Hands-on prescriptive analytics optimizing your decision making with Python
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...
Otros Autores: | |
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Formato: | Libro electrónico |
Idioma: | Inglés |
Publicado: |
Sebastopol, CA :
O'Reilly Media, Inc
2024.
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Edición: | First edition |
Materias: | |
Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009853630106719 |
Sumario: | 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. |
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Descripción Física: | 1 online resource (412 pages) : illustrations |
ISBN: | 9781098153168 |