Business Analytics: A Data-Driven Decision-Making Approach for Business, Volume II by Amar Sahay is a comprehensive resource that delves into the application of data-driven models to measure past business performance, guiding organizations in visualizing and predicting future outcomes. This volume emphasizes predictive analytics, offering insights into regression analysis, forecasting, data mining, and emerging applications such as machine learning, neural networks, and artificial intelligence.
 
By integrating robust research, evidence-based practices, and compelling narratives, the text fosters a deeper understanding of key predictive models and their practical applications. It is an invaluable resource for students and professionals seeking to enhance their knowledge in business analytics and data-driven decision-making.
 
Business Analytics: A Data-Driven Decision-Making Approach for Business, Volume II by Amar Sahay, published by Business Expert Press in 2019, is available in PDF format, with Print ISBN: 1631574795, 9781631574795 and eTextbook ISBN: 1631574809, 9781631574801. This edition is categorized under Business Analytics, making it an invaluable asset for those aiming to excel in data-driven decision-making and predictive analytics. Purchase this eBook and save up to 80% at Ebookworm.
 
About the Author:
 
Amar Sahay: Dr. Amar Sahay is a professor of decision sciences engaged in teaching, research, consulting, and training. He holds a BS in production engineering from Birla Institute of Technology, India, an MS in industrial engineering, and a PhD in mechanical engineering from the University of Utah. Dr. Sahay has authored around 10 books in the areas of data visualization, business analytics, Six Sigma, statistics and data analysis, modeling, and applied regression. He is also associated with QMS Global LLC, a company engaged in data visualization, analytics, quality, lean six sigma, manufacturing, and systems analysis services. Dr. Sahay is a senior member of the Industrial & Systems Engineers, the American Society for Quality (ASQ), and Data Science.