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QuickBooks

This page describes how to configure a QuickBooks data source. With Data Loader, you can replicate and load your source data into your target destination.

Schema Drift Support: No.

Return to any page of this wizard by clicking Previous.

Click X in the upper-right of the UI and then click Yes, discard to close the pipeline creation wizard.


Prerequisites

  • Read the Allow-listed IP Addresses topic before you begin. You may not be able to connect to certain data sources without first allow-listing the Batch IP addresses. In these circumstances, connection tests will always fail and you will not be able to complete the pipeline.

Create pipeline

  1. In Data Loader, click Add pipeline.
  2. Choose QuickBooks from the grid of data sources.
  3. Choose Batch Loading.

Connect to QuickBooks

Configure the QuickBooks database connection settings, specifying the following:

Property Description
QuickBooks Online Connection Select a connection from the drop-down menu, or click Add Connection if one doesn't exist.
Connection Name Give a unique name for the connection, and click Connect. A new browser tab will open, where QuickBooks will ask you to confirm authorization using valid credentials.
Company ID Your QuickBooks company ID. Click Authorize. A new browser tab will open, where QuickBooks will ask you to confirm authorization using valid credentials.
Advanced settings Additional JDBC parameters or connection settings. Expand the Advanced settings, and choose a parameter from the drop-down menu. Enter a value for the parameter, and click Add parameter for any extra parameters you want to add. For a list of compatible connection properties, read Allowed connection properties.

Click Continue.


Choose tables

Choose any tables you wish to include in the pipeline. Use the arrow buttons to move tables to the Tables to extract and load listbox and then reorder any tables with click-and-drag. Additionally, select multiple tables using the SHIFT key.

Click Continue with X tables to move forward.


Review your data set

Choose the columns from each table to include in the pipeline. By default, Data Loader selects all columns from a table.

Click Configure on a table to open Configure table. This dialog lists columns in a table and the data type of each column. Additionally, you can set a primary key and assign an incremental column state to a column.

:::info{title='Note'}

  • Primary Key columns should represent a true PRIMARY KEY that uniquely identifies each record in a table. Composite keys work, but you must specify all columns that compose the key. Based on the primary key, this won't permit duplicate records. Jobs may fail or replicate data incorrectly if these rules aren't applied.
  • Make sure an Incremental column is a true change data capture (CDC) column that can identify whether there has been a change for each record in the table. This column should be a TIMESTAMP/DATE/DATETIME type or an INTEGER type representing a date key or UNIX timestamp. :::

Click Add and remove columns to modify a table before a load. Use the arrow buttons to move columns out of the Columns to extract and load listbox. Order columns with click-and-drag. Select multiple columns using SHIFT.

Click Done adding and removing to continue and then click Done.

Click Continue once you have configured each table.


Choose destination

  1. Choose an existing destination or click Add a new destination.
  2. Select a destination from Snowflake, Amazon Redshift, or Google BigQuery.

Set frequency

Property Description
Pipeline name A descriptive label for your pipeline. This is how the pipeline appears on the pipeline dashboard and how Data Loader refers to the pipeline.
Sync every The frequency at which the pipeline should sync. Day values include 1—7. Hour values include 1—23. Minute values include 5—59. The input is also the length of delay before the first sync.

Currently, you can't specify a start time.

Once you are happy with your pipeline configuration, click Create pipeline to complete the process and add the pipeline to your dashboard.