This article focuses on the tough questions that a project manager has to ask to their companies executives and themselves as to building a data warehouse. A data warehouse solution needs flexibility and scalability to change with the business it is intended to support. Flexibility is generally viewed from the architectural standpoint of a physical model based on third normal form (3NF). An architecture which is not based on the 3NF model can be the cause for the failure of a data warehouse project. The obstacles that has to be overcome while building data warehouse are informational versus operational data and framework and methodology. Operational data is organized around functional organizations within a business. Functionally oriented data is used to satisfy the immediate functional processing requirements of the business user. For a successful implementation of a data warehouse a proven framework or a blueprint is required. The three basic steps required to build a warehouse is planning, design and implementation and support and enhancement. In data warehousing, metadata refers to anything that defines a data warehouse object, such as a table, a column, a query, a report, a business rule, or a transformation algorithm. Building a warehouse is a complex process requiring careful planning and alignment between the IT department and business users.
Stored only when both papers are in the corpus — 461 citations exist upstream.