Publisher:

Emerald Publishing

Book Title:

Data Science for Decision Makers: Leveraging Business Analytics, Intelligence, and AI for Organizational Success

Editors:

· Dr. Miltiadis D. Lytras, The American College of Greece, Greece

· Dr. Lily Popova Zhuhadar, Western Kentucky University, USA

Book Description

As the digital landscape evolves, the integration of Business Analytics (BA), Business Intelligence (BI), and Artificial Intelligence (AI) is revolutionizing Decision-Making processes across industries. Data Science for Decision Makers serves as a comprehensive resource, exploring these fields' convergence to optimize organizational success. With the continuous advancements in AI and data science, this book is both timely and essential for business leaders, managers, and academics looking to harness these technologies for enhanced Decision-Making and strategic growth. This book combines theoretical insights with practical applications, addressing current and future challenges and providing actionable guidance. It aims to bridge the gap between advanced analytical theories and their applications in real-world business scenarios, featuring contributions from global experts and detailed case studies from various industries.

Book Sections and Chapter Topics

Section 1: Foundations of Business Analytics and Intelligence

· The evolution of business analytics and intelligence

· Key concepts and definitions in BA and BI

· Data management and governance

· Analytical methods and tools

· The role of descriptive, predictive, and prescriptive analytics

Section 2: Artificial Intelligence in Business

· Overview of AI technologies in business

· AI for data mining and pattern recognition

· Machine learning algorithms for predictive analytics

· Natural language processing for business intelligence

· AI-driven decision support systems

Section 3: Integrating AI with Business Analytics and Intelligence

· Strategic integration of AI in business systems

· Case studies on AI and BI synergies

· Overcoming challenges in AI adoption

· The impact of AI on business reporting and visualization

· Best practices for AI and BI integration

Section 4: Advanced Analytics Techniques

· Advanced statistical models for business analytics

· Deep learning applications in BI

· Sentiment analysis and consumer behavior

· Realtime analytics and streaming data

· Predictive and prescriptive analytics case studies

Section 5: Ethical, Legal, and Social Implications

· Data privacy and security in AI and BI

· Ethical considerations in data use

· Regulatory compliance and standards

· Social implications of AI in business

· Building trust and transparency in analytics

Section 6: Future Trends and Directions

· The future of AI in business analytics

· Emerging technologies and their potential impact

· Evolving business models driven by AI and analytics

· The role of AI in sustainable business practices

· Preparing for the next wave of digital transformation

Objectives of the Book

· Provide a deep understanding of AI’s role in transforming business analytics and intelligence.

· Present strategies for integrating AI to enhance Decision-Making and operational efficiency.

· Address ethical and regulatory considerations in data analytics.

· Serve as a practical guide for executives, data scientists, and academics in a data-driven economy.

Important Dates

· Chapter Proposal Submission Deadline: 25 November 2024

· Full Chapter Submission Deadline: 31 January 2025

· Revisions Due: 4 April 2025

· Submission to Publisher: 1 May 2025

· Anticipated Publication: Winter 2025

Target Audience

· Business Professionals and Executives: Seeking insights to improve Decision-Making.

· Data Scientists and Business Analysts: Expanding their toolkit with AI and analytics techniques.

· Academic Researchers and Educators: Using it as a resource for teaching and research.

· IT and MIS Professionals: Enhancing their understanding of BI systems and data management.

· Policy Makers and Regulatory Bodies: Understanding the social and regulatory impacts of AI and analytics.

Keywords

· Artificial Intelligence

· Business Analytics

· Business Intelligence

· Data Science

· Decision-Making

Submission Guidelines

We invite chapter proposals that align with the outlined sections and objectives. Proposals should include:

· Title

· Authors and affiliations

· Abstract (200-250 words)

· Keywords

Contact Information

Dr. Miltiadis D. Lytras: [email protected]

Dr. Lily Popova Zhuhadar: [email protected]