What is meant by “multi-dimensional analysis” in Tableau?

Multi-dimensional analysis in Tableau refers to the capability to examine data across multiple dimensions or variables simultaneously. This approach allows for a more in-depth understanding of the data by enabling users to slice and dice it through various perspectives, such as time, geography, product categories, or customer segments.

For example, if you're analyzing sales data, multi-dimensional analysis would allow you to view sales performance not just over time, but also segmented by region and product type. This can reveal insights such as which products are performing well in specific regions during a given timeframe, facilitating more informed decision-making.

In contrast, analyzing data in only two dimensions restricts the insights that can be gained since it overlooks the complexities and relationships that can exist between multiple variables. Viewing data across a single variable would provide a very narrow view, as it only considers one aspect of the data at a time. Summarizing large datasets into binaries would simplify the data too much, eliminating important nuances that can be uncovered through a multi-dimensional lens. Thus, the ability to analyze across multiple dimensions is crucial for comprehensive and effective data analysis in Tableau.