Various data-related aspects of GA4
In this guide, you will learn about the various data-related aspects of GA4.
Data Freshness
How quickly Google Analytics collects and processes an event from your property is referred to as data freshness. Data freshness is 20 minutes if that operation takes 20 minutes.
Intervals of data freshness
The approximate intervals of data freshness for standard properties and/or Google Analytics 360 are as follows:
Interval | Processing time | Properties | Data limits per property | Query coverage |
Realtime | Less than 1 minute | 360, Standard | None | |
360 intraday | About 1 hour | 360 | Premium Normal and Premium Large as defined here | All reports and API queries, except these |
Standard intraday | 4-8 hours | Standard | All property sizes | All reports and API queries, except these |
Daily | 12 hours | 360, Standard | Standard, Premium Normal | All reports and API queries |
Daily | 18 hours | 360, Standard | Premium Large | All reports and API queries |
Daily | 24+ hours | 360, Standard | Premium XLarge | All reports and API queries |
Data thresholds
If data is missing from your report or exploration, Google Analytics may have set a data threshold. Data thresholds are used to prevent people from being identified based on their demographics, interests, or other data signals when viewing a report or exploration.
Data thresholds are determined by the system. They cannot be altered.
When data thresholds are applied
Google signals
When Google signals are enabled and you have a low user count for the given date range, data in a report or exploration may be suppressed.
Demographic information
If there aren’t enough users overall, the row containing the demographic data may be suppressed if a report or exploration uses the device ID as the reporting identity.
When viewing a report or exploration or making an API call that includes demographic data combined with user identifiers (e.g., user ID, client ID), custom dimensions, or specific user-generated content fields (e.g., source/medium), data may be withheld and you may encounter thresholding or incompatibility restrictions.
Search query information
If there aren’t enough users overall, the row holding search query information may be withheld from a report or exploration.
Adjusting the date range
If there are few users or events during the specified period range, data thresholds might be applied when you read a report or conduct a search inside that time frame. You may be able to see the previously thresholded data by increasing the date range if more users have triggered events.
Exporting to BigQuery
Google Signals data is not exported by Analytics to BigQuery. As a result, Analytics and BigQuery might display various event counts per occurrence. There can be discrepancies between the user counts in Analytics and BigQuery since Google signals remove duplicate event counts from specific users.
Data compatibility
Google Analytics gathers information from the websites and mobile applications you tag, as well as through manual data import, Google-only data, integrations (such connecting to Google Ads), and other sources. This article explains why some data cannot be reconciled with other data.
To check whether specific dimensions and metrics are compatible, use the Compatible Fields portion of the GA4 Dimensions & Metrics Explorer.
Why data is incompatible
When any of the following conditions are true, you cannot mix specific dimensions and metrics:
Metrics and dimensions are incompatible with one another. Some combinations of dimensions and metrics that can’t be searched simultaneously are stored separately in analytics. For instance, it is unable to separate data from a Google Ads integration by a dimension like Event name, such as campaign cost.
A visualisation or method cannot be used with the dimensions and metrics. You have access to cutting-edge methods for data exploration with Explorations. Every approach has a different data model that is incompatible with some dimensions and metrics. For instance, only the User and Event count metrics are supported by the pathing approach.
Additionally, you cannot mix some dimensions and metrics due to other Analytics-imposed compatibility restrictions. For instance, you might be combining custom dimensions or some user-generated content fields with demographic and interest dimensions that are no longer compatible.