Cube’s data model is built for flexibility and control. By mirroring data from your source systems and structuring it within your custom hierarchy, Cube transforms your financial data into a cloud-based OLAP cube. The result? Fast access to the insights you need to drive informed decisions.
Beyond structured financial data, tables allow you to store and manage supplemental details, such as assumptions, transaction-level data, and non-numeric attributes, directly within Cube. Whether used independently or alongside Cube’s core dimensions, tables add richer context to your models, enabling more dynamic planning and analysis. Learn more about tables.
To optimize Cube for your needs, there are two important decisions your team will make during the initial setup:
- Determining your data’s primary categories or top-level dimensions.
- Designing the hierarchy outlining how data will be structured within each top-level dimension.
While dimension members can be adjusted as your business evolves and tables can be created at any time, defining your top-level dimensions and hierarchy upfront ensures a more seamless experience as you begin using Cube. Establishing this foundation early helps maintain consistency across your financial models.
What is an OLAP cube?
OLAP is short for Online Analytical Processing, and an OLAP cube is a type of data structure that catalogs data at the intersections of dimensions or categories. Although "cube" suggests a specific shape, the form it takes adapts based on the number of dimensions.
For instance:
Traditional spreadsheets offer a two-dimensional data representation, where data points correspond to row and column intersections.
An OLAP cube with three dimensions, such as accounts, departments, and time, will be shaped like a cube.
As dimensions increase, so does the OLAP cube's complexity. No matter how complex an OLAP cube becomes, the relational model continues to use the intersection of dimensions to locate values. The image below represents the relational model of a five-dimensional OLAP cube.
Top-level dimensions
The dimensions we use to build your OLAP cube are called top-level dimensions because they sit at the top level of your data. During implementation, your team will determine up to eight top-level dimensions to serve as the foundation of your Cube.
Dimension hierarchy
Once top-level dimensions are in place, the associated data for each dimension needs to be organized. A coherent and well-maintained data hierarchy, or structure, expedites data retrieval.
You are probably already familiar with your source system's hierarchy and can choose to use a similar hierarchy in Cube. The Account top-level dimension commonly follows your Chart of Accounts, while the Time top-level dimension naturally orders chronologically. However, any top-level dimension can have a custom hierarchy.
If you are new to creating a data structure, you can visualize a warehouse. The most efficient way to locate a specific item in the warehouse requires knowing its aisle, shelf, and bin numbers. Similarly, navigating through an OLAP cube uses the top-level dimensions and subcategories to locate values.
Top-level dimension sub-categories
Each top-level dimension in the OLAP cube has subcategories called parent or child dimensions. Child dimensions store values mapped from your source system or calculated using formulas. Parent dimensions have children nested below them, increasing the granularity of the data at that location.
Unlike child dimensions, parent dimensions don't house values directly. Instead, they derive their values from their children, including any dimensions calculated using a formula, ensuring up-to-date accuracy. Values undergo a cumulative rollup in hierarchies with multiple nested dimensions, aggregating data until all computations are completed.
The hierarchy of each top-level dimension is flexible. Using the Cube web portal, you can introduce or modify parent/child dimensions, rearrange them, or modify the linkage between them and your source data.
Learn more about how to use the Web portal to manage your dimensions.