Abstract: A server has a data processing module with instructions executed by a processor to maintain an annotation of a first visualization of data, where the first visualization of data has visualization configuration parameters. The annotation is linked to a second visualization of the data that utilizes the visualization configuration parameters.

Abstract: A server has a data processing module with instructions executed by a processor to maintain a collection of visualization frames that characterize a sequence of data analytics. Each visualization frame is a snapshot of data. The collection of visualization frames has associated permissions and visualization settings. A collection of discussion threads is maintained for the collection of visualization frames. Each discussion thread identifies different users and comments made by the different users.

Abstract: A server has a data processing module with instructions executed by a processor to maintain a collection of visualization frames that characterize a sequence of data analytics. Each visualization frame is a snapshot of data and the collection of visualization frames has associated permissions and visualization settings. A user navigation path through the collection of visualization frames is maintained. The navigation path specifies a data set used and a dimension accessed in the data set. A recommendation for a new visualization based upon the user navigation path is supplied. A new visualization selection is accepted and a new visualization is rendered based upon the new visualization selection.

Abstract: A server includes a data ingestion module with executable instructions executed by a processor to produce inferred data types from received data and utilize the inferred data types to augment the received data with computed values that aggregate the received data along a hierarchical dimension.

Abstract: A server includes a data processing module with executable instructions executed by a processor to produce a first inferred data type from first received data and a second inferred data type from second received data. The first inferred data type is utilized to augment the first received data with computed values that aggregate the first received data along a first hierarchical dimension. The second inferred data type is utilized to augment the second received data with computed values that aggregate the second received data along a second hierarchical dimension. The first hierarchical dimension and the second hierarchical dimension are harmonized to a lowest common unit value. A first visualization of the first received data is provided based upon the lowest common unit value. A second visualization of the second received data is provided based upon the lowest common unit value.

Abstract: A server includes a data ingestion module with executable instructions executed by a processor to produce inferred data types from received data and utilize the inferred data types to augment the received data with computed values that aggregate the received data along a hierarchical dimension.

Abstract: A server includes a data processing module with executable instructions executed by a processor to produce a first inferred data type from first received data and a second inferred data type from second received data. The first inferred data type is utilized to augment the first received data with computed values that aggregate the first received data along a first hierarchical dimension. The second inferred data type is utilized to augment the second received data with computed values that aggregate the second received data along a second hierarchical dimension. The first hierarchical dimension and the second hierarchical dimension are harmonized to a lowest common unit value. A first visualization of the first received data is provided based upon the lowest common unit value. A second visualization of the second received data is provided based upon the lowest common unit value.