[GA4] About Data Import

Why use Data Import?

Each business system you use generates its own data. Your CRM might contain information like customer-loyalty ratings, lifetime values, and product preferences. If you're a web publisher, your content-management system might store dimensions like author and article category. If you run an ecommerce business, you store item attributes like price, style, and size.

And you use Analytics to measure traffic and performance for your websites and apps.

Typically, each body of data exists in its own silo, uninformed by the other data. Data Import lets you join all this data in Analytics on a defined schedule in order to take down these silos, unlock new insights, and democratize your data.

How Data Import works

Uploading data

You upload CSV files that contain external data to an Analytics property. You can export those CSV files from an offline business tool like your CRM or CMS system, or for smaller amounts of data, you can create the files manually in a text editor or spreadsheet.

Data Import joins the offline data you upload with the event data that Analytics collects. The imported data enhances your reports, comparisons, and audiences. The result is a more complete picture of online and offline activity.

Joining data

Data is joined 2 different ways depending on the type of imported data:

• Collection/Processing time: Your imported data is joined with Analytics data as the Analytics data is collected and processed, as if it were collected with the event, and the joined data is written to the Analytics aggregate tables. The imported data is not joined with Analytics historical data (data that is already processed). If you delete the imported data file, no further joins take place, but the joins that have already already taken place remain.
  
  User data and offline-event data are joined at collection/processing time.

• Reporting/Query time: Your imported data is joined with Analytics data when you open a report and Analytics issues a query for the report data. This type of join is temporary: if you delete the imported data file, no further joins take place and the joined data will no longer be accessible in Analytics.
  
  Cost, item, and custom event data are joined at reporting/query time.
  
  Reporting/Query time data is not available when you're creating audiences in Analytics or when you're creating segments in Explorations.

When you import data, previously imported data will persist while appending any new imported data. Note that if the imported data has the same set of keys as previously imported data, the data will be overwritten.

Types of metadata you can import

Metadata

Importing metadata adds to the data already collected and processed by a property. Typically, metadata is stored in a custom dimension or metric, though in some cases you might want to overwrite the default information already gathered (for example, importing a product catalog with updated categories).

You can import the following data types:

• Cost data: Third-party (non-Google) ad network clicks, cost and impression data
• Item data: Product metadata like size, color, style, or other product-related dimensions
• User data: User metadata, for example, a loyalty rating or lifetime customer value, which you can use to create segments and remarketing lists
• Offline events: Offline events from sources that don't have an internet connection or that otherwise don’t support real-time event collection
• Custom event data: Import event metadata via standard fields and/or custom dimensions

Limits

You can find the current quota usage in-product through the "Quota information" button.

How to import data

When you import data, you create a data source. A data source is the combination of the CSV file you want to upload and a mapping of existing Analytics fields to the fields in your CSV. For example:

You may refer to this article if you want to understand data sources

Prerequisites for using SFTP to upload data

If you plan to use the SFTP option in Step 5, make sure your SFTP server supports the ssh-rsa and ssh-dss host-key algorithms. Learn more about verifying which host-key algorithms you use and how to format the SFTP-server URL.

Start the import process

1. In Admin, under Data collection and modification, click Data import.
   Note: The previous link opens to the last Analytics property you accessed. You can change the property using the property selector. You must be an Editor or above at the property level to successfully start the import process.
2. Create a new data source or select an existing data source. (Check the following sections.)

Create a new data source

1. Click Create data source.
2. Enter a name for your data source.
3. Select the data type:
   • Cost data (query-time import only)
   • Item data (reporting/query-time import)
   • User data by User ID (collection/processing-time import)
   • User data by Client ID (collection/processing-time import)
   • Offline events data (collection/processing-time import)
   • Custom event data (reporting/query-time import)
4. Click Review terms if prompted. This prompt is displayed if you are importing device or user data.
5. Do one of the following:
   • Select Manual CSV upload, select the CSV file on your computer, then click Open.
   Or
   • Select SFTP.
   • SFTP server user name: Enter your user name for your SFTP server.
   • SFTP server URL: Enter the URL for your SFTP server.
   • Frequency: Choose the upload frequency (Daily, Weekly, Monthly).
   • Start time: Select the hour when you want the upload to start.
   • After the data source is created, the public key for your SFTP server will be visible in the interface where you're creating the data source, and it will be available in the data-source details (refer below).
6. Click Next to proceed to the mapping stage.
7. Select the Analytics fields and imported fields you want to map to one another. Edit the field names as necessary.
8. Click Import.

Upload data to an existing data source

1. In the row for an existing data source, click Import now.
2. If the data source is configured for CSV import, then select the CSV file you want to import and click Open.

The CSV file has to include the same fields, or subset of fields, as the original. If you want to import different fields for the same data type, you need to delete the existing data source and create a new one.

Data import done in the Source Property will be automatically exported to both the roll-up and subproperties.

Verify SFTP host-key algorithms; format SFTP-server URL

View data-source details, get your SFTP public key, import new data, delete a data source

1. In Admin, under Data collection and modification, click Data import.
   Note: The previous link opens to the last Analytics property you accessed. You can change the property using the property selector.

   You must be a Viewer or above at the property level to view data source details.

2. In the row for the data source, click .

You can view the name, data type, public key, and history of each upload.

• Public key: The public SFTP server key that corresponds to a matching private key that Analytics stores (and never shares) that is used to ensure a secure, private connection between your server and Analytics data-import servers. It is vital that you authorize this public key on your server to ensure that data import can function safely and securely.
• % imported: The number of rows successfully imported divided by the number of rows in the import file. 100% means all rows successfully imported.
• Match rate: The ratio of keys in the import file that can be found in your property within the last 90 days. 100% means the data is fully useful and relevant for your data within the last 90 days.
  Note: % imported and match rate are relevant to cost, item, and custom event data import, but are not applicable to user data import or offline event data import.

To import new data:

Click Import now and choose the relevant CSV file on your computer.

To delete the data source:

1. Click > Delete data source.
2. Read the deletion notice, then click Delete data source.

You can delete Collection/Processing-time data, but if you want to remove the data that was previously uploaded from all events processed by Analytics, then you may also need to follow up with a user or user-property deletion. Deleting an already imported file will not remove the processed data that has been associated with events collected since the import was completed. You may use this article to learn more about data-deletion requests.