Categorical Data

Categorical Data is like having different buckets to sort things based on their types or categories. In business intelligence, it refers to data that can be divided into specific groups that are usually labeled with names rather than numbers. Examples of categorical data could be a list of product types (like “shoes,” “shirts,” “hats”), customer responses (like “satisfied,” “unsatisfied,” “neutral”), or colors (like “red,” “blue,” “green”).

Businesses use categorical data to organize information in a way that’s easy to understand and analyze. This data is key when it comes to making sense of customer feedback, analyzing sales patterns, or segmenting the market. It’s not about numbers or how much; it’s about what kind or which one.

For data analysts, categorical data is essential because it can show how often each category comes up, which is important for making decisions. For instance, if most customers fall into the “satisfied” bucket after a survey, a business knows it’s doing something right. Categorical data helps turn complex customer information into actionable insights, helping businesses to focus their efforts and improve where it counts.