Data Mining and Data Warehousing (Paperback)

Parteek Bhatia

ISBN 10: 1108727743 / ISBN 13: 9781108727747

Published by Cambridge University Press, Cambridge, 2019

About this Item

Paperback. Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naive Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding. This textbook gives an in-depth discussion of basic principles and practical techniques of data mining and data warehousing. Theoretical concepts are discussed in detail with the help of practical examples. It covers data mining tools and language such as Weka and R language. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Seller Inventory # 9781108727747

Bibliographic Details

• Title: Data Mining and Data Warehousing (Paperback)
• Publisher: Cambridge University Press, Cambridge
• Publication Date: 2019
• Language: English
• ISBN 10: 1108727743
• ISBN 13: 9781108727747
• Binding: Paperback
• Condition: new

About this title

Synopsis

Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.

About the Author

Parteek Bhatia is an associate professor in the department of computer science and engineering at Thapar Institute of Engineering and Technology, Patiala. He has more than twenty years of teaching experience and has published papers in journals. His current research includes natural language processing, machine learning and human computer interface. He has taught courses including data mining and data warehousing, big data analysis and database management system at undergraduate and graduate levels.