Profit-driven business analytics : a practitioner's guide to transforming big data into added value /

Maximize profit and optimize decisions with advanced business analytics Profit-Driven Business Analytics provides actionable guidance on optimizing the use of data to add value and drive better business. Combining theoretical and technical insights into daily operations and long-term strategy, this...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Verbeke, Wouter, 1983- (Autor), Bravo, Cristián, 1983- (Autor), Baesens, Bart (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, New Jersey : John Wiley & Sons, Inc., [2017]
Temas:
Management > Statistical methods.
Management > Data processing.
Big data.
Value added.
Strategic planning.
Business > Data processing.
Gestion > Méthodes statistiques.
Gestion > Informatique.
Données volumineuses.
Valeur ajoutée.
Planification stratégique.
BUSINESS & ECONOMICS > Industrial Management.
BUSINESS & ECONOMICS > Management.
BUSINESS & ECONOMICS > Management Science.
BUSINESS & ECONOMICS > Organizational Behavior.
Business > Data processing
Big data
Management > Data processing
Management > Statistical methods
Strategic planning
Value added
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover ; Title Page ; Copyright ; Contents ; Foreword; Acknowledgments; Chapter 1: A Value-Centric Perspective Towards Analytics ; Introduction ; Business Analytics ; Profit-Driven Business Analytics ; Analytics Process Model ; Analytical Model Evaluation ; Analytics Team ; Profiles.
  • Data Scientists Conclusion ; Review Questions; Multiple Choice Questions; Open Questions; References ; Chapter 2: Analytical Techniques ; Introduction ; Data Preprocessing ; Denormalizing Data for Analysis ; Sampling ; Exploratory Analysis ; Missing Values ; Outlier Detection and Handling.
  • Principal Component Analysis Types of Analytics ; Predictive Analytics ; Introduction ; Linear Regression ; Logistic Regression ; Decision Trees ; Neural Networks ; Ensemble Methods ; Bagging ; Boosting ; Random Forests ; Evaluating Ensemble Methods.
  • Evaluating Predictive Models Splitting Up the Dataset ; Performance Measures for Classification Models ; Performance Measures for Regression Models ; Other Performance Measures for Predictive Analytical Models ; Descriptive Analytics ; Introduction ; Association Rules.
  • Sequence Rules Clustering ; Survival Analysis ; Introduction ; Survival Analysis Measurements ; Kaplan Meier Analysis ; Parametric Survival Analysis ; Proportional Hazards Regression ; Extensions of Survival Analysis Models ; Evaluating Survival Analysis Models.

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