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Prescriptive Analytics: Python and Excel Approaches

Authors

Dr. Randy Bulriss, PhD
Grand Canyon University
Dr. Mark Keith, PhD
Brigham Young University

Contributors

Edition 1
(rev. 1845)

Epigraph:

“The realm of analytics has embarked on an astonishing journey, evolving from its descriptive origins to predictive prowess, and now, poised at the threshold of prescriptive excellence. This transformative progression has revolutionized decision-making, equipping organizations to distill actionable insights from data and orchestrate strategies that drive business triumph.” - Eujish Selvaraj

Abstract:

Prescriptive analytics empowers organizations to optimize decisions by leveraging data-driven insights to proactively determine the best actions for future success. We will build upon your introduction to programming (in Python), statistics, data cleaning, and automating workflows from prior courses. This book is to assist with advancing your analytics skills from distilling descriptive analytics from historical data and anticipating future trends with predictive analytics. The course outcomes will enable you to master applying advanced algorithms, decision optimization while minimizing risks with prescriptive analytics using both Excel and Python models.

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