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.
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.
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.
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.
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.
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.
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.
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.
On the core level RadarCube supports a few types of hierarchies:
It's worth mentioning that both parent-child and multilevel hierarchies can also contain additional attributes.
RadarCube is the only OLAP-client that simultaniously supports a few types of drilling. These are:
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.
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.
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.
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.
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.
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".
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 ".
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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 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.
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.
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.
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".
The values of a few measures can be displayed simultaneously on the same diagram, thus making their visual comparison easy.
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.
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.
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.
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.