Applying Data Science

Business Case Studies Using SAS

By: Gerhard Svolba

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Paperback | 29 March 2017

At a Glance

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490 Pages

Dimensions(cm)
27.94 x 20.96 x 2.52

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See how data science can answer the questions your business faces!

Applying Data Science: Business Case Studies Using SAS, by Gerhard Svolba, shows you the benefits of analytics, how to gain more insight into your data, and how to make better decisions. In eight entertaining and real-world case studies, Svolba combines data science and advanced analytics with business questions, illustrating them with data and SAS code.

The case studies range from a variety of fields, including performing headcount survival analysis for employee retention, forecasting the demand for new projects, using Monte Carlo simulation to understand outcome distribution, among other topics. The data science methods covered include Kaplan-Meier estimates, Cox Proportional Hazard Regression, ARIMA models, Poisson regression, imputation of missing values, variable clustering, and much more!

Written for business analysts, statisticians, data miners, data scientists, and SAS programmers, Applying Data Science bridges the gap between high-level, business-focused books that skimp on the details and technical books that only show SAS code with no business context.

Industry Reviews

"The book perfectly combines data science methods with relevant business case studies, providing insights into how applications of data science can build the basis for better business decisions.. . . It can be read by business experts, data scientists, and SAS programmers." -- Wolfgang Hauner, Chief Data Officer "Munich Re"

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