Building a data warehouse involves answering critical questions about costs, time, users, people, hardware, software, and services. The project manager must determine what data is needed, who will use it, and how it will be managed. Understanding the difference between operational and informational data is crucial, as informational data is subject-oriented and provides a broader view of the business. Data warehouses must be flexible and scalable to adapt to changing business needs. They allow cross-functional analysis, enabling users to discover why certain trends occur. A solid informational infrastructure should enable users to get answers to their questions. The data warehouse framework includes planning, design and implementation, and support and enhancement. Planning involves identifying business problems and providing a structured process. Design and implementation involve analyzing the current environment and ensuring the solution is effective. Support and enhancement involve maintaining and expanding the warehouse to meet new needs. Anthem Blue Cross Blue Shield has implemented a data warehouse to improve the quality and reduce the cost of care for its policyholders. The warehouse contains 1.3TB of data, providing better access to information and helping reduce fraud, negotiate lower rates, and improve patient care. The warehouse also helps in detecting fraud and winning new business by providing detailed data and reporting capabilities. Metadata is essential for managing data in a data warehouse. It provides a roadmap to the data, helping users find and understand the information. Metadata must be carefully managed to ensure data accuracy and consistency. Successful data warehouse projects require executive support, a specific business problem to solve, a well-defined plan, proven technology, and experienced people. Careful planning and alignment between the IT department and business users are essential for success. A data warehouse is built to answer specific business problems, not to showcase technology. Using the guidelines outlined here can significantly improve the chances of success.Building a data warehouse involves answering critical questions about costs, time, users, people, hardware, software, and services. The project manager must determine what data is needed, who will use it, and how it will be managed. Understanding the difference between operational and informational data is crucial, as informational data is subject-oriented and provides a broader view of the business. Data warehouses must be flexible and scalable to adapt to changing business needs. They allow cross-functional analysis, enabling users to discover why certain trends occur. A solid informational infrastructure should enable users to get answers to their questions. The data warehouse framework includes planning, design and implementation, and support and enhancement. Planning involves identifying business problems and providing a structured process. Design and implementation involve analyzing the current environment and ensuring the solution is effective. Support and enhancement involve maintaining and expanding the warehouse to meet new needs. Anthem Blue Cross Blue Shield has implemented a data warehouse to improve the quality and reduce the cost of care for its policyholders. The warehouse contains 1.3TB of data, providing better access to information and helping reduce fraud, negotiate lower rates, and improve patient care. The warehouse also helps in detecting fraud and winning new business by providing detailed data and reporting capabilities. Metadata is essential for managing data in a data warehouse. It provides a roadmap to the data, helping users find and understand the information. Metadata must be carefully managed to ensure data accuracy and consistency. Successful data warehouse projects require executive support, a specific business problem to solve, a well-defined plan, proven technology, and experienced people. Careful planning and alignment between the IT department and business users are essential for success. A data warehouse is built to answer specific business problems, not to showcase technology. Using the guidelines outlined here can significantly improve the chances of success.