Role of AI in Data Analytics: Theory, Design and Development

Artificial Intelligence (AI) is essentially transforming data analytics by making it quicker, more accurate, more efficient, and more insightful. Businesses use data as a motivator, using it to inform decisions about the future based on performance to date. Large Language Models (LLMs) are sophisticated artificial intelligence (AI) systems that use deep learning to comprehend large datasets, create content, summarize data, and make predictions. The need for data analysts has increased along with the importance of data analytics in today's data-driven world. If you are seeking to grasp the basics of data analytics, Data Analytics Essentials is a thorough yet concise guide that is ideal for you. Get started and learn how to collect data efficiently, guarantee repeatability, perform in-depth literature reviews, alter data, and clearly communicate your findings. There are eight chapters in this "Role of AI in Data Analytics" textbook:

Chapter 1: Introduction of Data Analytics
Chapter 2: Data Analysis
Chapter 3: Applications of Data Analytics
Chapter 4: Digital Data and Data Science
Chapter 5: Big Data and Management
Chapter 6: Statistical Measures
Chapter 7: Predictive Analytics
Chapter 8: Role of AI in Data Analytics
After finishing this book, you will receive:
[1] A basic understanding of data analytics, including its various forms
[2] Knowledge of data analytics procedures, and various analytics approaches
[3] An examination of the potential and difficulties of the broad subject of big data analytics
[4] Knowledge of current legal frameworks, as well as privacy and ethics concerns data analytics
[5] Applying a range of real-world case studies to application-based learning

Research and data analysts are examples of career professionals moving from academia to a workplace where career advancement is greatly impacted by production quality. Beyond just a theoretical guidebook, Data Analytics Essentials includes fun facts and real-world case studies to help you learn more. Regardless of your level of experience, this book will help you advance from novice to proficient data analyst-one clean dataset at a time. Beginners who work with data and those who need to understand how to interpret their consumer or corporate data should read this book. High-level ideas that are helpful to managers, such as data pipelines, machine learning, data storytelling, and visualizations, are also covered in the book.