Data aggregation is part of your daily life and you may or may not even realize it. When you pull up a review of a restaurant that uses one to five stars or if you purchase an item on Amazon because it has thousands of customer ratings, both examples are data aggregates. A data aggregate can be defined as a summary typically based on a significantly larger detail. In SQL, an aggregation is when a groupby command is applied against one or more tables, which includes a statistical calculation such as sum, average, min, or max against one or more fields.
Understanding the granularity of data
The aggregation of calculations would be known as the measure. When you are grouping by one or more fields to get their distinct values, they are classified as dimensions.
So, this should all sound very familiar because we introduced the concept of dimensions and measures in both Chapter 5, Gathering and Loading Data in Python...