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Applying Predictive Analytics: Finding Value in Data

AUTHOR McCarthy, Mary M.; Ceccucci, Wendy; McCarthy, Richard V.
PUBLISHER Springer (12/24/2022)
PRODUCT TYPE Paperback (Paperback)

Description

The new edition of this textbook presents a practical, updated approach to predictive analytics for classroom learning. The authors focus on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life examples of how business analytics have been used in various aspects of organizations to solve issues or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes. The new edition includes chapters on clusters and associations and text mining to support predictive models. An additional case is also included that can be used with each chapter or as a semester project.

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Product Format
Product Details
ISBN-13: 9783030830724
ISBN-10: 3030830721
Binding: Paperback or Softback (Trade Paperback (Us))
Content Language: English
Edition Number: 0002
More Product Details
Page Count: 274
Carton Quantity: 26
Product Dimensions: 6.14 x 0.61 x 9.21 inches
Weight: 0.91 pound(s)
Feature Codes: Illustrated
Country of Origin: NL
Subject Information
BISAC Categories
Technology & Engineering | Telecommunications
Technology & Engineering | Engineering (General)
Technology & Engineering | Data Science - Data Analytics
Descriptions, Reviews, Etc.
jacket back
The new edition of this textbook presents a practical, updated approach to predictive analytics for classroom learning. The authors focus on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life examples of how business analytics have been used in various aspects of organizations to solve issues or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes. The new edition includes chapters on clusters and associations and text mining to support predictive models. An additional case is also included that can be used with each chapter or as a semester project.
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publisher marketing

The new edition of this textbook presents a practical, updated approach to predictive analytics for classroom learning. The authors focus on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life examples of how business analytics have been used in various aspects of organizations to solve issues or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes. The new edition includes chapters on clusters and associations and text mining to support predictive models. An additional case is also included that can be used with each chapter or as a semester project.

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Paperback