This book, Data Warehousing and Mining, covers all aspects of data warehousing and mining in an easy manner. This book will give learners sufficient information to acquire a complete knowledge over the subject. It covers the practical aspects of data mining, data warehousing, and knowledge discovery in a simplified manner without compromising on the details of the subject. The most important strength of the book is the illustration of concepts with practical examples so that the learners can grasp the contents in an easy manner. Another important feature of the book is illustration of data mining algorithms. 

The data mining has huge potential to improve business outcomes. There is a growing demand for data mining experts. This book intends training learners to fill this gap. This textbook includes many features such as chapter wise summary, exercises including probable problems, question bank, and relevant references, that provide sound knowledge to learners. It provides the students a platform to obtain expertise on data warehousing and mining technology, for better placements.

It covers a variety of topics, such as data warehousing and its benefits; architecture of data warehouse; data mart, data warehousing design strategies, Data Warehouse and OLAP technology, multidimensional data models, different OLAP Operations, ROLAP, MOLAP, fact tables and dimension tables; concept of primary key, surrogate keys and foreign keys; ETL process; Data Mining: Introduction, Data Preprocessing, Data mining techniques, KDP (Knowledge Discovery Process), Association Rule Mining, Single Dimensional Boolean Association Rules, Multi-Level Association Rule, Apriori Algorithm, Decision Tree, Bayesian Classification, Web Mining and its types, Spatial Mining, Temporal Mining, Text Mining.

We hope you will enjoy learning from this book as much as we enjoyed writing it.