Why don't the numbers match the Google Analytics interface?

Google Analytics processes events with a delay of 24 to 48 hours, so figures for the most recent days keep changing after Renta first loads them. Set the **Overwrite period** to at least **Last 3 days**: on every run Renta reloads those days and picks up the late-processed events. On high-cardinality reports the GA4 API can also collapse rare rows into an aggregated (other) row, which the Google Analytics interface may display differently.

Can I export custom dimensions and metrics?

Yes. Renta loads the parameters list directly from your property metadata, so the property's custom dimensions and metrics appear in the picker next to the standard fields. In the destination table their column names use an underscore instead of a colon: customEvent:signup becomes customEvent_signup.

Can I sync several properties?

Each pipeline exports data for one GA4 property, so create a separate pipeline for every property you want to sync. All pipelines can share the same Google Analytics connection.

Google Analytics 4

Renta allows you to sync Google Analytics 4 data to your data warehouse: reports built from the dimensions and metrics of your GA4 property, including the property's custom dimensions and metrics.

Authentication

Renta uses OAuth to authenticate with Google. You will be redirected to Google to grant Renta limited access to your Google Analytics account.

Your credentials are encrypted in transit and at rest, and never stored in Renta's application database. You stay in control and can revoke access from your Google account settings at any time.

Connect Google Analytics 4 source

Follow these steps to add Google Analytics 4 as a source in Renta using OAuth authentication.

Go to the CatalogStep 1

Navigate to the Connections > Catalog section in the left sidebar.
Open the Analytics category and click the Google Analytics 4 card.

Google Analytics 4 card in the Analytics category of the Renta catalog

Authorize connectionStep 2

Click Log in to your Google Analytics account. You will be redirected to Google to grant access.

Authorize Google Analytics connection page in Renta

Choose a Google accountStep 3

Google shows the account selection screen. Choose the account that has access to your Google Analytics 4 properties and allow the requested access. After that you are redirected back to Renta.

Google sign-in page with the account selection list

Name the connection and saveStep 4

Finish the setup:

Source name.
Specify a name for this data source. This is used exclusively in the Renta interface.
Access granted.
Verify that the account is connected successfully.

Click Save to finish.

If your Google authorization later changes (for example, after a password change), click Re-authorize on this source. The connection refreshes in place and every pipeline built on it keeps running.

Set up your Google Analytics connection with source name and access granted

Source createdStep 5

The new source appears in the Sources list with the Active status. You can now use it in pipelines.

Sources list with the new Google Analytics 4 source

Create a pipeline

Once the source is connected, create a pipeline to sync your Google Analytics 4 data into your destination.

Create a Google Analytics 4 pipeline

Link your Google Analytics 4 source to a destination and configure the pipeline.

Select Google Analytics 4 as the sourceStep 1

In the left sidebar, click New pipeline. On the Source step, select Google Analytics 4 under Already connected and click Next step.

Select a source step with Google Analytics 4 under Already connected

Select your Google Analytics connectionStep 2

Choose the Google Analytics connection you created earlier and click Next step.

Select a destinationStep 3

On the Destination step, select your destination (for example, Google BigQuery) and click Next step.

Select a destination step with Google BigQuery

Select the destination connectionStep 4

Choose the destination connection you want to load data into and click Next step.

Select your Google BigQuery connection step

Pipeline configuration

On the final step, choose which Google Analytics 4 data to export and how Renta loads it.

Report configuration

Point the pipeline at the Google Analytics account and property you need.

Google Analytics 4 account and property selection

Accounts.
Choose the Google Analytics account available to the connected Google user.
Properties.
Choose the GA4 property to export data from. Each pipeline exports data for one property.

Dimensions and metrics

Select the GA4 parameters to include in the destination table. Your dataset schema is defined by the parameters you choose here.

Google Analytics 4 dimensions selection with the Select All button

On the Dimensions tab, check the dimensions to group the report by: date, country, device category, traffic source, and others. Use the search field to find a parameter by name, or click Select All.

Google Analytics 4 metrics selection with the Select All button

On the Metrics tab, check the metrics to export: sessions, users, events, revenue, and others. The Selected tab shows everything you picked, and the Selected Dimensions & Metrics list below the picker lets you remove a parameter.

Renta loads the parameters list directly from your property metadata, so the property's custom dimensions and metrics (customEvent and customUser fields) appear next to the standard ones. In the destination table, column names repeat the API names of the parameters, and colons in custom field names are replaced with underscores.

Include the Date dimension in the report. With it, each row in the destination table is one day, the table is partitioned by the date column, and Renta loads data incrementally. Without it, Renta reloads the whole date range on every run.

A report can include up to 9 dimensions and 10 metrics. This is a Google Analytics Data API limit. Renta validates the selected combination against the GA4 API when you create the pipeline: if the parameters are incompatible or exceed the limits, you get a validation error.

Table name and date range

Name the pipeline and set the historical period to load.

Integration name.
The name of the pipeline. It is used exclusively in the Renta interface.
Table name.
The destination table name. You can keep the auto-generated name or enter your own.
Date start.
The first date of the extraction period.
Date end.
The last date of the extraction period. Leave it as Today to keep collecting new data on every run.

Overwrite period

The overwrite period defines how many recent days Renta reloads on every run.

On each run, Renta re-fetches the report starting from the date of the last successful run minus the overwrite period. The affected days are deleted from the destination table and inserted again, while older data stays untouched. The options range from Without overwrite data to Overwrite all data; the default is Last 1 day.

Google Analytics processes events with a delay of 24 to 48 hours, so figures for the most recent days keep changing after they are first loaded. Set the overwrite period to at least Last 3 days to capture the late-processed events.

Schedule

Choose how often the pipeline runs.

Schedule type	Description
Manual	The pipeline runs only when triggered manually through the interface or via API.
Daily	The pipeline runs once a day at the specified update time.
Interval	The pipeline runs at specified time intervals.
Cron Expression	The pipeline runs on a schedule defined by a cron expression.

For Daily schedules, set the Update time, the exact time each run starts, then click Create pipeline.

Update time selection and the Create pipeline button

Renta also supports API triggers and integration with external orchestrators such as Apache Airflow, Dagster, and Prefect. See the full scheduling documentation for details.

The new pipeline appears in the Pipelines section under the ETL tab, where you can track its runs, progress, and the destination table name.

Pipelines list with the new Google Analytics 4 integration

Sync strategy

The synchronization strategy depends on whether the report includes the Date dimension.

Strategy	Supported report types	Description
Incremental	Reports that include the Date dimension	Each row is one day, and the destination table is partitioned by the `date` column. On every run Renta reloads the window from the last successful run minus the overwrite period to the end of the date range: those daily partitions are deleted and inserted again, and older partitions stay untouched.
Full reload	Reports without the Date dimension	The table has no date column to partition by, so Renta requests the whole configured date range and replaces the dataset on every run.

Changing the selected dimensions or metrics updates the table schema, so the next run after the change reloads the entire date range.

Frequently asked questions

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