Data granularity refers to the level of detail or precision in a dataset. It indicates how finely data is broken down, which can range from broad categories to specific measurements. For example, a dataset on sales could be granular at the level of individual transactions or aggregated to show total sales by month. Higher granularity provides more detailed insights but can also lead to larger datasets that are more complex to analyze. Conversely, lower granularity simplifies data but may obscure important trends. Choosing the right level of granularity is crucial for effective data analysis and decision-making in fields like business and research.