Towards Business Intelligence over Unified Structured and Unstructured Data Using XML

Traditional data warehousing has been very successful in helping business enterprises to make intelligent decisions through declarative analysis of large amount of structured data stored in a relational database. However, not all enterprise data naturally fit into a relational model. Within an enterprise, there are huge amount of unstructured data, such as document content, emails, spreadsheets, that do not have a fixed schema, or have a very sparse or loose schema that cannot be effectively modeled using relational model. Yet, like relational data, unstructured data record many useful facts that are equally essential and important to be analyzed by businesses to make intelligent decisions. In this chapter, we propose an XML-enabled RDBMS that uses XML as the underlying logical data model to uniformly represent both well-structured relational data, semi-structured and unstructured data in building an enterprise data warehouse that is able to store and analyze any data regardless of existence of schema or not. We show how XQuery used in SQL/XML as a declarative language to do data query, analysis and transformation over both structured data and unstructured content in the data warehouse. We present the rationale for using XML as the logical data model for unified data warehouse query, XML extended inverted text index to integrate structured data query and context aware full text search for unstructured content so as to support efficient data analysis over large volume of structured and unstructured data. We argue that the technical approach of using XML to unify both structured and unstructured data in a warehouse has the potential to push business intelligence over all enterprise data to a new era.