Abstract: A method of defining a well-formed database system by defining the organization of the data in the database, and by defining the operations for that data, is described. The definition can be used to automatically create and populate the well-formed database system. The well-formed database system conforms to rules of correctness and produces results that conform to the rules. The organization is defined by a data organization definition that specifies tables, their columns, and the relationships between tables. The operations define procedures that operate on the tables and the table columns. Importantly, the operations are defined along with the tables, columns, and relationships, so that the resulting system is well-formed.

Abstract: A method of defining a well-formed database system by defining the organization of the data in the database, and by defining the operations for that data, is described. The definition can be used to automatically create and populate the well-formed database system. The well-formed database system conforms to rules of correctness and produces results that conform to the rules. The organization is defined by a data organization definition that specifies tables, their columns, and the relationships between tables. The operations define procedures that operate on the tables and the table columns. Importantly, the operations are defined along with the tables, columns, and relationships, so that the resulting system is well-formed.

Abstract: A method of generating a datamart is described. The datamart includes tables having rows and columns. The method comprises accessing a description of a schema. The schema defines the relationships between the tables and columns. The description further defines how data is to be manipulated and used to populate the tables in the datamart. That is, the description defines the semantic meaning of the data. The description is further used to create a set of commands to create the tables. The commands are executed causing the creation of the tables. Importantly, when the semantic meaning is associated with the column and rows, programs for manipulating and propagating data into those columns and rows are automatically defined. Previously, consultants would have to hand code the creation, manipulation, and population programs for a datamart. Thus, the amount of work required to create and populate the datamart is significantly reduced.

Abstract: A method of defining in a computer system a subset of entries in a database is described. The subset is defined by a query. The method includes displaying an interface having a number of criteria description locations. The criteria description locations being positioned in rows where each row has one or more columns. The method also includes creating a criteria description in the interface. The criteria description corresponds to criteria, where the criteria define a corresponding subset of the database. Importantly, the relative location of the criteria description in the user interface determines how the criteria contribute to the selectivity of the query.

Abstract: A method for automatically defining aggregates for use in a datamart is described. The datamart includes fact and dimension tables. The method comprises accessing a schema description and an aggregates description for the datamart. The schema description specifies a schema, which in turn, defines the relationships between the fact tables and dimension tables of the datamart. The aggregates description specifies the aggregates, which define, from the schema definition, which aggregate tables are to be created from the fact tables and dimension tables in the datamart. The data in the aggregates correspond to the pre-computed results of specific types of queries. In response to a query, the aggregates can be searched to determine an appropriate aggregate to use in response to that query. The schema description is used to create a first set of commands to create and populate the fact and dimension tables.