Skip to main content

Integrating Hightouch with Lakehouse SQL


Hightouch serves as a Reverse ETL (Extract, Transform, Load) solution, facilitating the extraction of data from a warehouse or database, and subsequently loading it into Sales, Marketing, and analytics tools via SQL, with no need for scripts. By leveraging this technology, you can synchronize your data from Skypoint AI Lakehouse SQL with Hightouch, without having to rely on APIs, CSVs, or engineering assistance. Skypoint AI is built to accommodate various analytics, machine learning, artificial intelligence, and business intelligence applications.

Skypoint AI leverages Databricks SQL to create a connection between the Lakehouse in Skypoint AI and the Hightouch client. This connection allows for the seamless loading of data into your Sales, Marketing, or analytics tools.


  • Lakehouse SQL must be provisioned in your tenant.
  • Connection details, such as Server Hostname, Port, and HTTP Path, are required to establish a connection.
  • You must also have a personal access token from Lakehouse SQL for your tenant.

Follow the below steps to integrate Hightouch with Lakehouse SQL:

Connect Hightouch to Lakehouse SQL

  1. Login in with a Hightouch account.

Alt text

  1. Click Create a workspace to create a new workspace. If you have already created a workspace, then select an existing one.

Alt text

  1. Enter a name for a new workspace and click Create workspace. You can choose Region from the drop-down list.

Alt text

  1. In the left pane, click Sources.
  2. Click Add source.

Alt text

  1. Click Databricks, and then click Continue.

Alt text

  1. Enter Server Hostname, Port, HTTP Path, and Access Token. You can get these deatils from Lakehouse > SQL access in Skypoint studio.

Alt text

  1. For Default Schema, enter the name of the target database.
  2. Click Test Connection. Make sure that testing the source returns green before continuing to the next step.
  3. Once the connection is successful, click Continue.

Alt text

  1. You can enter a name for the connection, and then click Finish.

Connect to your destination

Follow the below steps to set your destination:

  1. In the workspace navigation pane, click Destinations.

  2. Click the Add destination button to add your destination. You can also type your destination in the filter box.

Alt text

  1. Select your Destination catalog and click on Continue. For instance, in this section, we create a connection with the SendGrid connector for exporting data.

Alt text

  1. Enter API Key and then click Continue.

Alt text

  1. Enter a name for the destination, and then click Finish.

Alt text

Add a model in Hightouch

Follow the below steps to add a model in Hightouch:

  1. Select "Add model" and select the datasource for which the model has to be added.

Alt text

  1. Define the model. Hightouch provides 3 options for defining the model: Query with SQL, Create from table or view and import model from Sigma.

Alt text

  1. For instance,in this section we select Query with SQL to define a model.

  2. After the model definition, provide basic details for the model like name, description and primary key.

Alt text

  1. Click on "Finish".

Add a sync in Hightouch

To add sync for models in Hightouch, follow these steps:

  1. Click on "Add sync" and choose the model you want to sync.

Alt text

  1. Select the destination where you want the data to be synced.

Alt text

  1. Configure the sync to the destination by selecting the primary keys and mapping the necessary fields between the source and destination tables.

Alt text

  1. Set the schedule type for the sync and click "Finish".

  2. Run the sync.

Check the exported data in destination.

To check the exported data in the destination after syncing with Hightouch, follow these steps:

  1. Access the destination where the data was synced.

  2. Look for the data that was exported from the source table and confirm that it has been successfully transferred to the destination.

  3. Verify that the data is accurate and complete.

  4. If needed, perform any necessary data cleansing or transformation.

  5. The exported data is now available for further usage, such as reporting, analysis, or integration with other systems.