Principles and implementation of data warehousing

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This book provides a comprehensive introduction to the concepts, architecture, and practical implementation of data warehousing, with a strong focus on performance and maintainability. It explains the fundamental principles of designing a data warehouse, including schema modeling (star and snowflake schemas), dimension design, and the role of materialized views, indexing, and partitioning to optimize query performance. A major part of the book is devoted to the extraction, transformation, and loading (ETL) process, highlighting data quality, change data capture, and methods to keep warehouses synchronized with source systems. The author also addresses ongoing operational concerns such as maintaining and expanding the warehouse, managing growth, and optimizing summaries for analytical use. Online Analytical Processing (OLAP) techniques are presented as the foundation for multi-dimensional analysis, supported by SQL aggregations and Oracle-based examples. While rooted in Oracle 9i/10g technologies, the book’s principles remain broadly applicable, making it a practical guide for students and practitioners who need both theoretical grounding and implementation strategies.

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