Abstract: A system is described for generating smart advertisements based on a dynamic file and a configuration file over a network. The smart advertisements may adapt to a specific user profile information and available advertising campaign information. The system may select a deal associated with a smart advertisement campaign based on user profile data and create a dynamic file containing specific information related to the deal. The configuration file may contain advertiser specific graphical information to create a tailored and uniform look and feel for each smart advertisement generated for a particular advertiser. The system may select an appropriate graphical template relating to the smart advertisement campaign and create the smart advertisement by applying the dynamic file and the configuration file to the graphical template to create an advertisement tailored to both the user and the advertiser.

Abstract: A system is described for generating smart advertisements based on a dynamic file and a configuration file over a network. The smart advertisements may adapt to a specific user profile information and available advertising campaign information. The system may select a deal associated with a smart advertisement campaign based on user profile data and create a dynamic file containing specific information related to the deal. The configuration file may contain advertiser specific graphical information to create a tailored and uniform look and feel for each smart advertisement generated for a particular advertiser. The system may select an appropriate graphical template relating to the smart advertisement campaign and create the smart advertisement by applying the dynamic file and the configuration file to the graphical template to create an advertisement tailored to both the user and the advertiser.

Abstract: A system is described for optimizing the performance of smart advertisements generated over a network for display to a user. The smart advertisements may adapt to specific user profile information and available advertising campaign information. The system may consume log data relating to previously displayed smart advertisements and compare the performance rates of the smart advertisements to determine relationships between controllable variables and the performance rates. The system may manipulate the controllable variables based on the relationships to optimize the performance of smart advertisements.

Abstract: A system is described for generating smart advertisements to display to a user over a network. The smart advertisements may adapt to specific user profile information and available advertising campaign information. The system may select a smart advertisement campaign and one or more deals associated with the smart advertisement campaign that match the user profile. The system may select an appropriate graphical component relating to the smart advertisement campaign and create the smart advertisement by applying the user profile data and deal attributes to the graphical component and display the specific smart advertisement to the user.

Abstract: A method and system for accessing and sharing metadata amongst a number of data marts through the use of object referencing. A global repository is created. Shared folders containing metadata is contained in the global repository. Any number of data marts can be linked to the global repository. Stored within the folders of the linked data marts are references pointing to certain metadata stored in the shared folders of the global repository. Multiple data marts can reference the same metadata in the global repository. Thereby, the same metadata can be accessed, used, and shared by multiple users across different data marts, provided that they have been granted the proper authority. New metadata can be promoted from a linked data mart into the global repository so that it can be shared, and updates to shared metadata can be automatically propagated to all users referencing that metadata.

Abstract: A transformation description language (TDL) for specifying how data is to be manipulated in a data warehousing application. The TDL is comprised of a source for storing raw data, one or more transformation objects for processing the raw data according to predefined instructions, and a target for storing the processed data. A mapping is used for directing the data flow between the I/O ports corresponding to the source, the plurality of transformation objects, and the target. The mapping specifies the connectivity between the source, transformation, and target objects as well as the order of these connections. There are a number of different transformations which can be performed to manipulate the data. Some such transformations include: an aggregator transformation, an expression transformation, a filter transformation, a lookup transformation, a query transformation, a sequence transformation, a stored procedure transformation, and an update strategy transformation.