Each report dimension (e.g., User source, User medium, User campaign, etc.) has a number of values that can be assigned to it. The total number of unique values for a dimension is known as its cardinality. For example, the User campaign dimension has a different value for every attributed ad campaign.
Dimensions with a large number of possible values are known as high-cardinality dimensions. Reports containing high-cardinality dimensions may be affected by Analytics system limits, returning more rows than Analytics can render. Those excess rows are aggregated under the dimension value (other) and displayed in a single row.
Analytics queries different tables to render the chart and the table in a report. Discrepancies can occur when the query of one or both tables returns more rows than Analytics can render, resulting in excess data being aggregated as (other).