Data Mining and Data Warehousing
Book Details
- Publisher: S.K. KATARIA & SONS
- Author: Gunjan Goswami
- Language: English
- Edition: 2012
- Pages: 265
- Cover: Paperback
- ISBN: 9789350143537
- Dimensions: 9.4 x 7.2 x 0.5 inches
About the Book
This book by Gunjan Goswami provides a detailed introduction to Data Warehousing and Data Mining concepts for students and professionals in computer science information technology and data analytics. The book is written in a simple and structured manner making complex topics easy to understand for academic learning examination preparation and practical application.
The book covers important topics such as data warehouse features architecture dimensional modeling OLAP and strategies for large data warehouse projects. It also explains data warehouse implementation techniques and introduces readers to core concepts of data mining including classification association rules clustering and mining complex types of data.
Additional sections including question banks test yourself exercises model test papers and examination papers help students strengthen conceptual understanding and improve preparation for university and competitive examinations. The organized presentation and practical approach make this book a valuable resource for learners interested in data warehousing data mining and business intelligence technologies.
Original: $3.39
-65%$3.39
$1.19Product Information
Product Information
Shipping & Returns
Shipping & Returns
Description
Book Details
- Publisher: S.K. KATARIA & SONS
- Author: Gunjan Goswami
- Language: English
- Edition: 2012
- Pages: 265
- Cover: Paperback
- ISBN: 9789350143537
- Dimensions: 9.4 x 7.2 x 0.5 inches
About the Book
This book by Gunjan Goswami provides a detailed introduction to Data Warehousing and Data Mining concepts for students and professionals in computer science information technology and data analytics. The book is written in a simple and structured manner making complex topics easy to understand for academic learning examination preparation and practical application.
The book covers important topics such as data warehouse features architecture dimensional modeling OLAP and strategies for large data warehouse projects. It also explains data warehouse implementation techniques and introduces readers to core concepts of data mining including classification association rules clustering and mining complex types of data.
Additional sections including question banks test yourself exercises model test papers and examination papers help students strengthen conceptual understanding and improve preparation for university and competitive examinations. The organized presentation and practical approach make this book a valuable resource for learners interested in data warehousing data mining and business intelligence technologies.
