Klappentext

Business decisions in any context--operational, tactical, or strategic--can have considerable consequences. Whether the outcome is positive and rewarding or negative and damaging to the business, its employees, and stakeholders is unknown when action is approved. These decisions are made under a proverbial cloud of uncertainty.
With this practical guide, data analysts, data scientists, and business analysts will learn why and how maximizing positive consequences and minimizing negative ones requires three forms of rich information: Descriptive Analytics explores the results of a previous action--what has already happened. Predictive Analytics focuses on what could happen under different conditions leading to a menu of decision options. Prescriptive Analytics advises decision-makers what should be selected from the menu.
While all three are important for decision-making under uncertainty, the primary focus of this book is the third: Prescriptive Analytics. Author Walter R. Paczkowski, PhD, shows you:
The distinction among Descriptive, Predictive, and Prescriptive Analytics
How Predictive Analytics produces a menu of decision options
How Prescriptive Analytics narrows the menu of decision options
The forms of Prescriptive Analytics for selecting from a menu
Two broad classes of these methods: non-stochastic and stochastic
The potential role of AI in Prescriptive Analytics
Ways to use an appropriate toolset in Python for Prescriptive Analytics