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Overview: 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 usually made under the 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 from an action—what has already happened. Predictive analytics focuses on what could happen. The third, prescriptive analytics, informs us what should happen in the future. While all three are important for decision-makers, the primary focus of this book is on the third: prescriptive analytics. This book is intended for people involved in demand measurement and forecasting; predictive modeling; pricing analytics including elasticity estimation; customer satisfaction assessment; market and advertisement research; new product development and research; capital investment decisions; and any place where these analyses are input into major decisions at the operational, tactical, and strategic levels. This book will provide background for Prescriptive Analytics by explaining the intuition underlying analytic concepts; developing the necessary mathematical and statistical analytic principles; demonstrating concepts using Python in JupyterLab notebooks; and illustrating analytical concepts with use-cases.
Genre: Non-Fiction > Tech & Devices
Download Instructions:
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