Data-Warehouse Principles for Supporting Enterprise-Enabled Business-Intelligence Applications

Summary: This article focuses on the design principles to support a global data-warehouse (DW) architecture, the golden triumph of any successful business-intelligence (BI) application story. It draws from the Microsoft Global independent software-vendor (ISV) partner experience in designing enterprise BI applications by using Microsoft platform technologies and contains external links and references to public content that delves deeper into the design topics that are covered.

This article assumes that the reader has some basic DW understanding of a dimensional store, the underlying fact tables in which columns are known as measures, dimension tables in which columns are known as attributes, and how schemas take on star and snowflake patterns. There are many available resources to provide this overview; however, if needed, a concise overview can be found here: http://www.simple-talk.com/sql/learn-sql-server/sql-server-data-warehouse-cribsheet. This article focuses also on successful DW project strategies and advanced topics of effective design for performance.