Artificial Intelligence

This companion volume to Artificial Intelligence for Everyone delves into the dynamic landscape of modern business, where leveraging data through Business Intelligence (BI) and Data Analysis is paramount. Exploring Business Intelligence and Data Analysis in the Age of AI offers a comprehensive journey through foundational principles to advanced AI applications, equipping professionals for success in today's data-driven world. This book covers a wide range of essential topics:

• Delve into the analytics process, data understanding, and Big Data complexities
• Explore data integration, quality, governance, security, and privacy
• Understand data storage solutions like data warehousing and data lakes
• Learn practical techniques such as ETL processes, data design, and programming languages like R, SQL, and Python
• Discover the importance of effective reporting, cloud computing, and data visualization
• Gain insights into predictive analytics and advanced data analysis techniques
• Uncover the transformative impact of AI in BI and data analysis, while addressing risks, ethics, and future implications

With these key areas, the book ensures a thorough grounding in BI and data analysis, preparing readers to harness the power of AI for insightful, ethical, and effective data utilization.

Beginning with the development process of machine learning and AI, this book uncovers the intricate components of AI systems and sub-fields, including cognitive computing, computer vision, and machine learning.

AI categories, such as artificial narrow intelligence (ANI) and artificial general intelligence (AGI), are explored. Categories based on functionality provide insight into different types of AI systems.

The core of the book delves into analytics, covering techniques, stages, AI analytics, and applications. It sheds light on elements of the AI framework, platforms, and tools, as well as key players. AI infrastructure is discussed, encompassing hardware components, vendors, and software aspects.

Several chapters address the various risks associated with AI, from bad data to privacy concerns, and explore strategies for risk mitigation. The challenges faced in implementing AI are discussed in their own chapter.

Lastly, the book peers into the future of AI, examining its transformative potential and offering recommendations for starting your AI journey. Appendices provide additional insights into AI applications, platforms, tools, and key players.