Abstract:
Examples of auto-monitoring and adjusting dynamic data visualizations are provided herein. A data visualization based on initial data can be generated. A series of data updates can be received. The data visualization can be updated based on the series of data updates. Various performance metrics can be monitored, and data updates and/or the updated data visualization can be adjusted accordingly. Performance metrics can include at least one of: a data visualization rendering time; a data transfer time; or a data update generation time. Upon determining that one or more performance metrics exceed a threshold: a time between data updates of the series of data updates can be increased; sampled data can be requested for subsequent data updates; and/or a time-dimension extent of the updated data visualization can be reduced.
Abstract:
Examples of auto-monitoring and adjusting dynamic data visualizations are provided herein. A data visualization based on initial data can be generated. A series of data updates can be received. The data visualization can be updated based on the series of data updates. Various performance metrics can be monitored, and data updates and/or the updated data visualization can be adjusted accordingly. Performance metrics can include at least one of: a data visualization rendering time; a data transfer time; or a data update generation time. Upon determining that one or more performance metrics exceed a threshold: a time between data updates of the series of data updates can be increased; sampled data can be requested for subsequent data updates; and/or a time-dimension extent of the updated data visualization can be reduced.