Why We Use Multi-Dimensional Cubes

Why we us Multi-Dimensional cubes

Imagine you want to represent the sales data of a specific product. To do so effectively, you need to consider several attributes:

  • Sales of a Product
  • In a Month
  • Of a Year
  • In a Given Location

In Excel, however, data representation is confined to two dimensions: rows and columns or
product categories. This limitation makes answering certain complex questions challenging:

  • How do you compare sales of all products in a specific month to the sales of the same products in the corresponding month last year?
  • Can you easily track sales of one product in a particular location across multiple months?
  • How do we plot the sales of one product category across multiple locations in a given month?
  • What about analyzing sales of a specific product within a defined region, considering data from multiple months?
  • These inquiries often lead to extensive data wrangling in Excel, resulting in a timeconsuming and error prone process.

Excel’s Pivot Tables try to replicate the cube concept but fall short in precision for financial analyses. FP&A tools with multidimensional cubes provide a structured and hierarchical approach to data storage, allowing for efficient organization and analysis of financial data. This offers clarity and efficiency for finance professionals.


In summary, multi-dimensional cubes are the secret sauce behind FP&A tools, empowering finance teams to navigate intricate financial landscapes with ease. Say goodbye to data wrangling and hello to insightful analysis!

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