By reading this page, you can learn about the following aspects of data cubes, a key MODLR functionality:  

• Introducing Cubes, a Key MODLR Functionality
• Why are Cubes Better Than Tables for Data Storage?
• What are the Benefits of Using Data Cubes in MODLR?
• How Are Cubes Used in MODLR?
• Why Do Cubes Matter to MODLR Users?
• How Do MODLR Cubes Compare with Other Data Storage Alternatives?
• I am a MODLR User. How Can I Create Cubes on MODLR?

Cubes in MODLR are multi-dimensional data structures that can be used to store, organise and analyse business information across dimensions like time, product, and department. (MODLR technical documentation)

Data cubes, a key MODLR functionality, are more customisable than static tables with rows and columns, and empower users to customise, manipulate and query data quickly and at a granular level. They make modelling in budgets, forecasts, and reporting quicker,  more versatile and reports more detailed and elegant. You can link cubes to your dashboards and workviews in MODLR for real-time visibility, quick insights and better decision-making. For all these reasons, MODLR has chosen to use cubes instead of tables. 

A cube is a data structure that stores data in a multidimensional form. Compared to tables, with rows and columns, cubes enable us to organise, hold and select data along dimensions and measures

• Cubes are more customisable than tables. They make it easier and faster to slice, dice, and summarise information for planning, budgeting, forecasting, and reporting in a more elegant manner. 
• Cubes make it easier to create more detailed reports. Data in cubes are not confined to a single column or row header as with tables. Pivoting data in a table—assuming we are talking about SQL tables—requires technical knowledge. In contrast, the dimensionality of cubes lets you view data in multiple ways with speed and ease. MODLR users are able to create detailed reporting formats, where they can drill into elements at a deeper level or to review items at a higher level. 
• Cubes help present data in a more elegant fashion.  You can create more polished layouts and  reports when using cubes, whereas tables typically offer lists of unfiltered data. 
• In the MODLR platform, data cubes act as an online hub. This way the data in cubes can be drawn on and easily accessible to all users via a website link. This flexibility is not available to regular users of tables that do not have SQL querying skills.

MODLR Founder Ben Hill  believes that the power of cubes lies in the dimensionality, user friendliness and customisability. 

What Does a Cube in MODLR Look Like?

Visualise a data cube as a three dimensional Rubik’s Cube for storing data. 

• The 3 Dimensions in a cube are the categories that define how your data can be broken down. Dimensions can be any variable of the data, including geographic location, product, time period or scenario. 
• The Measures Dimension is a special dimension that always comes last and defines the numeric metrics stored in the cube (like Revenue, Units Sold, Cost). 
• A Cell lies at the intersection point of three dimension elements. In other words, a cell is a specific combination of dimension elements (such as Jan 2026 × Retail Sales × of Product A) and holds the measured values for that intersection.
• Each cell in a cube contains the aggregated data values for a particular combination of dimension elements (one element from each dimension). In other words, each cell contains the aggregated measures, for an element from each dimension of that cube.

Here’s An Illustrated and Simplified Example of a Sales Data Cube 

• This cube has Products, Time Period and a ‘Measures’ dimension which holds data for units sold, gross revenue, cost of goods, net revenue and  average selling price. 
• The cells in this diagram correspond with respective products, time period and the measures such as units sold, gross revenue, cost of goods sold etc.
• To elaborate, here’s what you get from each of the coloured cell in this sales data cube:

According to Ben Hill, Founder of MODLR, cubes, with their versatility and the ability to store large data volumes, make for quick access and faster processing times. 

• Quick access. Because cubes store aggregated data at a summary or non-transactional level, they allow quick access to the data without having to perform summations of transactional data on the fly each time for every query. 
• Faster processing. Quick access to data inevitably means faster processing. Your queries can be answered with minimal delays.  
• Ideal for storing and analysing large volumes of data. Quick access and , particularly when that data is changing slowly over time.
• Cubes are versatile. You can link cubes with formulas, by letting one cube’s values feed into another. For example you  can link a Sales cube to a Profit & Loss cube with ease.