Data Mining and Data Warehousing
Data Warehousing and Data Mining (English Version)
- Publisher: S.K. Kataria & Sons
- Author: Kanika Lakhani & Gaurav Girdhar
- Language: English
- Edition: 2012
- Pages: 250
- Cover: Paperback
- ISBN: 9789350143193
About the Book
Data Warehousing and Data Mining by Kanika Lakhani and Gaurav Girdhar is a comprehensive textbook designed for students and professionals studying computer science, information technology, and data analytics. The book provides a clear introduction to the concepts, techniques, and applications of data warehousing and data mining in modern information systems.
The book covers important topics such as data mining concepts, data preprocessing, language and concept description, associative rule mining, classification and prediction techniques, and cluster analysis. It also explains the fundamentals of data warehousing, OLAP systems, client-server computing, and web mining with practical and academic relevance.
Special emphasis has been given to the role of security in data warehousing and data mining environments, making the book useful for understanding real-world business intelligence systems and data analysis applications. The structured presentation and easy-to-understand explanations help students grasp both theoretical and practical aspects of the subject.
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Description
Data Warehousing and Data Mining (English Version)
- Publisher: S.K. Kataria & Sons
- Author: Kanika Lakhani & Gaurav Girdhar
- Language: English
- Edition: 2012
- Pages: 250
- Cover: Paperback
- ISBN: 9789350143193
About the Book
Data Warehousing and Data Mining by Kanika Lakhani and Gaurav Girdhar is a comprehensive textbook designed for students and professionals studying computer science, information technology, and data analytics. The book provides a clear introduction to the concepts, techniques, and applications of data warehousing and data mining in modern information systems.
The book covers important topics such as data mining concepts, data preprocessing, language and concept description, associative rule mining, classification and prediction techniques, and cluster analysis. It also explains the fundamentals of data warehousing, OLAP systems, client-server computing, and web mining with practical and academic relevance.
Special emphasis has been given to the role of security in data warehousing and data mining environments, making the book useful for understanding real-world business intelligence systems and data analysis applications. The structured presentation and easy-to-understand explanations help students grasp both theoretical and practical aspects of the subject.
