The document provides an overview of data warehousing and decision support systems. It discusses how data warehouses evolved from databases used for transaction processing to integrated databases designed for analysis and decision making. Key points include: - Data warehouses store historical data from multiple sources to support analysis and decision making. - They address limitations of transactional databases that are optimized for real-time queries rather than complex analysis. - Effective data warehousing requires resolving data conflicts, documenting assumptions, and learning from mistakes in the implementation process.

1. Data Warehouses Dr S.Natarajan

2. Introduction

11. Organizational Data Flow and Data Storage Components

12. Loading the Data Warehouse Source Systems Data Staging Area Data Warehouse (OLTP) Data is periodically extracted Data is cleansed and transformed Users query the data warehouse

14. A Data Warehouse is Subject Oriented

15. Data in a Data Warehouse are Integrated

18. Components of the Data Warehouse Architecture