Abstract: A data query and retrieval system receives a query request and identifies a plurality of data warehouses, or stores, where data needed to satisfy the query is stored. Data items, or fields, called for by the query request are grouped into sets based on fields stored at the same data warehouse. Individual data connections are generated for each data warehouse accessed, and a database view defined for the fields available at each respective data warehouse. The individual views are invoked in a single query statement by a query processor for accessing the respective data warehouses via the corresponding database view. In this manner, a query operator or user need not define multiple query expressions or perform separate queries for accessing data fields or dimensions residing at different data warehouses.

Abstract: A multidimensional database query engine processes a query request by forming a logical plan of subqueries for retrieving and assembling the data called for by the query request. A multi-pass analysis identifies a granularity of facts needed to fulfill the query request. A recursive analysis parses the query request and identifies components comprising the full query request. The analysis derives a subquery from each component, and identifies dependencies on other subqueries. The subqueries are arranged in a tree structure based on the dependencies. The tree represents subqueries as nodes, with query operations denoted by parent nodes for the dependent subqueries. The result is a hierarchical tree of subqueries associated based on operations between the subqueries and dependent subqueries descending from their parent subqueries.

Abstract: A data query and retrieval system receives a query request and identifies a plurality of data warehouses, or stores, where data needed to satisfy the query is stored. Data items, or fields, called for by the query request are grouped into sets based on fields stored at the same data warehouse. Individual data connections are generated for each data warehouse accessed, and a database view defined for the fields available at each respective data warehouse. The individual views are invoked in a single query statement by a query processor for accessing the respective data warehouses via the corresponding database view. In this manner, a query operator or user need not define multiple query expressions or perform separate queries for accessing data fields or dimensions residing at different data warehouses.

Abstract: A multidimensional database query engine processes a query request by forming a logical plan of subqueries for retrieving and assembling the data called for by the query request. A multi-pass analysis identifies a granularity of facts needed to fulfill the query request. A recursive analysis parses the query request and identifies components comprising the full query request. The analysis derives a subquery from each component, and identifies dependencies on other subqueries. The subqueries are arranged in a tree structure based on the dependencies. The tree represents subqueries as nodes, with query operations denoted by parent nodes for the dependent subqueries. The result is a hierarchical tree of subqueries associated based on operations between the subqueries and dependent subqueries descending from their parent subqueries.