Abstract: Systems, methods, and other embodiments associated with dynamic inclusion of custom columns into a logical model are described. In one embodiment, a method includes: accepting a mapping between a placeholder logical column of a static logical model and a custom physical column; generating an enriched dataset that combines a description of the custom physical column with values of the custom physical column; placing the enriched dataset into the placeholder logical column; and presenting the static logical model with the enriched dataset in the placeholder logical column.

Abstract: Embodiments autonomously test a logical model for inconsistencies. For example, metadata descriptive of a logical model can be received, where the logical model includes an abstraction for a database schema, the database schema is implemented at a database, and the database schema includes a fact table and a dimension table. Logical queries can be automatically generated including at least first and second logical queries based on the retrieved metadata, where the first and second logical queries target a logical object of the logical model. At least the first and second logical queries can be issued to a server that hosts the logical model, where, at the server, the first and second logical queries are translated to first and second database queries, and the first and second database queries target at least a fact table and a dimension table from the database schema. Query results received from execution of the first and second database queries can be compared.

Abstract: Embodiments autonomously test a logical model for inconsistencies. For example, metadata descriptive of a logical model can be received, where the logical model includes an abstraction for a database schema, the database schema is implemented at a database, and the database schema includes a fact table and a dimension table. Logical queries can be automatically generated including at least first and second logical queries based on the retrieved metadata, where the first and second logical queries target a logical object of the logical model. At least the first and second logical queries can be issued to a server that hosts the logical model, where, at the server, the first and second logical queries are translated to first and second database queries, and the first and second database queries target at least a fact table and a dimension table from the database schema. Query results received from execution of the first and second database queries can be compared.

Abstract: Embodiments provide systems and methods for learning extract, transform, and load mappings by example. A plurality of features can be extracted from a source schema and a target schema. Example ETL mappings can be provided to a machine learning algorithm that comprise definitions for extracting data from source tables and loading the extracted data into target tables. Using the machine learning algorithm and based on the source schema, target schema, and extracted features, one or more ETL rules can be predicted that define logic for extracting data from the source schema and loading the extracted data into the target schema. Additional ETL mappings can be generated based on the predicted ETL rules, the additional ETL mappings providing additional definitions for extracting data from the source schema and loading the extracted data into the target schema.

Abstract: Systems, methods, and other embodiments associated with dynamic inclusion of custom columns into a logical model are described. In one embodiment, a method includes: accepting a mapping between a placeholder logical column of a static logical model and a custom physical column; generating an enriched dataset that combines a description of the custom physical column with values of the custom physical column; placing the enriched dataset into the placeholder logical column; and presenting the static logical model with the enriched dataset in the placeholder logical column.

Abstract: Embodiments autonomously test a logical model for inconsistencies. For example, metadata descriptive of a logical model can be received, where the logical model includes an abstraction for a database schema, the database schema is implemented at a database, and the database schema includes a fact table and a dimension table. Logical queries can be automatically generated including at least first and second logical queries based on the retrieved metadata, where the first and second logical queries target a logical object of the logical model. At least the first and second logical queries can be issued to a server that hosts the logical model, where, at the server, the first and second logical queries are translated to first and second database queries, and the first and second database queries target at least a fact table and a dimension table from the database schema. Query results received from execution of the first and second database queries can be compared.

Abstract: Systems, methods, and other embodiments associated with dynamic inclusion of custom columns into a logical model are described. In one embodiment, a method includes mapping a selected custom logical column in the logical model to a custom physical column represented as a row in a physical table in real time by assigning a column sequence identifier uniquely associated with the selected custom logical column to the custom physical column; retrieving a custom column definition for the custom physical column in real time to form an enriched dataset of custom column records; pivoting the enriched dataset into the selected custom logical column in real time to integrate the custom logical column into the logical model; and presenting the logical model including the mapped custom logical columns for access in a business intelligence environment.

Abstract: Systems, methods, and other embodiments associated with dynamic inclusion of custom columns into a logical model are described. In one embodiment, a method includes mapping a selected custom logical column in the logical model to a custom physical column represented as a row in a physical table in real time by assigning a column sequence identifier uniquely associated with the selected custom logical column to the custom physical column; retrieving a custom column definition for the custom physical column in real time to form an enriched dataset of custom column records; pivoting the enriched dataset into the selected custom logical column in real time to integrate the custom logical column into the logical model; and presenting the logical model including the mapped custom logical columns for access in a business intelligence environment.

Abstract: Embodiments provide systems and methods for learning extract, transform, and load mappings by example. A plurality of features can be extracted from a source schema and a target schema. Example ETL mappings can be provided to a machine learning algorithm that comprise definitions for extracting data from source tables and loading the extracted data into target tables. Using the machine learning algorithm and based on the source schema, target schema, and extracted features, one or more ETL rules can be predicted that define logic for extracting data from the source schema and loading the extracted data into the target schema. Additional ETL mappings can be generated based on the predicted ETL rules, the additional ETL mappings providing additional definitions for extracting data from the source schema and loading the extracted data into the target schema.

Abstract: Automatic generation of logical database schemas from physical database tables and metadata is disclosed. One exemplary method for automatic generation of logical database schemas from physical database tables and metadata includes identifying physical fact tables in a data repository. The method further includes identifying physical dimension tables in the data repository. The method includes mapping the physical fact tables to logical fact tables. The method further includes mapping the physical dimension tables to logical dimension tables. The method further includes determining relationships between the physical fact and dimension tables. The method further includes logically joining the logical tables based on the identified relationships between the physical tables to form a logical database schema. The method further includes outputting the logical database schema to the user.

Abstract: Automatic generation of logical database schemas from physical database tables and metadata is disclosed. One exemplary method for automatic generation of logical database schemas from physical database tables and metadata includes identifying physical fact tables in a data repository. The method further includes identifying physical dimension tables in the data repository. The method includes mapping the physical fact tables to logical fact tables. The method further includes mapping the physical dimension tables to logical dimension tables. The method further includes determining relationships between the physical fact and dimension tables. The method further includes logically joining the logical tables based on the identified relationships between the physical tables to form a logical database schema. The method further includes outputting the logical database schema to the user.

Abstract: Various embodiments of the present invention are directed to providing a user the ability to self-declare one or more permission attributes about the user that form the basis for the filtering (e.g., the dynamic filtering) of current and/or future content. In this manner, access to the content may thus be governed by the self-declared permission attributes (in one example (which example is intended to be illustrative and not restrictive), the present invention may operate within a secure, tracked content delivery infrastructure).

Abstract: Various embodiments of the present invention are directed to providing a user the ability to self-declare one or more permission attributes about the user that form the basis for the filtering (e.g., the dynamic filtering) of current and/or future content. In this manner, access to the content may thus be governed by the self-declared permission attributes (in one example (which example is intended to be illustrative and not restrictive), the present invention may operate within a secure, tracked content delivery infrastructure).

Abstract: The communications system has a communications terminal that transmits status data to a remote computer. The remote computer processes a program that generates an instruction sequence on the basis of the status data. The instruction sequence is processed by a central controller of the communications terminal as a program section.

Abstract: A web-based call center and a method for its operation include multiple agent and customer terminals connected to a web server. The agent terminals and the customer terminals include a web browser for accessing web documents from the web server and annotation plug-in software for recording and replaying static and dynamic annotations on web documents. An HTML document registration tool formats web documents prior to storage on the web server, so that the web documents are formatted for annotation. An annotation server includes a database for storing annotated documents received from agent and customer terminals. Indexing software associated with the annotation server extracts key information from annotations received from customer terminals as part of callback requests. The extracted key information is indicative of a skills set which is required by an agent in order to handle the callback request. An ACD server utilizes the key information to route callback requests to qualified call center agents.

Abstract: A system and method for supporting an interactive decision tree with placeholder capability include an interactive decision tree-based expert unit with an input enabled to receive user data that includes a user identification and with an output enabled to transmit system data. A memory is connected to the expert unit for storing the system data. Optionally, the user memory stores the identification and an associated decision tree node identifier representing a node in the decision tree visited by a user prior to termination of a communications link between the expert unit and the user. A device is provided for accessing the decision tree node identifier from the memory utilizing the associated user identification, so that a connecting device can automatically connect the user to a node within the decision tree based solely upon the user identification. Alternatively, the decision tree node identifier is transmitted to the user.

Abstract: A user interface is organized using different personae. When in a master persona mode, a user is provided access to a full list of contacts and to a full set of data files. When in a first alternate persona mode, user access is provided to only a first subset of the full list of contacts and to only a first subset of the full set of data files.

Abstract: An automatic call distribution system utilizes a number of H.323 compatible devices. An automatic call distribution (ACD) server (52) interfaces with a computer telephony interface gateway (54) to route calls to agents or to a music/video server (56). Calls are received by a gateway and supplied to a gatekeeper that determines an IP address of the destination. The ACD server selects the destination in response to the number of agents available. In addition, customer calls can be received via e-mail, facsimile or the Internet. The call distribution system can instruct an agent to return an e-mail or facsimile message or to call a customer if desired. Calls from one H.323 device can be routed to another H.323 device by a third party application by sending a call control message to the device's application program interface that executes the message as if it were generated at the device itself.

Abstract: A user interface is organized using different personae. When in a master persona mode, a user is provided access to a full list of contacts and to a full set of data files. When in a first alternate persona mode, user access is provided to only a first subset of the full list of contacts and to only a first subset of the full set of data files.

Abstract: The present invention relates to a call forwarding system for forwarding telephone calls to a target telephone not having a direct dial number. The call forwarding system includes an intelligent forwarding unit for storing a forwarding direct dial number and the extension number for accessing the target telephone and for connecting the received forwarded call to the target telephone, a voice response unit including a DTMF decoder for receiving the forwarded telephone call and for decoding the extension number of the target telephone. A call connecting unit directly connects the in-coming telephone call to the target telephone.