What is low granularity in the context of data?

In the context of data, low granularity refers to a summary view of detail. This means that the data is presented in an aggregated form, where individual data points are not visible, allowing for broader insights and trends to be analyzed at a higher level. For instance, sales data might be summarized monthly or annually, rather than showing individual transactions day by day.

Low granularity is advantageous when the goal is to understand overarching trends rather than specific details. It allows for quick decision-making and analysis without getting bogged down in excessive detail. This approach is often used in dashboards and reports aimed at high-level stakeholders who require insights without the need for granular specifics.

Granularity essentially describes the level of detail contained in a data set, where lower granularity indicates a more condensed set of data points, while higher granularity provides finer detail.