000			01649nam a22001817a 4500
003			CUTN
005			20250522154433.0
008			250522b |||||||| |||| 00| 0 eng d
020			_a9789389583755
041			_aEnglish
082			_a005.74 _bKAM
100			_aKamthania, Deepali
245			_aData Warehousing and Data Mining /
260			_aNew Delhi : _bWiley India, _c2022.
300			_c24 cm.
520			_aDivided in two sections, this book is organized in 15 chapters. The first section covers data warehousing concepts and the steps required in creating a data warehouse for a decision support system along with data warehouse implementation case study. The second section provides a comprehensive introduction to data mining and is designed to be accessible and useful to students, instructors, researchers and professionals. It includes data preprocessing, visualization, predictive modeling, association analysis, clustering, and anomaly detection. The goal is to present fundamental concepts and algorithms for each topic, thus providing reader with the necessary background for the application of data mining to the real problems. Salient Features Important concepts of data warehousing and data mining. Solved numerical problems and case studies. The exercises have been provided at the end of every chapter. Chapters are organized into the following sections: Objectives, Theory and examples, Summary and Solved Problems. Summary at the end of the chapter Long and short answer type questions at the end of each chapter Tables and figures for better illustration Solutions to numerical problems.
942			_2ddc _cBOOKS
999			_c44352 _d44352