What is one benefit of using measures instead of calculated columns in Power BI?

Using measures instead of calculated columns in Power BI offers the distinct advantage of calculating values based on the context of the data model at the time of query. This context-sensitive computation allows measures to react dynamically to filter context and user interactions within reports, providing up-to-date and relevant results based on the current data being analyzed.

When users change slicers, apply filters, or drill down into data, measures automatically recalculate to reflect these changes without needing to store additional data in memory. This flexibility makes measures highly efficient and powerful for real-time data analysis, allowing for a more interactive and responsive user experience in visualizations.

In contrast, calculated columns are computed during the data load process and are static, not adjusting to the filtering or slicing applied in reports. They provide fixed values that do not change based on user interactions, which limits their versatility compared to measures. Additionally, while measures are optimized to use less memory since they only compute results on demand, calculated columns can consume more memory as they persist data in the model. This underlines the importance of understanding when to use measures versus calculated columns in data modeling within Power BI.