Introduction To Business Data Mining
Olson, David L.
Verkauft von Toscana Books, AUSTIN, TX, USA
AbeBooks-Verkäufer seit 7. November 2023
Neu - Hardcover
Zustand: Neu
Anzahl: 1 verfügbar
In den Warenkorb legenVerkauft von Toscana Books, AUSTIN, TX, USA
AbeBooks-Verkäufer seit 7. November 2023
Zustand: Neu
Anzahl: 1 verfügbar
In den Warenkorb legenExcellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
Bestandsnummer des Verkäufers Scanned0072959711
Introduction to Business Data Mining was developed to introduce students, as opposed to professional practitioners or engineering students, to the fundamental concepts of data mining. Most importantly, this text shows readers how to gather and analyze large sets of data to gain useful business understanding.
A four part organization introduces the material (Part I), describes and demonstrated basic data mining algorithms (Part II), focuses on the business applications of data mining (Part III), and presents an overview of the developing areas in this field, including web mining, text mining, and the ethical aspects of data mining. (Part IV).
The author team has had extensive experience with the quantitative analysis of business as well as with data mining analysis. They have both taught this material and used their own graduate students to prepare the text’s data mining reports. Using real-world vignettes and their extensive knowledge of this new subject, David Olson and Yong Shi have created a text that demonstrates data mining processes and techniques needed for business applications.
Introduction to Business Data Mining was developed to introduce students, as opposed to professional practitioners or engineering students, to the fundamental concepts of data mining. Most importantly, this text shows readers how to gather and analyze large sets of data to gain useful business understanding.
A four part organization introduces the material (Part I), describes and demonstrated basic data mining algorithms (Part II), focuses on the business applications of data mining (Part III), and presents an overview of the developing areas in this field, including web mining, text mining, and the ethical aspects of data mining. (Part IV).
The author team has had extensive experience with the quantitative analysis of business as well as with data mining analysis. They have both taught this material and used their own graduate students to prepare the text’s data mining reports. Using real-world vignettes and their extensive knowledge of this new subject, David Olson and Yong Shi have created a text that demonstrates data mining processes and techniques needed for business applications.
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