This article is about Google Analytics 4 properties. Refer to the Universal Analytics section if you're still using a Universal Analytics property, which will stop processing data on July 1, 2023 (October 1, 2023 for Analytics 360 properties).

[GA4] (other) entries in reports

What causes the (other) row

Each dimension (e.g., First user source, First user medium, Session campaign, etc.) has a number of possible values that can be assigned to it. The total number of unique values for a dimension is known as its cardinality. For example, the First user campaign dimension has a different value attributed to each ad campaign.

Dimensions with a large number of possible values are known as high-cardinality dimensions. High-cardinality dimensions may affect quality and granularity shown in different parts of Analytics, depending on the system limits. The cardinality limit applies to all data collected in a property for the date range specified in the report, not just the data thats rendered in a given report.

Reports and the Data API

Data in both the Analytics reports and the Google Analytics Data API may be affected by the Analytics system limits, resulting in data aggregating under the (other) dimension value. However, the metric totals for all the data retrieved are correct.

Analytics queries different data sources to render the data in a report. Discrepancies can occur when the dimensions in a property's aggregate tables exceed their system limits, resulting in the remaining data being aggregated under the dimension value (other).

You may see data aggregated under (other) when the total values of all dimensions in a property exceeds 50,000 values per day. When a property exceeds the limit, the (other) row can be reported, regardless of how many or which dimensions are selected in a report.


Explorations are subject to different limits, which can explain some of the differences in metrics when limits are reached. Unlike reports and the Data API, explorations never show an (other) row. Learn more about the differences between Reporting and Explorations.

Best practices

  • Use default reports where possible. The default reports are supported by specific data sources, which will decrease the likelihood of data aggregating under the (other) dimension value.
  • If your standard or 360 property shows the (other) row, consider prioritizing the data that's most important to your business. The cardinality limit applies to all data collect in the property for the date range specified in the report, not just the data rendering in one report. For example, avoid collecting high-cardinality custom dimensions, like a unique identifier for each user. Instead, use our User ID feature. Learn more about User ID in Google Analytics 4 properties.
  • If your standard properties hit the (other) row, consider upgrading to Analytics 360 to take advantage of automatic custom tables. For 360 properties, automatic custom tables are enabled automatically when you experience the (other) row so that data aggregates under (other) far less frequently. Learn more about automatic custom tables.
  • Google Analytics 360 users who see the (other) row in their reports can run the same queries in explorations. If an exploration begins to sample data, you can request unsampled exploration results. Learn more about unsampled explorations.
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