Data Warehousing and Data Mining: Concepts and Practical Techniques for IT Professionals is a comprehensive academic resource designed to bridge theoretical knowledge with practical applications in the evolving field of data science. Authored by Dr. Shaheen Layaq, Dr. V. Poornachandar, and Keesara Vani, the book provides IT professionals, educators, and students with a deep understanding of the core concepts, methods, and tools involved in modern data warehousing and data mining. It begins by explaining foundational principles such as knowledge discovery, data preprocessing, and data visualization, then progresses into advanced topics like OLAP operations, classification, clustering, and outlier detection.

Through its structured chapters and real-world case examples, the book illustrates how data mining supports decision-making, predictive analytics, and business intelligence. Special attention is given to applications for IT professionals, including skill gap analysis, recruitment optimization, and performance prediction. Covering key techniques such as decision trees, neural networks, association rule mining, and data modeling, the book offers practical insights supported by statistical and machine learning frameworks. This volume is an essential guide for learners and practitioners aiming to master data-driven strategies in today’s data-centric industries.