
is designed for undergraduate students pursuing courses in
engineering disciplines such as electrical and electronics,
electronics and communication, electronics and instrumentation,
telecommunications, and computer science and engineering. It is
also useful as a text for MCA, M.Sc. (Electronics) and M.Sc.
(Computer Science) students. The text covers the basic concepts in
combinational and sequential circuit design, such as digital
electronics, digital signal processing, number system, data and
information representation and computer arithmetic. Advanced topics
in digital logic design, such as types of counter design, register
design, ALU design, threshold circuit and digital computer design
are also discussed.
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