Skip to main content

Documentation Index

Fetch the complete documentation index at: https://parabola.io/docs/llms.txt

Use this file to discover all available pages before exploring further.

​
What is Square?

Square is a financial services and payment processing platform that helps businesses accept payments, manage sales, and track customer transactions. It offers a suite of tools for in-person and online payments, plus customer engagement management. Square is widely used by retail stores, restaurants, and service providers to streamline operations and improve the checkout experience.

​
How to use Parabola’s Square integration

Parabola’s Square integration helps businesses automate transaction data workflows and optimize financial reporting.
  • Import and analyze Square sales, payments, and customer data automatically
  • Transform and segment transaction data for better insights and reporting
  • Sync Square data with other business tools to enhance automation and decision-making
Learn more about Parabola’s Square integration below.

​
Pull from Square

The Pull from Square step connects directly to your data in Square. Pull in data on transactions, refunds, customers, locations, and more.

​
Connect your Square account

To connect your Square account to Parabola, double-click on the Pull from Square step and click “Authorize.” A window will pop up asking you to sign in to your Square account using your email and password. Once you complete the login, you’ll see the step on Parabola connected and pulling in your data.

​
Default settings

When you first connect to the Pull from Square step, it’ll pull in Location Details which is the first option in the data type dropdown. If you click into “Advanced Settings,” you can filter locations if you have multiple locations and you want to filter to see data for those particular locations.

​
Custom settings

Here are the available data sets in the data type dropdown:
  • Location Details (see default settings)
  • Transactions
  • Refunds
  • Catalog
  • Customers
  • Employees

​
Transactions

Pulling in Transactions data will return the following columns:
  • “created_at”
  • “transaction_id”
  • “device.id”
  • “device.name”
  • “tax_money.amount”
  • “total_collected_money.amount”
  • “net_sales_money.amount”
  • “location_id”
By default, this option will pull in all data for your selected time frame. However, you can filter for the following subsets of data: Tenders, Refunds, Line Items, Transactions Report, and Item Details Report. The Timeframe will default to the Last 7 Days, but the following timeframe options are available: Last 24 Hours, Last 1 Day, Last 7 Days, Last 30 Days, Last Month, Last 3 Months, Last 6 Months, Last Year, This Year, and Custom Range. If you select the Custom Range option, you can configure a Start Date and End Date. Please make sure to provide these dates in the following format: MM-DD-YYYY. So, February 28, 2020 will be indicated as 02-28-2020. You should also set the appropriate Time Zone to use to filter for your dates. By default, the Africa/Abidjan time zone will be selected since that’s the first time zone listed in our alphabetical list. If you click into “Advanced Settings,” you’ll see an option to Filter Locations if it’d be useful to filter your data by one or many locations. You can also adjust the offset of your relative timeframe by customizing how many days, weeks, or months ago we should start the timeframe from. You can also specify a Day Start Time which will be 12:00AM as a default.

​
Refunds

Pulling in Refunds data will return the following columns:
  • “created_at”
  • “transaction_id”
  • “device.id”
  • “device.name”
  • “tax_money.amount”
  • “total_collected_money.amount”
  • “net_sales_money.amount”
  • “location_id”
By default, this option will pull in all data for your selected time frame. However, you can filter for the following subsets of data: Original Transaction Tenders, Original Transaction Line Items, Refunds Report, Item Details Report. The Timeframe, Time Zone, and Advanced Settings are all the same as the Transactions data type above.

​
Catalog

Pulling in Category data will return your item catalog including items, variations, categories, discounts, taxes, modifiers, and more. A total of 92 columns are returned.

​
Customers

Pulling in Customers data will return the following columns:
  • “id”
  • “created_at”
  • “updated_at”
  • “given_name”
  • “family_name”
  • “email_address”
  • “reference_id”
  • “preferences.email_unsubscribed”
  • “groups[0].id”
  • “groups[0].name”
  • “address.address_line_1”
  • “address.locality”
  • “address.administrative_district_level_1”
  • “address.postal_code”
  • “phone_number”

​
Employees

Pulling in Employees data will return the following columns:
  • “authorized_location_ids[0]”
  • “authorized_location_ids[1]”
  • “id”
  • “first_name”
  • “last_name”
  • “status”
  • “authorized_location_ids[2]”
  • “role_ids[0]”
  • “email”
If you click into “Advanced Settings,” you can filter locations if you have multiple locations and you want to filter to see data for those particular locations.

​
Helpful tips

  • Timeframes will always shift to only include full units of time. If you choose the last 7 days, it will begin with the most recent full day, not the partial day you are in right now. If you choose the last 3 months, it will begin with the most recent full month, not including the partial month you are in right now.
  • Inventory is not currently a supported category in the native Square integration, but you can attempt to connect Square’s API directly to pull in inventory data.
Last modified on May 1, 2026