Abstract: A system for joining modeled data with new data sources. Modeled tabular data containing categorical and metric data is received. New data containing structured or non-structured data is received. The new data is indexed and data clusters and/or data facets are identified. Data clusters and data facets are also identified within the received modeled data. A textual query from a user is received and semantically indexed into keywords. Data clusters and data facets within the new data are matched to the keywords in the indexed query. Data clusters and data facets within in the modeled data are matched to the keywords in the indexed query. A table is generated containing the modeled data and matching data clusters and data facets from the new data.

Abstract: A system for joining modeled data with new data sources. Modeled tabular data containing categorical and metric data is received. New data containing structured or non-structured data is received. The new data is indexed and data clusters and/or data facets are identified. Data clusters and data facets are also identified within the received modeled data. A textual query from a user is received and semantically indexed into keywords. Data clusters and data facets within the new data are matched to the keywords in the indexed query. Data clusters and data facets within in the modeled data are matched to the keywords in the indexed query. A table is generated containing the modeled data and matching data clusters and data facets from the new data.

Abstract: A system for joining modeled data with new data sources. Modeled tabular data containing categorical and metric data is received. New data containing structured or non-structured data is received. The new data is indexed and data clusters and/or data facets are identified. Data clusters and data facets are also identified within the received modeled data. A textual query from a user is received and semantically indexed into keywords. Data clusters and data facets within the new data are matched to the keywords in the indexed query. Data clusters and data facets within in the modeled data are matched to the keywords in the indexed query. A table is generated containing the modeled data and matching data clusters and data facets from the new data.

Abstract: A system for joining modeled data with new data sources. Modeled tabular data containing categorical and metric data is received. New data containing structured or non-structured data is received. The new data is indexed and data clusters and/or data facets are identified. Data clusters and data facets are also identified within the received modeled data. A textual query from a user is received and semantically indexed into keywords. Data clusters and data facets within the new data are matched to the keywords in the indexed query. Data clusters and data facets within in the modeled data are matched to the keywords in the indexed query. A table is generated containing the modeled data and matching data clusters and data facets from the new data.

Abstract: A multidimensional query results processing system for translating output of an execution of a multidimensional query into a data result set that reflects the semantics of an entity/relationship schema report specification is provided. The system comprises a result set description generation module for producing a result set description that reflects the semantics of the report specification, a tabular row generation module for converting the results of the single multi-dimensional query into a collection of rows of data, a tabular summary level calculation module for calculating a summarization level of a row a data, a tabular header row generation module for producing a header row to include in the row of data, and a cross-tabulated result generation module for converting the results of the single multi-dimensional query into a result set that matches the semantics of the report specification.

Abstract: A mechanism for summary filter transformation is provided. The mechanism comprises a summary filter analysis module for analyzing a multidimensional query that is not supported by a target database system, and a summary filter transformation module for transforming the multidimensional query into a semantically equivalent query that is supported by the target database system.

Abstract: A method of transforming queries based upon an entity/relationship schema into multi-dimensional expression queries is provided. The method comprises matching an object referenced in an entity/relationship schema based report specification to a corresponding object in the entity/relationship schema, the corresponding object adorned with associated multidimensional metadata; adding the associated multi-dimensional metadata to the object referenced in the entity/relationship schema based report specification; translating the entity/relationship schema based report specification into a multi-dimensional expression query; and retrieving directly all data required to populate a report output of the entity/relationship schema report specification.

Abstract: A system for transforming queries based upon entity/relationship schema into multi-dimensional expression queries is provided. The system comprises a binding module for matching an object reference in a report specification to a corresponding entity/relationship schema object and adding associated multi-dimensional metadata information from the entity/relationship schema to a corresponding report specification object, and a query translation module for translating the report specification into a single multi-dimensional query.

Abstract: A multidimensional query results processing system for translating output of an execution of a multidimensional query into a data result set that reflects the semantics of an entity/relationship schema report specification is provided. The system comprises a result set description generation module for producing a result set description that reflects the semantics of the report specification, a tabular row generation module for converting the results of the single multi-dimensional query into a collection of rows of data, a tabular summary level calculation module for calculating a summarization level of a row a data, a tabular header row generation module for producing a header row to include in the row of data, and a cross-tabulated result generation module for converting the results of the single multi-dimensional query into a result set that matches the semantics of the report specification.