Breaking down data across multiple dimensions is known as what?

The term that describes breaking down data across multiple dimensions is known as slicing data. This concept involves taking a dataset and examining it from different perspectives, such as by department, time period, geographical location, or other relevant criteria. By "slicing" the data, you can isolate specific sections of interest, allowing for more detailed analysis and understanding of underlying trends and patterns.

Slicing is an essential aspect of data analysis as it helps in creating more detailed reports, facilitating decision-making, and enabling organizations to gain insights that are not visible when looking at the data as a whole. It enhances the ability to look at aggregated data while still being able to access the finer details that matter for strategic planning. This process is integral in environments like Workday Adaptive Planning, where multi-dimensional analysis is vital for comprehensive financial planning and forecasting.