Abstract: A business intelligence (BI) server maintains a plurality of metadata objects to support the extract, transform and load (ETL) processes. These metadata objects includes a transparent view object, which takes a joined set of source tables and represents a data shape of the joined set of source tables using a transformation, and a ETL mapping association object that maps the transformation contained in the transparent view object to a target table. The BI server can then orchestrate the movement of data from source systems into the target data warehouses in a source and target system agnostic way.

Abstract: An administration tool can be used to provide data flexibility in a business intelligence (BI) server that is associated with a data warehouse. The administration tool can display one or more data objects that are adapted to be imported from an application framework into a physical model maintained on the BI server. The administration tool can further map the one or more data objects in the physical model into a logical model, also maintained on the BI server, which corresponds to at least one target table in the data warehouse. Additionally, the administration tool can publish an extension input to an extender associated with the data warehouse based on the logical model, wherein the extender operates to generate one or more metadata extensions based on the extension input.

Abstract: An input extension specification can be generated, via an administration tool on a business intelligence (BI) server, for an extender associated with a data warehouse in order to extend the data warehouse. The administration tool can request for data flow information of the data warehouse from the extender. The data flow information indicates the mapping relationship between one or more source data objects and one or more target tables in the data warehouse. The administration tool further allows a user to select said one or more target tables in the data warehouse to be extended based on the data flow information, and builds the input extension specification for the extender.

Abstract: Systems and methods are described for automating the creation of data marts within an enterprise. Data is maintained in a plurality of data sources that include at least a relational database and a multidimensional database. The system includes a business intelligence server that provides a virtual logical semantic model to integrate all of the plurality of data sources. The user specifies a list of levels and measures on the virtual logical semantic model. The list of levels and measures can span data from multiple data sources. The user can also specify a location in the plurality of data sources that will store the aggregate matrix. Once the list of levels and measures are specified, the business intelligence server generates a multidimensional cube to store the data for the aggregate matrix and stores the multidimensional cube in the data source location.

Abstract: Systems and methods are described for performing a SQL bypass in a business intelligence (BI) server environment. The BI server initially receives a SQL query and constructs an extensible markup language (XML) representation of the SQL query. The XML representation is sent to an application server that hosts an application developer framework (ADF). The ADF receives the XML representation of the SQL query and constructs a composite view object at runtime, to access the appropriate data. It then generates a database-specific query based on the composite view object and returns it to the BI server. The BI server replans the database-specific query and sends it to a database storing the data.

Abstract: An extender associated with a data warehouse can support metadata extension for the data warehouse. The extender can create an ETL extension plan for extending the data warehouse. The ETL extension plan includes one or more ETL plan elements that indicate extensions on ETL metadata objects. The one or more ETL plan elements within the ETL extension plan can be ordered, and ETL metadata extension can be performed based on the ETL extension plan.

Abstract: An input extension specification can be generated, via an administration tool on a business intelligence (BI) server, for an extender associated with a data warehouse in order to extend the data warehouse. The administration tool can request for data flow information of the data warehouse from the extender. The data flow information indicates the mapping relationship between one or more source data objects and one or more target tables in the data warehouse. The administration tool further allows a user to select said one or more target tables in the data warehouse to be extended based on the data flow information, and builds the input extension specification for the extender.

Abstract: A business intelligence (BI) server maintains a plurality of metadata objects to support the extract, transform and load (ETL) processes. These metadata objects includes a transparent view object, which takes a joined set of source tables and represents a data shape of the joined set of source tables using a transformation, and a ETL mapping association object that maps the transformation contained in the transparent view object to a target table. The BI server can then orchestrate the movement of data from source systems into the target data warehouses in a source and target system agnostic way.

Abstract: A scorecard application can support business strategy management using a business intelligence (BI) server. The BI server can take inputs from different data sources. The scorecard application can define an internal data structure that holds a plurality of strategy components and one or more key performance indicators (KPIs). Then, the scorecard application can populate each said strategy component in the internal data structure based on the inputs from the different data sources, and perform one or more actions once an alert is triggered, wherein the alert is triggered when a said KPI meets one or more criteria.

Abstract: Systems and methods are described for automating the creation of data marts within an enterprise. Data is maintained in a plurality of data sources that include at least a relational database and a multidimensional database. The system includes a business intelligence server that provides a virtual logical semantic model to integrate all of the plurality of data sources. The user specifies a list of levels and measures on the virtual logical semantic model. The list of levels and measures can span data from multiple data sources. The user can also specify a location in the plurality of data sources that will store the aggregate matrix. Once the list of levels and measures are specified, the business intelligence server generates a multidimensional cube to store the data for the aggregate matrix and stores the multidimensional cube in the data source location.

Abstract: Systems and methods are described for performing a SQL bypass in a business intelligence (BI) server environment. The BI server initially receives a SQL query and constructs an extensible markup language (XML) representation of the SQL query. The XML representation is sent to an application server that hosts an application developer framework (ADF). The ADF receives the XML representation of the SQL query and constructs a composite view object at runtime, to access the appropriate data. It then generates a database-specific query based on the composite view object and returns it to the BI server. The BI server replans the database-specific query and sends it to a database storing the data.

Abstract: An administration tool can be used to provide data flexibility in a business intelligence (BI) server that is associated with a data warehouse. The administration tool can display one or more data objects that are adapted to be imported from an application framework into a physical model maintained on the BI server. The administration tool can further map the one or more data objects in the physical model into a logical model, also maintained on the BI server, which corresponds to at least one target table in the data warehouse. Additionally, the administration tool can publish an extension input to an extender associated with the data warehouse based on the logical model, wherein the extender operates to generate one or more metadata extensions based on the extension input.

Abstract: An extender associated with a data warehouse can support metadata extension for the data warehouse. The extender can create an ETL extension plan for extending the data warehouse. The ETL extension plan includes one or more ETL plan elements that indicate extensions on ETL metadata objects. The one or more ETL plan elements within the ETL extension plan can be ordered, and ETL metadata extension can be performed based on the ETL extension plan.