Abstract: Examples of pinning portions of data visualizations are provided herein. A portion of interest of a data visualization can be selected, and a pinned portion can be generated that includes the portion of interest. A data visualization can be generated that represents data in a dataset. Instructions to select a portion of interest of the data visualization can be received. A pinned portion of the data visualization can then be generated. The pinned portion has pinned visualization content that includes at least some of the portion of interest of the data visualization. The pinned portion can be presented in association with the data visualization.

Abstract: Examples of pinning portions of data visualizations are provided herein. A portion of interest of a data visualization can be selected, and a pinned portion can be generated that includes the portion of interest. A data visualization can be generated that represents data in a dataset. Instructions to select a portion of interest of the data visualization can be received. A pinned portion of the data visualization can then be generated. The pinned portion has pinned visualization content that includes at least some of the portion of interest of the data visualization. The pinned portion can be presented in association with the data visualization.

Abstract: Examples of data visualization adaptation to filtered data are provided herein. A visualization type of a data visualization can be changed to reflect filtering of the data represented by the visualization to provide a clear, useful representation of the filtered data. A first data visualization can be generated that represents data in a dataset. The first data visualization is of a first visualization type. Filter information for filtering the data in the dataset can be received. Based at least in part on the filter information, one or more alternative visualization types can be selected. A second data visualization can then be generated. The second data visualization represents data in a subset of the dataset corresponding to the filter information. The visualization type of the second data visualization is one of the alternative visualization types.

Abstract: A perspective selection may be used to identify one or more algorithms that may be of interest to an end user and that are associated with the selected perspective. The perspective selection may be used to determine an algorithm for the predicted data of interest and to determine the relevant data for the determined algorithm to generate the predicted data. The relevant data may be retrieved from a backend system and used with the determined algorithm to generate the predicted data. The predicted data may be output to a client device to display a visualization of the predicted data for easy consumption by an end user.

Abstract: A scale for a first business intelligence (BI) report is determined and filters over data properties of received BI data are applied. A first BI report is generated. A second BI report based on the same BI data is generated for comparing with the first BI report. For the generation of the second BI report, the same data properties are filtered as for the first BI report. The first and the second BI reports use a common scale and are displayed as two layers placed one on top of the other. In some aspects, multiple other BI reports are generated and visualized for comparative study together with the first and second BI reports as overlapping layers. These multiple BI reports share the same scale as defined for the first BI report and include filters for the same data properties as for the first BI report.