Business Objects Software Limited

Sap Se

Sap Ag

Julian Gosper

Flavia Silvana Moser

Scott Cameron

Davor Cubranic

Alexander MacAulay

Virgile Chongvilay

Saurabh Abhyankar

Jean-Luc Agathos

David R Siegel

Stephen Petschulat

Madison Poon

Michael Emmett Thompson

Soroush Momen-pour

Ryan Wayne Hanna

Alexander Sorin

Richard Bruce Cameron

Sylvie Denis

Ashley Gadd

Henry Lo

Adam Binnie

Yahui Lu

Ian McAlpine

Gavin Olle

Chun Pong Chan

Edward Prinsen

Philip Coldrey Lo

Ian Forneri

Chuen Chi Yau

Oliver Woolgar

Paul McArthur

Qing Li

In some example embodiments, an indication of a selected data point of a current visualization can be received. A context of the selected data point can be determined based on a dimension of the data point, and explanation candidates can be generated based on the context of the selected data point. Each exploration candidate can have a different dimension context that is within the context of the selected data point and a corresponding value for the dimension context. For each one of the explanation candidates, a corresponding score can be generated based on a difference between the value for the explanation candidate and an average value of all the values of the explanation candidates. The explanation candidates can be ranked based on the scores. At least one of the explanation candidates can be selected based on the ranking, and selectable explanation(s) for the selected explanation candidate(s) can be displayed.

System and method of providing visualization explanations

A raw dataset including measures and dimensions is processed, by a preprocessing module, using an algorithm that produces a preprocessed dataset such that at least one type of statistical analysis of the preprocessed dataset yields equal results to the same type of statistical analysis of the raw dataset. The preprocessed dataset is then analyzed by a statistical analysis module to identify subsets of the preprocessed dataset that include a non-random structure or pattern. The analysis of the preprocessed dataset includes the at least one type of statistical analysis that produces the same results for both the preprocessed and raw datasets. The identified subsets are then ranked by a statistical ranker based on the analysis of the preprocessed dataset and a subset is selected for visualization based on the rankings. A visualization module then generates a visualization of the selected identified subset that highlights a non-random structure of the selected subset.

Multivariate insight discovery approach

At least one analytical operation from a set of different analytical operations may be determined based on at least one input. The input(s) may comprise contextual information of working content being displayed to a user on a device and comprising numerical data. Supplemental information for the working content may be generated using the determined analytical operation(s), may comprise a numerical-based analysis of the numerical data, and may be caused to be displayed to the user concurrently with the working content. The contextual information may comprise structured data. The input(s) may further comprise at least one of a history of the user's interactions with the working content, a history of the user's interactions with recommendations of supplemental information for the working content, a history of other users' interactions with the working content, and a history of other users' interactions with recommendations of supplemental information for the working content.

Methods and systems of providing supplemental informaton

Techniques of providing visualization suggestions are disclosed. In some example embodiments, a current visualization of at least a portion of data of a dataset is determined to be displayed to a user in a graphical user interface of a device, a plurality of visualization candidates is generated based on an application of transition rules to the current visualization, a corresponding score for each one of the plurality of visualization candidates is generated based on a corresponding level of data variance for the data of the corresponding visualization candidate, a ranking of the plurality of visualization candidates is generated based on the scores, at least one of the plurality of visualization candidates is selected based on the ranking, and a plurality of selectable visualization suggestions corresponding to the selected visualization candidates is caused to be displayed to the user in the graphical user interface of the device.

System and method of providing visualization suggestions

Described herein are methods and systems for analyzing multidimensional data that use tangential exploration of data via a third or Z-dimension to the current two-dimensional view. The tangential exploration allows higher dimensionality to be explored without causing visual clutter.

Peeking into the Z-dimensional drawer

Described herein are methods and systems for providing hints for and selecting cells within a crosstab that are compatible. Providing hints manifests the compatible cells and the selection is limited to compatible members. Hinting at unselected but compatible cells provides leads for user for other operations they may seek to pursue. User selections that include incompatible cells are corrected to ensure integrity of group operations to be performed on the selections. Compatibility is determined by aggregation level, measure and the like.

Aggregation level and measure based hinting and selection of cells in a data display

Parental dependency information for various data fields may be analyzed to create a data field hierarchy. Each of the data fields may be presented in a selectable list through an interface. Once a data field is selected, any immediate parent(s) and/or child(ren) field(s) of the active data element may be demarcated in the list according to the hierarchy. Additional data entry fields relating to the selected data field and its familial fields may also be displayed. Data in each of data fields may also be analyzed to identify fields with incomplete data. Systems and methods are provided.

Progressive exploration of data relationships

A computer readable storage medium includes executable instructions to provide a Graphical User Interface with a plurality of visualization types and a semi-structured workspace. A drag-and-drop of a visualization type into a drop zone in the semi-structured workspace is received. The drop zone corresponds to a location in the semi-structured workspace where an associated visualization is displayed. A link is created between the associated visualization and a query to a data source.

Displaying visualizations linked to one or more data source queries

A computer readable storage medium includes executable instructions to receive a relevancy parameter. The relevancy parameter is searched in a category ensemble including a set of categories, where the category ensemble overlies a dataset. A first order of the set of categories is created based on the relevancy of the relevancy parameter to each category in the set of categories, where the relevancy is a degree of match to the relevancy parameter. A second order of the set of categories is created based on the merit of each category to partition the dataset. The first order and the second order are combined into a final order, which is returned. A measure in the category ensemble is searched based on the relevancy parameter. The measure is returned as a selected measure, where the selected measure is a codomain of a visualization depicting a portion of the dataset.

Assessing relevant categories and measures for use in data analyses

A computer implemented method includes receiving a data filter from a first panel of filtering categories. The data filter is applied to a dataset wherein a resulting data subset is created. One or more further data filters is displayed within a nested second panel of filtering categories.

Apparatus and method for filtering data using nested panels

Apparatus and method for assessing relevant categories and measures for use in data analyses

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Vancouver, Canada

Julian Gosper