RadarCube for WPF

Flexible and yet powerfull OLAP controls you can use in your WPF applications. Easy use and happy users getting much benefit from using WPF graphics on different devices. Combines perfect visualization and power of the desktop application.

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Data sources and export features

Supports any kind of data sources, like database, file etc. Supports Sql Server Analysis Services cubes as a multidimensional data source.

There're two versions of RadarCube for ASP.NET:
Works with relational data sources of any kind through the DataSet, LINQ for SQL or Entity Framework. The real way of storing the data is irrelevant, since the MOLAP - architecture of the Radar Cube Desktop core makes it independent, hence fully universal.
Unlike the Desktop version uses Microsoft Analysis Services cubes and local cubes, created by MSAS. The versions from 2000 to 2012 are supported.

Supports large-size databases and cubes.

The special cache mechanisms and visual improvements allow working with databases containing up to 1,000,000 records (and in the case of MSAS version - practically with Cubes of any size), and with dimensions of many a thousand members.

Saving and restoring the current OLAP slice.

RadarCube supports a few methods of saving/restoring the state of OLAP slice: the data may be saved both by an end-user and programmatically. The state files are cross-platform - the data saved in WPF can be read in WinForms or in ASP.NET-version of RadarCube, and vice versa. Moreover, the Desktop version also supports the saving mode for Cellset with the Cube data.

Handy integration with charting and other third-party components.

RadarCube may serve as data source for other controls - in this case RadarCube provides its current Cellset as data source. Data can be exposed in different modes - see the RadarCube documentation for details.

Export the Cellset to the most popular formats, like PDF, HTML, GIF, XLS etc.

In addition to copying to the Clipboard, RadarCube allows exporting an OLAP cellset into many other popular formats. RadarCube has lots of options for tuning its appearance and changing the contents of cells upon export, enabling/disabling paging and many other things.

OLAP specific features

Calculated measures of a few different types (row-table based measures, custom-aggregated measures and measures based on other Cube cells).

RadarCube Direct supports many types of aggregating functions and, moreover, allows you to implement your own aggregating functions. Number, string or data fields can be used as measures. The Direct-version also supports the measures calculated on the fact table row level - a value of such measure is calculated sequentially for every row of the fact table during its fetching. The source data for measure calculation of this type is the information of the current row of the fact table and the rows of the dimension table related to it. Moreover, both MSAS and Direct versions support measures calculated from the current cellset data. The way of calculating can be implemented programmatically. Also it is possible to add measures, defined by MDX expressions.

Calculated hierarchy members.

Both the Direct and the MSAS versions allow creating additional calculated members inside any hierarchy. These members come very handy for, say, displaying some intermediate results. The algorithms of calculating such members are implemented programmatically in the appropriate control's event handlers. There's also an option of creating calculated hierarchy members through the end-user interface, with MDX expressions.

Attributes which store additional information about hierarchy members.

Informational attributes contain additional information about dimension members. For example, for "Personnel" dimension the attributes may include information about home addresses and phone numbers. Usually attributes are presented as fields of the same dimension table that describes the dimension itself. A short video below will demonstrate you how to define attributes with Cube Editor and the way it looks in OLAP Grid.

Hierarchies of three types: Attribute (or flat),Parent-Child and Multilevel hierarchies

On the core level RadarCube supports a few types of hierarchies:

attribute (or flat)
ordinary lists of titles and, possibly, a set of additional attributes. For example, the title for the Customers table will be Customer Name, and the set of attributes may include EMail, HomePhone, etc.
created on the basis of self-referencing tables.
created based on fields of one or a few tables, logically connected to each other by one-to-many relation.

It's worth mentioning that both parent-child and multilevel hierarchies can also contain additional attributes.

A few types of drill-down support separately for every hierarchy member.

RadarCube is the only OLAP-client that simultaniously supports a few types of drilling. These are:

drilling down to the next level
applied to multilevel hierarchies;
drilling down to children of a parent-child hierarchy member
applied to parent-child hierarchies or for member-groups.
drilling down to the next hierarchy
applied, when a few hierarchies are placed into the same active row or column area.

Each type of drilling is marked by a unique icon.
With this tool an analyst is able to create most complex OLAP-reports, impossible for any other OLAP-client, and display in the OLAP-environment the exact amount of information he needs at the moment.

Different simultaneous measure display modes (values, per cents from various totals etc).

The same measure can be displayed in Grid in different modes: it can be exposed in its' absolute mode - as a value, or in relational - in per cent value from the totals by columns or by rows.

Member grouping on any hierarchy level.

Besides standard OLAP operations, such as pivoting and drilling, RadarCube also supports member grouping. Groups may be created in hierarchies of any kind. Member grouping makes understanding and analyzing an OLAP-slice much easier, for example, applying the Pareto principle, you can save the "unimportant" for the current analysis hierarchy members into member groups.

Individual hierarchy or dimension customizable sorting on any level.

Any hierarchy level may be sorted in three ways: in alphabetical order, in descending order or by default (with elements coming in the same order they do in the table or on the MSAS server). Besides, you can programmatically override all three methods, assigning "ascending" and "descending" order any custom meaning. For example, you can range the months not in alphabetical order, but from January to December.

Ascending or descending sorting based on any column value in the OLAP grid.

Sorting by value allows an analyst to quickly pick out OLAP-cube elements he needs for the current analysis. It's worth saying, that the cells may be sorted not just by their absolute values, but by their per cent relation to rows' or columns' totals.

Filtering of any set of hierarchy members with or without applying these filters in the OLAP calculations.

RadarCube allows using complicated filters applied to an arbitrary subset of members of different dimensions and hierarchies. At that, it doesn't matter if the filtered dimensions are situated in the active area (of rows or columns) - the applied filters and Cellset configuration are not interdependent. Moreover, besides the filters applied to hierarchy members, there're also context and visual filters - see other sections of "Detailed features".

Context filtering of the hierarchy members depending on their values in the Grid. Major/minor members selection, either based on their rank or on the Pareto principle.

The result of applying context filters depends on the currently displayed Cellset and on the Cube data. For example, it is possible to apply such filters as "Show 3 most significant members of the Product Categories level by Internet Sales Amount values", "Show only the members that contain "ic" in their names", or "Display the data related to the third quarter of 2003". The context filters may be applied not only to dimensions, but to measures as well/ like: "Show the data cells with Sales Amount value over $1,000,000". Moreover, besides the context filters, there're also visual filters and filters applied to separate hierarchy members - see other sections of "OLAP specific features ".

Threshold visual filtering feature.

Unlike filters for hierarchy members or context filters, visual filter is of the visual type - it simply lets you hide the values beyond the threshold defined by the user - without recalculating the whole Cube.

Supports the Writeback option (the Cube cells editing).

RadarCube supports editing Cube cells. Native MSAS Writeback is used for the MSAS version, but for the Direct-version a programmer will have to implement the preferred way of changing the database.

Supports the Drillthrough option (browsing the relational data aggregated into a Cube cell).

RadarCube supports browsing database data, aggregated into a displayed Cube cell (drillthrough). This operation is supported in both the MSAS- and the Direct-versions of RadarCube.


Full control over an OLAP Grid cell and ability to embed any content of yours.

It is possible to programmatically change the contents of OLAP Grid cells, change the cell text, insert images and icons into cells and even arbitrary WPF UI content. OLAP Grid will automatically adjust the size of the cell to its contents, whatever it is.

Fixed columns/headers on scrolling Grid. Automatical cell ajustment by content. An option of changing the width of columns.

The width of the Grid columns is automatically adjusted to the contents of the cell, no matter what exactly they contain: text, images, or anything else. Of course, you can change the cell width, if you like.

Hierarchies' page-viewing mode. This feature allows you to significantly lessen the network traffic and make the OLAP analysis easier.

The option of page viewing hierarchy members is enabled in RadarCube OLAP Grid by default. The exact settings can be selected individually for each hierarchy: you can set the number of elements on a page, or disable paging altogether. You can also use the option of page-viewing in the hierarchy filters editor.

Customizable context menus.

RadarCube offers an advanced system of context menus that provides users a quick access to all control's options. But more that that: any additional function may be implemented into RadarCube programmatically and then accessed via the context menu.

Easy localization. It is even possible to localize the evaluation version as well.

RadarCube's interface is very convenient for localization - all the lines visible for an end user, can be translated into any language. Moreover, any translation made by any user is also available to the rest of them, and is included into the next release of RadarCube. Thus, at the moment RadarCube is translated - fully or partially - into more than 20 languages. By default, RadarCube uses the preferred language of an end-user's browser - but there is an option of strictly defining the main language for RadarCube.

Supports end-user comments on OLAP cells.

RadarCube allows commenting on the contents of the cells, saving the comment even if the position of the cell in Grid is changed. All the comments are also stored in the Grid state file and can be read later.

Conditional formatting, depending on the cells’ values and using different patterns.

RadarCube OLAP Grid allows you to paint cells with different colors, depending on their values and a selected color scheme. This makes presentation of OLAP-data much more visual.

Context formatting, selecting and copying to Clipboard.

RadarCube RIA OLAP Grid supports three modes of selection, that can be transformed into one another simply by pressing Shift or Ctrl. The purpose of making two additional modes was to achieve a better presentaion of information in the Grid, visualizing in different colors and histograms the full range of values from the selected cells. The selected Grid area (including all affected measures and members) may also be copied to Clipboard and then pasted to another application for further analysis.

Visualizing OLAP-slice both as table (OLAP Grid) and graph (OLAP Chart).

Visualizing OLAP-slice is possible both by the OLAP Grid and the OLAP Chart controls. In the first case, the information will be presented as a cross-tabulated table, in the other case, as a set of different charts.

OLAP Chart features

Modifications of OLAP Chart elements’ color, form and size depending on the values of different measures. Discrete and continuous color modifications.

OLAP Chart supports shape, color and size modificators, i.e. it allows using different measures and dimensions as additional conditions and elements of visualization. That means that the color, size or shape of a point (or another Chart element) can be changed depending on values assigned to measures in a multidimensional Cube cell. It significantly increases the clearness of the presented OLAP data.

Areas, Lines, Splines, Bars, Pies and Points data visualization modes.

An OLAP-slice can be visualized – if necessary – by Areas, Lines, Splines, Bars, Pies and Points. End-users are able to select the type of visualization through a convenient context menu.

Numerical X and Y axes for visualizing the correlation between two measures.

Both X and Y axes of the diagram are able to display hierarchies as well as measures. In case, measures will be selected for both the X and the Y axes, we’ll see the visualized correlation between measures on both axes of the charts, depending on the factors (hierarchies), set by the Detail-modificator.

Displaying an arbitrary number of levels in a multi-level hierarchy.

The drilling operation in OLAP Chart is somewhat different from the same operation in OLAP Grid: OLAP Grid supports only the step-by-step drilling of a value, while OLAP Chart visualizes the whole value of elements on the same level, while intermediate levels may be skipped. For example, for the Year-Quarter-Month hierarchy it is possible to visualize only the "Year" and the "Month" levels, skipping the "Qarter".

Grouping a few measures in a single diagram.

The values of a few measures can be displayed simultaneously on the same diagram, thus making their visual comparison easy.

Direct version specific features

Auto conversion of the DateTime fields into flat or multilevel hierarchies.

Each dimension member, displayed in OLAP Grid, can have the attributes containing additional information about it. For example, for the list of company's personnel there can be the following attributes: personal email addresses and phone numbers or the date of employment.

MSAS version specific features

Support of the MSAS Actions.

RadarCube supports MSAS Actions, such as URL, Drillthrough, Rowset etc. All these actions are interpreted according to their description in the MSAS Cube, and are accessible through the context menus of the corresponding RadarCube cells.

Support of Time intelligence features.

In the MSAS-versions for the data cells that deal with time measurement there is an option of using the "Time Intelligence" features - a powerful means for statistical analysis of Time series. It can be accumulating amounts, moving average or evaluating values growth in comparison to the previous period, etc. Time Intelligence functions are available through the context menu of data cells. As many other things in RadarCube, the Time Intelligence menu can be tuned programmatically.

Displaying results of arbitrary MDX queries.

Not only can RadarCube be used as a tool for browsing a multidimensional cube, but it can also display the results of MDX-queries. In that case, the Grid doesn't support such operations as drilling, pivoting, sorting, grouping, and filtering, but as always you’ll be able to change a cell's contents and its look and feel, as well as fix the row/column headers.

Client requirements

  • NET Framework 4 or higher.

Developer requirements

  • Visual Studio 2010 (recommended) or 2012.
  • For RadarCube for MSAS: ADOMD.NET, Microsoft SQL Server Analysis Services OLE DB Provider.