Cubes containing information to be analyzed are based in the multidimensional data model. This model's main feature is its ability to display information in a very close way to the way it is displayed in real life.
As an example of the elements forming the multidimensional model, here is the analysis of a case in a company sales area.
In the multidimensional model you must consider all the elements that enable the desired analysis. For instance in order to perform the sales analysis, we must arrange data in such a way we can access them according by:

Dates
Customers
Products
Location
Salespeople

This classification is reflected in the model's dimensions.
By combining elements from the different dimensions, O3 Browser satisfies your analysis needs, responding, for instance, to queries with different combination of dimensions:

Date and customer
Product and customer
Product, salesperson and location
Date and location

Apart from data classification, it is essential to define those data we wish to quantify.
For the example above, we may think in terms of:

Units sold
Sales Amount
Costs
Gross Profit

The quantified elements in the model are called measures. Measures are the values to be analyzed, classified according to the different focuses dimensions offer. They are business indicators allowing the user to measure and determine trends.
Model definition includes the possibility to arrange the elements in each dimension hierarchically. This enables users to analyze information at different levels of detail. For example: "Date" dimension may include years, quarters, months and days; the dimension known as "location" may include countries, states, cities, etc.
To sum up, the analysis potential is based in the model definition, (data specification and structuring) and the possibility to make queries combining the different dimensions and measures, and selecting different levels of detail for the dimensions.
Going back to the sales analysis example, the user can check the evolution of profit during the last quarter. If a very low profit is detected for a given month, they can study the units sold, sales and cost in search of the cause for such situation. If, for example, it is due to the fact that fewer units were sold, the user can then study if different products are to blame or if the trend depends on the location, or on salesperson in particular.

Choosing Measures

A cube may contain several measures that represent the indicators we wish to analyze.
Measures are located in the rightmost end of the Dimensions Bar and are identified with a different color.
The user may change the measure being analyzed at any time either from the Analysis Pane, the Dimensions Bar or from the Dimensions Explorer. In the chapter "About Drilling" there is a detailed description of the different ways to change the analysis context.
In graphs, measures are represented on the Y- axis by default.
Also in the Analysis Pane a graph may be displayed where two measures are considered simultaneously. In this case, the Dimensions Bar changes to include two lists of measures to allow you to select those that will be displayed in the Analysis Pane.

Choosing Dimensions

When analyzing data with O3 Browser, besides choosing the kind of graph they consider most adequate, users must place the dimensions that determine the initial context for their analysis on the corresponding axes.
By default when a cube is opened the first two dimensions in the Dimensions Bar are shown on the X-axis and on the Series respectively.
The user can change the analysis context at any time either from the Analysis Pane itself or from the Dimensions Bar or the Dimensions Explorer.
In the chapter "About drilling" there is a detailed description of the different ways to change the analysis context.

Filters

The set of data analyzed at every moment is determined by the dimensions placed on each of the axes and the selected measures.
Besides, the dimensions that do not lie on the axes can also take part in the determination of the context analysis. Selecting one element in one given level of these dimensions adds the condition that the result be restricted to those elements only.
For example, if sales evolution by product in 1998 is being analyzed, placing the "Date" dimension in the X-axis, and the "Product" dimension in the Series, you can easily focus the analysis on a specific country, choosing that country in the dimension "Location". In this way, what we say is that data is restricted or filtered to include only the ones associated to that country.
Filters can be applied either from the Dimensions Bar or from the Dimensions Explorer. In the chapter "About drilling" there is a detailed description of the different ways to change the analysis context.

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