Import Data from Databricks to Netcore

Import Databricks contact data to power targeted campaigns and journeys in Netcore CE.

Overview

The Databricks contact import moves contact data from a Databricks table or view into Netcore CE. You choose the Databricks connection, catalog, schema, and table. You map the table columns to Netcore CE attributes. You then run the import once or on a recurring schedule.

Databricks Contact Import at a Glance

Item	Detail
Source	Databricks
Destination	Netcore CE contact master, and optionally one or more lists
Location in Netcore CE	Settings > Data transfer > Import
Import type covered in this guide	Contacts
Wizard steps	Setup, Data mapping, Schedule
Required identity mapping	EMAIL (Primary key) and Updated on
Schedule options	One-time or Recurring
Recurring behavior	The first run transfers the complete dataset. Later runs transfer incremental data.

Pre-requisites

You must have an active Databricks connection of type Import in Netcore CE. See Databricks.
You must have read access to the Databricks catalog, schema, and table or view you want to import from.
Decide in advance which Netcore CE list, if any, you want to add imported contacts to.
Decide which email addresses receive import alerts. Alert email is a required field.

Start a Databricks Data Import

Follow these steps to start an import.

Log in to the Netcore CE dashboard and navigate to Settings > Data transfer.
Click the Import tab.
Click CREATE NEW. A panel titled "How would you like to start?" opens with two options: Export data and Import data.
Select Import data.
Under "What would you like to import?", select Contacts. The dropdown also lists Events. This guide covers Contacts.
Click NEXT. A panel titled "Select a source to import your data" opens. It shows two sources: Snowflake and Databricks.
Click Databricks.

The Databricks contact import wizard opens. It has three steps: Setup, Data mapping, and Schedule. A "Learn more about Databricks data imports" link appears at the top of the wizard. Click FINISH LATER at any point to save your progress and return to it later.

Step 1: Setup

The Import details section asks for the basic details of your import.

Field name	Description
Import title	A unique name for this import. Up to 80 characters.
Connection	Select an existing Databricks connection that you created under Integrations.
Path	Select the path for the import. This field stays disabled until you select a connection. A tooltip reads "Select a connection to choose a path."
Catalog	Select the Databricks catalog to import from.
Schema	Select the schema within the selected catalog.
Table	Select the table or view to import contacts from.
Type of contacts	Choose Identified or Anonymous for the imported contacts. Identified is the default.
Import contact to list(s)	Optional. By default, Netcore CE adds contacts to the contact master. You can also add them to one or more lists.
Alert email	Required. Select the email address or addresses that receive alerts about this import.

Each field after Connection stays disabled until you complete the field above it.

Preview the Table

After you select a table, click PREVIEW next to the Table field. Netcore CE opens a "Table preview" window that shows a small number of sample records with their column names and values.

Note
Sample records help you verify the data. Run a quick sanity check before you continue.

Use the preview to confirm that you picked the right table.

Click NEXT to move to Data mapping. Netcore CE saves your setup details at this point.

Step 2: Data Mapping

This step is titled "Data mapping." It asks you to map the columns of your Databricks table to the attributes in Netcore CE.

Identity Mapping

Identity mapping tells Netcore CE which Databricks column to use to match and update contact records.

Netcore attribute	Requirement
EMAIL (Primary key)	Required. Map it to the Databricks column that uniquely identifies each contact.
Updated on	Required. Map it to a Databricks column that stores when a record was last updated.

Click + ADD to add more identity mapping rows if you need them.

When you map Updated on to a column, a date time format dropdown appears next to it. The available formats are:

YYYY-MM-DD
YYYY/MM/DD
DD/MM/YYYY
DD-MM-YYYY
DD-MM-YYYY hh:mm:ss
YYYY-MM-dd HH:mm:ss.SSS XX
⚠️
Validation
If the column mapped to Updated on is not a timestamp type, or if you skip the date time format, Netcore CE outlines the field in red. Clicking NEXT shows the error "Please select a date-time format for 'Updated on'." Correct this before you continue

Attributes Mapping

Below Identity mapping, Netcore CE shows a note: "We have detected [N] columns in your table." The count includes only the columns that Identity mapping does not use.

For each detected column, Netcore CE shows:

Column	Description
Column name (Databricks)	The source column name, for example `CITY` or `SIGNUP_TIMESTAMP`.
Data type	The Databricks data type of the column, for example `STRING` or `TIMESTAMP`.
Netcore attributes	A searchable dropdown of existing Netcore CE attributes. It lists only attributes with compatible data types.
Sample data	An example value from the previewed table for that column.
Transformation	For timestamp columns, a Select date time format dropdown that uses the same format list as above.
Skip column	A checkbox that excludes the column from this import.

The Skip all checkbox above the table checks or clears every Skip column checkbox in one action.

Create a New Netcore Attribute

If no existing Netcore CE attribute matches a column, open the Netcore attributes dropdown and select + Create attribute. You create the attribute without leaving this screen.

⚠️
Validation
You must map every detected column to a Netcore attribute or mark it as Skip column. If a column stays unresolved, clicking NEXT shows the error "Please map or skip the columns you don't wish to import." Resolve every row before you continue.

Click NEXT to move to Schedule. Netcore CE saves your attribute mapping at this point.

Step 3: Schedule

This step is titled "Import schedule." It asks you to set the schedule for importing your data. The page shows your account timezone and the current date and time, for example "Timezone: Asia/Calcutta."

Select one of two options:

Option	Behavior
One-time	Netcore CE fetches and transfers the complete dataset in the selected table or view. It performs no incremental or ongoing transfer.
Recurring	The first run transfers the complete dataset from the selected table or view. All later runs transfer incremental data based on the configured schedule.

One-time Fields

Field	Description
Scheduled at	The date and time to run the single import.

Recurring Fields

Field	Description
Start date time	When the recurring schedule begins.
End date time	When the recurring schedule ends.
Frequency	How often the import repeats, for example Weekly.

Import Status and Monitoring

The Import tab of Settings > Data transfer lists every import. Each row shows these columns:

Column	Description
Data transfer info	The import title, its ID, and a status badge.
Total transfers	The number of transfers that have run.
Next transfer date	The date of the next scheduled transfer. Shows NA when none is scheduled.
Destination	The data platform linked to the import.
Module	The type of data you import, for example Contacts.
Frequency	One-time, or the recurring frequency such as Weekly.
Creation date	The date you created the import.

Status badges include Draft, Running, and Stopped.

Error Handling

Error message	Cause
"Please select a date-time format for 'Updated on'."	The Updated on identity mapping points to a column with no valid date time format selected.
"Please map or skip the columns you don't wish to import."	One or more detected columns in Attributes mapping are neither mapped to a Netcore attribute nor marked Skip column.

Important Notes and Limitations

This guide covers the Contacts import type. The "What would you like to import?" dropdown also lists Events.
A Databricks connection must exist and be active before you create an import. See Databricks.
The connection must have read access to the catalog, schema, and table you select. Netcore CE cannot list or import data that the connection cannot read.
EMAIL (Primary key) and Updated on are mandatory identity mappings. You cannot continue without them.
Click FINISH LATER to save your progress and resume the import later.

FAQs

How do I import contacts from Databricks into Netcore CE?

Go to Settings > Data transfer > Import and click CREATE NEW. Select Import data, choose Contacts, and select Databricks as the source. Then complete the Setup, Data mapping, and Schedule steps.

What do I need before I create a Databricks import?

You need an active Databricks connection of type Import, read access to the source catalog, schema, and table, and at least one alert email address.

Which fields does Netcore CE require for identity mapping?

Netcore CE requires EMAIL (Primary key) and Updated on. Map Updated on to a column that stores the last update time of each record, and select a date time format for it.

What is the difference between a One-time and a Recurring import?

A One-time import transfers the complete dataset once at the scheduled date and time. A Recurring import transfers the complete dataset on the first run, then transfers only incremental data on later runs.

Can I skip columns I do not need?

Yes. Select the Skip column checkbox for each column you want to exclude. Use Skip all to select every column at once. You must map or skip every detected column.

Can I create a new attribute during mapping?

Yes. Open the Netcore attributes dropdown for a column and select + Create attribute.

Can I save my progress and finish later?

Yes. Click FINISH LATER at any point in the wizard. Netcore CE saves your progress so you can resume later.

Which contacts does Netcore CE add to lists?

Netcore CE adds all imported contacts to the contact master. If you select one or more lists in Import contact to list(s), it also adds the contacts to those lists.

Updated 1 day ago

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