Dimensions can be displayed in three different positions. They can be displayed either as Page Dimensions, Column Dimensions or Row Dimensions. This position can be changed interactively at any time using either a drag-and-drop method or a dialogue box.

Pivoting is one of the most powerful features of Cubes or OLAP-reports as it allows users to view their data from different perspectives. In this way, the same set of data can be used to answer numerous business questions without requiring additional reports.

Filtering is a very useful operation aimed at reducing the amount of data to be included in an analysis. In the context of a cube or OLAP-report, this means filtering out one or several members from one or several dimensions.

OLAP-dimensions can be filtered regardless of the orientation or position on which they are displayed. When a dimension is filtered, filtered members are automatically hidden in the cube grid and total and sub-totals are immediately re-calculated.

An important characteristic of dimensions in a Cube or OLAP-report is that their members can be searched as if they were a regular list. However, searching can only be performed on Column Dimensions and Row Dimensions.

Searching is very useful when a dimension contains a large number of members and a particular dimension member needs to be located.

Data sorting is another important tool for data analysis. In Cubes or OLAP-reports, sorting is done on dimensions based on measures which are used as sorting keys. In other words, the members of the selected dimension are arranged according to the values of the chosen measure at the aggregation level defined by the selected dimension. For instance, if the dimensions Year and Month are nested in the same orientation and the sorting is done on Year based on Sales, only the members of the Year dimension are arranged according to Sales, not the members of Month. This is because the selected aggregation level or dimension is Year.

Sorting can only be performed of Column Dimensions and Row Dimensions. However, any Measure can be defined as sorting key, either the measure is hidden or visible.

From the analytical point of view, sorting is very useful in highlighting trends and season variations and in identifying patterns.

A very interesting capability of the Cubes or OLAP-reports delivered by Quella Cognitus is the possibility to emphasise individual values within one or several measures with colours according to user-defined criteria. A given criterion can be defined either for a particular measure or for all the measures in the OLAP-report.

From the analytical point of view, this functionality helps the user to easily spot important pieces of information as break-even points, over and/or under performance and the like.

The main aim of a Cube or OLAP-report is to allow users to easily see their data from different points of view. It is namely this ability that makes OLAP a powerful and versatile analysis tool.

Relative measures are a way to achieve this flexibility by allowing users to display any measure either as a Percentage of Columns, Percentage of Rows or as Actual Values. This enables users to better see the relative importance of each individual element in relation to the total sum of columns and rows.

An important aspect of any report is the use of colours and fonts. Colourful reports are both more attractive and effective when it comes to catch the readers' eyes. For this reason, Quella Cognitus allows users to choose between nine different pre-defined templates or to freely create their own.

The readability of a report can be further enhanced by adding a brief description of what an OLAP-report is about. A short explanation can effectively help to improve the communication between users. Furthermore, for new users it becomes easier to understand which analyses have been previously done and their purpose.

To achieve a more flexible data manipulation than the one offered by OLAP-reports, data need to be exported to List Reports. List reports created in this way are snapshots of OLAP-reports and they can be manipulated just like ordinary spreadsheets. In this way, the analysis is focused on a reduced data segment on which users have much greater freedom to manipulate both data and layout.

The graphic viewing of data is an excellent way to visualise underlying relationships and trends. With Quella Cognitus you can create 12 different types of charts (Plot Charts, Bar Charts, Pie Charts, Financial Charts, etc) with plenty of possibilities for user-defined adjustments.

In order to share information with users inside or outside your organisation, you can export your OLAP-data to MS Excel, MS Word or Text Files.