How do measures differ from dimensions in Tableau?

In Tableau, measures and dimensions serve distinct roles in data analysis, and understanding these differences is crucial for effective data visualization.

Measures are numerical values that can be quantified and aggregated. This means they can be summed, averaged, or otherwise mathematically manipulated to produce meaningful metrics, such as totals or averages of sales figures. Measures are the data points that can change in value (e.g., sales amount, profit margins) and are often displayed in aggregate form in visualizations.

On the other hand, dimensions are categorical fields that are used to segment data and provide context. They typically include categories such as names, dates, or geographical locations. Dimensions do not support aggregation; instead, they serve to classify and group measures. For example, you might use dimensions like "Product Category" or "Region" to break down sales figures by those categories, showcasing how totals vary across different segments.

Understanding the specific functions of measures and dimensions allows analysts to build more insightful visualizations and perform effective data analyses. In summary, measures can indeed be aggregated, while dimensions provide a way to categorize and segment that data into meaningful visual slices.