Abstract: Provided herein is a polymorphic form of Ivacaftor, namely APO-I, as well as processes for the preparation and pharmaceutical compositions of the same. Also, provided is a new solvate of Ivacaftor, processes for its preparation and use in the preparation of pure Ivacaftor.

Abstract: Provided herein is a polymorphic form of Ivacaftor, namely APO-I, as well as processes for the preparation and pharmaceutical compositions of the same. Also, provided is a new solvate of Ivacaftor, processes for its preparation and use in the preparation of pure Ivacaftor.

Abstract: The present invention provides a mobile data communication system which couples application specific remote data sources and mobile devices via an internet based server. An interface is provided by the server for extracting data from the application specific remote data sources. The extracted data is then generalized into generic objects and presented on the mobile devices by device specific application templates.

Abstract: A computer software architecture to automatically optimize the throughput of the data extraction/transformation/loading (ETL) process in data warehousing applications. This architecture has a componentized aspect and a pipeline-based aspect. The componentized aspect refers to the fact that every transformation used in this architecture is built up with transformation components selected from an extensible set of transformation components. Besides simplifying source code maintenance and adjustment for the data warehouse users, these transformation components also provide these users the building blocks to effectively construct pertinent and functionally sophisticated transformations in a pipelined manner. Within a pipeline, each transformation component automatically stages or streams its data to optimize ETL throughput. Furthermore, each transformation either pushes data to another transformation component, pulls data from another transformation component, or performs a push/pull operation on the data.

Abstract: A method for updating a target table of a data mart in response to changes made by a transaction to data stored in a source table of an operational database. Data that was changed in the source table by the transaction is stored in a dynamic image table of a change capture database. Data that was not changed in the source table by the transaction, but which is nevertheless required to be mapped to the target table, is stored in a static image table of the change capture database. The change capture database also contains relevant information regarding the transaction. Once the dynamic and static image tables are properly staged, the changes are propagated from the change capture database to the target tables of the data marts. In other words, data is extracted from the change capture database and subsequently transformed and loaded, thereby minimizing the impact to the operational database. Thereupon, the tables of the change capture database are truncated to discard data which is now no longer needed.

Abstract: A method of performing incremental aggregation of dynamically increasing database data sets. An embodiment of the present invention operates within a data mart or data warehouse to aggregate data stored within an operational database corresponding to newly received data to provide current information. Initially, a computer server creates an intermediate file which is initialized by the server with an aggregate data set. The aggregate data set consists of data values and count values that each correspond to specific group identifiers. The computer determines if any group identifiers within a new set of inputs data are identical to any group identifiers stored within the intermediate file. If an inputted group identifier matches a stored group identifier, the inputted data value is aggregated with the stored data value and the count value corresponding to the specific stored group identifier is incremented by one.