Scheduling and configuring imports

An import pulls data from a connected source — an AWS S3 bucket, a database, Salesforce, and so on — into Trak. Once an import is set up, you can have it run on a schedule, point it at a file whose name changes every day, and tell Trak the column headings when the file itself has none. You manage imports from Data → Imports.

Only Site Admins can see and change imports. If Imports does not appear under Data, your role does not have access — ask a Site Admin.

Before you start

• You need the Site Admin role.
• The connector for your source must already be enabled under Data → Connectors. See Setting up and managing Data Connectors.
• You need an import already created for that source. The settings below are on the import's edit form.

How do I schedule an import to run automatically?

An import can run once a day at a time you choose.

1. Open the import under Data → Imports and edit it.
2. Turn on Scheduled.
3. Under Daily At, choose the hour and minute.
4. In Email Results To, enter the address that should receive the run summary.
5. Choose Save.

The import now runs every day at that time, in your workspace's time zone, and emails the result to the address you set. To stop it, turn Scheduled back off and save.

Ordering imports that depend on each other

Trak does not run imports in a set order or wait for one to finish before starting another. When one import's data depends on another — for example, deals that need their accounts imported first — schedule the later import a few minutes after the earlier one, so the first has time to finish. Give each dependent import its own time a minute or two apart.

The file name changes every day — how do I import the latest one? (AWS S3)

When a file in your S3 bucket has the date in its name or its folder path and changes on every export, use filename variables so Trak builds the current name each time it runs. This applies to the AWS S3 connector only.

In the import's Filename field, insert a variable by wrapping its key in double square brackets — [[key]]. Choose Show Variables under the field to see the available keys and click one to insert it.

Available variables (examples assume the date is 17 September 2026):

For example, a file stored at /exports/2026/09/17/deals.csv each day is matched with:

/exports/[[year]]/[[month]]/[[day]]/deals.csv

If the file holds the previous day's data, use the yesterday variables instead:

/exports/[[yesterday-year]]/[[yesterday-month]]/[[yesterday-day]]/deals.csv

As you type, Trak checks the bucket and tells you whether a file matches the name you have built.

Other file connectors work differently. Google Drive imports point at one spreadsheet you pick — to bring in new data, overwrite or update that same file rather than uploading a new one; a changing filename is not supported. Microsoft Azure imports address the file by a fixed blob name. Neither uses filename variables.

My CSV has no header row — how do I set the columns? (AWS S3)

If the source CSV does not include a header row, you can supply the column headings yourself so Trak knows what each column is. This applies to the AWS S3 connector only.

1. Open the import and edit it, with AWS S3 as the data source.
2. In CSV Headers, type the first heading and press Enter to add it. Repeat for each column, in the same left-to-right order as the file.
3. Choose Save.

Two things to get right:

• The number of headings must match the number of columns exactly. Any row whose column count does not match your headings is skipped and does not import.
• Only use this when the file truly has no header row. Once you set headings, Trak treats every line — including the first — as data. If the file already has a header row and you add headings too, that header row is imported as a record.

Keep headings to plain text. Spaces are fine; avoid special characters.

To see the columns you are working with, choose Download Source CSV on the import's page. This reflects how Trak currently reads the file, so it is a good way to confirm your headings line up before you rely on the import.

Related

• Setting up and managing Data Connectors