Abstract: Providing predictive data predicting data values for a historical dataset. The method facilitates improving the accuracy of the predictive data by identifying for a user, and allowing the user to select ancillary datasets that can be evaluated, using a predictive evaluation, together with a historical dataset to improve the accuracy of the predictive data. A user interface is provided to a user. The user interface identifies one or more ancillary datasets. The ancillary datasets are identified to the user based on the ancillary datasets meeting a threshold condition to a historical dataset. The ancillary datasets are selectable by the user in the user interface. User input is received at the user interface selecting one or more of the ancillary datasets. A predictive dataset is displayed to the user. The predictive dataset is determined by predictive evaluation of the historical dataset and the one or more selected ancillary datasets.

Abstract: Various technologies pertaining to modifying visualizations are described herein. A client computing device requests a visualization from a server computing device, and the server computing device constructs the visualization responsive to receipt of the request. The server computing device further identifies anticipated transformations for the visualization, and transmits the visualization and the transformations to the client computing device. The client computing device displays the visualization, and responsive to receipt of a request to modify the visualization, executes a transformation provided by the server computing device to update the visualization.

Abstract: Various technologies pertaining to modifying visualizations are described herein. A client computing device requests a visualization from a server computing device, and the server computing device constructs the visualization responsive to receipt of the request. The server computing device further identifies anticipated transformations for the visualization, and transmits the visualization and the transformations to the client computing device. The client computing device displays the visualization, and responsive to receipt of a request to modify the visualization, executes a transformation provided by the server computing device to update the visualization.

Abstract: Providing predictive data predicting data values for a historical dataset. The method facilitates improving the accuracy of the predictive data by identifying for a user, and allowing the user to select ancillary datasets that can be evaluated, using a predictive evaluation, together with a historical dataset to improve the accuracy of the predictive data. A user interface is provided to a user. The user interface identifies one or more ancillary datasets. The ancillary datasets are identified to the user based on the ancillary datasets meeting a threshold condition to a historical dataset. The ancillary datasets are selectable by the user in the user interface. User input is received at the user interface selecting one or more of the ancillary datasets. A predictive dataset is displayed to the user. The predictive dataset is determined by predictive evaluation of the historical dataset and the one or more selected ancillary datasets.

Abstract: Architecture that includes optimizations for “Bump-in-the-API” (BIA) as employed for multi-stack hosts. These optimizations reduce the limitations imposed by the existing translation technologies by simplifying the implementation and addressing possible compatibility issues. More specifically, the architecture discloses optimizations that use a preconfigured NAT64 prefix for mapping of NAT64 IPv6 addresses in the prefix subnet to IPv4 addresses, without a mapping table (stateless), use configuration information for enabling API translation per application (resolves possible compatibility issues), and use a local IPv4 socket and a data pump to reduce the number of translated API calls.

Abstract: Architecture that includes optimizations for “Bump-in-the-API” (BIA) as employed for multi-stack hosts. These optimizations reduce the limitations imposed by the existing translation technologies by simplifying the implementation and addressing possible compatibility issues. More specifically, the architecture discloses optimizations that use a preconfigured NAT64 prefix for mapping of NAT64 IPv6 addresses in the prefix subnet to IPv4 addresses, without a mapping table (stateless), use configuration information for enabling API translation per application (resolves possible compatibility issues), and use a local IPv4 socket and a data pump to reduce the number of translated API calls.

Abstract: Aspects of the subject matter described herein relate to sharing policy and workload among network access devices. In aspects, a network access device receives a communication between a first and a second node. The network access device may be one of a set of network access devices responsible for processing traffic to and from a set of nodes. A network access device determines a policy to apply to the communication and at least one network device to apply the policy. The determination of the at least one network device to apply the policy may include determining which network access devices are capable of applying the policy as well as the workload on the network access devices.