Abstract: A computer implemented method of generating graphics video data for a computer game is disclosed. The method comprises receiving, from a remote device (601), first data including image data corresponding to a plurality of pixels of at least one frame of video data of the computer game. Second data, including colour data of a plurality of said pixels, and at least one frame of video data of the computer game based on the first and second data, are generated at a user device (602).

Abstract: A computer-implemented method of executing a distributed processing scheme, the method comprising receiving, at a first computing device, a first request associated with a processing task, identifying a plurality of computing devices, wherein each computing device of the plurality of computing devices is remote from the first computing device and each computing device satisfies at least one criterion of a predetermined list of criteria, determining a priority value for each computing device, wherein the priority value is at least partially based on the predetermined list of criteria, selecting one of the computing devices, wherein the selection is determined at least partially based on the priority value determined for each computing device, sending a second request from the first computing device to the selected computing device via a wireless communication channel, the second request instructing the selected computing device to complete a portion of the processing task.

Abstract: A business intelligence (BI) document preserves references to identities and formats of remote data sources and allows a local computing device to offload analytical operations to remote data sources. The BI document specifies a graph of entities connected by directed edges from the output of one entity to an input of another entity. An entity, for example, can represent without limitation a data structure, an external data source, a control element, an external event source, a visualization, or an update service. The entities of a BI document at a local computing device can reference data at an original data source—rather than extracting data from the original data source to a preferred local datastore. An entity of the BI document can direct a remote data source to execute transformations on the remote data before returning a solution to the local computing device.

Abstract: A business intelligence document provides functionality for testing a hypothesis on aggregated data in a business intelligence document (e.g., a spreadsheet-like document), wherein one or more of the input data values and transformation properties are designated as constrained (e.g., invariant or constrained within a range, set, enumeration, or domain). The hypothesis, which is articulated as a data mining assertion, is input through the user interface of the business intelligence document (e.g., via an expression interface or properties of a row, column, or cell) and solved over the aggregated data. The solution is then presented through the user interface of the spreadsheet-like document, such as in a table, graph, histogram, etc.

Abstract: A business intelligence document provides functionality for testing a hypothesis on aggregated data in a business intelligence document (e.g., a spreadsheet-like document), wherein one or more of the input data values and transformation properties are designated as constrained (e.g., invariant or constrained within a range, set, enumeration, or domain). The hypothesis, which is articulated as a data mining assertion, is input through the user interface of the business intelligence document (e.g., via an expression interface or properties of a row, column, or cell) and solved over the aggregated data. The solution is then presented through the user interface of the spreadsheet-like document, such as in a table, graph, histogram, etc.

Abstract: A business intelligence (BI) document preserves references to identities and formats of remote data sources and allows a local computing device to offload analytical operations to remote data sources. The BI document specifies a graph of entities connected by directed edges from the output of one entity to an input of another entity. An entity, for example, can represent without limitation a data structure, an external data source, a control element, an external event source, a visualization, or an update service. The entities of a BI document at a local computing device can reference data at an original data source—rather than extracting data from the original data source to a preferred local datastore. An entity of the BI document can direct a remote data source to execute transformations on the remote data before returning a solution to the local computing device.

Abstract: A business intelligence document provides functionality for testing a hypothesis on aggregated data in a business intelligence document (e.g., a spreadsheet-like document), wherein one or more of the input data values and transformation properties are designated as constrained (e.g., invariant or constrained within a range, set, enumeration, or domain). The hypothesis, which is articulated as a data mining assertion, is input through the user interface of the business intelligence document (e.g., via an expression interface or properties of a row, column, or cell) and solved over the aggregated data. The solution is then presented through the user interface of the spreadsheet-like document, such as in a table, graph, histogram, etc.

Abstract: A business intelligence (BI) document preserves references to identities and formats of remote data sources and allows a local computing device to offload analytical operations to remote data sources. The BI document specifies a graph of entities connected by directed edges from the output of one entity to an input of another entity. An entity, for example, can represent without limitation a data structure, an external data source, a control element, an external event source, a visualization, or an update service. The entities of a BI document at a local computing device can reference data at an original data source—rather than extracting data from the original data source to a preferred local datastore. An entity of the BI document can direct a remote data source to execute transformations on the remote data before returning a solution to the local computing device.

Abstract: A business intelligence document provides functionality for testing a hypothesis on aggregated data in a business intelligence document (e.g., a spreadsheet-like document), wherein one or more of the input data values and transformation properties are designated as constrained (e.g., invariant or constrained within a range, set, enumeration, or domain). The hypothesis, which is articulated as a data mining assertion, is input through the user interface of the business intelligence document (e.g., via an expression interface or properties of a row, column, or cell) and solved over the aggregated data. The solution is then presented through the user interface of the spreadsheet-like document, such as in a table, graph, histogram, etc.

Abstract: A business intelligence (BI) document preserves references to identities and formats of remote data sources and allows a local computing device to offload analytical operations to remote data sources. The BI document specifies a graph of entities connected by directed edges from the output of one entity to an input of another entity. An entity, for example, can represent without limitation a data structure, an external data source, a control element, an external event source, a visualization, or an update service. The entities of a BI document at a local computing device can reference data at an original data source—rather than extracting data from the original data source to a preferred local datastore. An entity of the BI document can direct a remote data source to execute transformations on the remote data before returning a solution to the local computing device.