Abstract: Generally described, embodiments of the present invention provide the ability to utilize dynamic thresholds and dynamic threshold values when generating variable formatting rules to be applied to a range of cells. Dynamic thresholds include, but are not limited to, “Highest Value,” “Middle Value,” “Lowest Value,” “Number,” “Percent,” “Percentile,” and “Formula.” When using a dynamic threshold, dynamic threshold values are determined based on values contained in a selected range of cells.

Abstract: Generally described, embodiments of the present invention relate to applying and evaluating an unlimited number of conditional formatting rules to a given range of cells. Additionally, multiple conditional formatting rules may be evaluated to TRUE for the same cell contained in a user interface and multiple formats applied to that cell.

Abstract: Variable formatting for cells in computer spreadsheets, tables, and other documents is provided. For a selected range of cells, cell formats vary with the value in each cell (or an associated value). Formats can include color-scale backgrounds, in-cell elements (e.g., icons and data bars), and other cell formats that can be varied with a value.

Abstract: A method and system associate conditional formats with selected data points or groups of data points within a summary table. In one embodiment, related groups of data are determined based upon currently highlighted cells in a summary table. A user then selects from the groups and identifies conditional formats to be associated with the specified data points. The conditional formats are associated with currently displayed as well as non-displayed data within the summary table. The associated conditions are saved relative to the data points rather than the original cell positions so that the conditions remain associated with the data points following a reorganization of the summary table.

Abstract: A data cell included in a document supporting cell structured data is conditionally formatted according to data that is stored in a separate location from the document. A user is allowed to select from a drop-down menu of related data sets a particular data set for conditionally formatting the data cell. The data cell is formatted according to the data set and the condition without requiring that the data set be stored locally in the document.

Abstract: The present invention leverages curve fitting data techniques to provide automatic detection of data anomalies in a “data tube” from a data perspective, allowing, for example, detection of data anomalies such as on-screen, drill down, and drill across data anomalies in, for example, pivot tables and/or OLAP cubes. It determines if data substantially deviates from a predicted value established by a curve fitting process such as, for example, a piece-wise linear function applied to the data tube. A threshold value can also be employed by the present invention to facilitate in determining a degree of deviation necessary before a data value is considered anomalous. The threshold value can be supplied dynamically and/or statically by a system and/or a user via a user interface. Additionally, the present invention provides an indication to a user of the type and location of a detected anomaly from a top level data perspective.

Abstract: A method of conditionally formatting a display of data is disclosed that involves providing a preliminary display automatically showing the intended consequences of the condition applied to the data prior to making the condition actually apply to the data. This is especially useful in analysis of spreadsheet data by conditionally formatting certain data. The method involves identifying one or more parameters of the data to be conditionally formatted on the display, selecting a predetermined condition; and automatically applying temporarily the predetermined condition to the parameter(s), displaying a temporary preview on the display of the predetermined condition applied to data that meet the predetermined condition. The method also provides the capability to preliminarily change the conditions and parameters applied to the data and automatically provide appropriate previews of the effect of such application of changed conditions on the displayed data.

Abstract: The present invention leverages curve fitting data techniques to provide automatic detection of data anomalies in a “data tube” from a data perspective, allowing, for example, detection of data anomalies such as on-screen, drill down, and drill across data anomalies in, for example, pivot tables and/or OLAP cubes. It determines if data substantially deviates from a predicted value established by a curve fitting process such as, for example, a piece-wise linear function applied to the data tube. A threshold value can also be employed by the present invention to facilitate in determining a degree of deviation necessary before a data value is considered anomalous. The threshold value can be supplied dynamically and/or statically by a system and/or a user via a user interface. Additionally, the present invention provides an indication to a user of the type and location of a detected anomaly from a top level data perspective.

Abstract: The present invention leverages machine learning techniques to provide automatic generation of conditioning variables for constructing a data perspective for a given target variable. The present invention determines and analyzes the best target variable predictors for a given target variable, employing them to facilitate the conveying of information about the target variable to a user. It automatically discretizes continuous and discrete variables utilized as target variable predictors to establish their granularity. In other instances of the present invention, a complexity and/or utility parameter can be specified to facilitate generation of the data perspective via analyzing a best target variable predictor versus the complexity of the conditioning variable(s) and/or utility. The present invention can also adjust the conditioning variables (i.e.