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Using a Pigment Connection

Learn how to use a Pigment connection to create Nexadata Datasets and configure Pipeline Outputs with automatic column validation.

Lourens Kok avatar
Written by Lourens Kok
Updated over 2 months ago

Using a Pigment Connection

Once you've successfully connected Pigment to Nexadata, you can start using the connection to bring data into Nexadata (via Datasets) or send data out to Pigment (via Pipeline Outputs). This article will guide you through both processes.

Here are the key capabilities:

  • Import data using Pigment Views, Blocks, or the Payload Builder.

  • Export data back into Pigment using supported Block types (Metric, Dimension List, or Transaction List).

  • Dynamically filter selections based on your prior choices (such as Block type → Block → View).

Let’s walk through each setup process step-by-step.


Part 1: Creating a Nexadata Dataset from Pigment

A Dataset brings data from Pigment into Nexadata, enabling you to use it in your pipelines.

Step 1: Start a New Dataset

  1. Navigate to Datasets.

  2. Click Create Dataset and select Pigment as the data connection.

Step 2: Configure Dataset Properties

  • Name: Provide a clear, unique dataset name.

  • Data Connection: Choose your configured Pigment connection.

Step 3: Select Data Format

Currently, Tabular is the only supported data format when working with Pigment connections in Nexadata.

Step 4: Choose Import Type and Configure the Source

Referencing the above screenshot, label highlights the options for how to retrieve data from Pigment:

  • View – for importing from a saved Pigment view

  • Block (Metric, Table, List) – for importing directly from Pigment data blocks

  • Payload Builder (Advanced) – for fully custom JSON-based import definitions

To learn more about the Payload Builder, see Pigment’s guide: Export raw data from a Pigment block

Continuing to reference the above screenshot, label highlights the dependent dropdowns that appear based on your import type:

  • Pigment Application – Choose the Pigment application that associated with the selected connection

  • Block – Select the source Metric, Table, or List within the selected application

  • View – Pick the saved view you want to use that is related to that Block

👍 The dropdowns dynamically filter based on your selections to ensure valid configurations.

Step 5: Submit the Dataset

After reviewing and verifying your inputs, click Submit.

Your dataset is now ready to be used in Nexadata pipelines.


Part 2: Configuring a Pigment Output in a Nexadata Pipeline

You can use Pigment as a destination in your Pipelines to write transformed data back into Pigment Blocks.

Step 1: Add an Output to a Pipeline

  1. Navigate to a pipeline where your dataset is processed.

  2. Click Add Output, and choose Pigment as the output type.

Step 2: Configure the Output

  • Connection: Select your Pigment connection.

  • Pigment Application: Select your Pigment Application that is accessible via the selected connection.

  • Block Type: Choose the type of block you want to write to:

    • Metric

    • Transaction List

    • Dimension List

  • Block: Choose the specific block within the selected Pigment application.

  • View: Select the associated view if applicable.

👍 The dropdowns dynamically filter based on your selections to ensure valid configurations.

Step 3: Submit the Output

Once configured and validated:

  • Click Save Changes to add the Pigment output to your pipeline.

  • When the pipeline runs, data will be written back to Pigment as specified.


Column Mismatch Handling

When writing data back to Pigment, Nexadata checks that the columns in your pipeline output match the structure of the target Pigment block. If the columns do not align, Nexadata will stop the writeback and display a clear error message to help you identify and resolve the issue.


Example error: "Some header(s) in the mapping configuration are not found in the CSV: - Segment"

This validation helps prevent schema-related errors by informing you exactly which column is missing or incorrect.

Troubleshooting Tip

If you see a column mismatch error:

  • Review the column names in your pipeline output and verify they match the expected names in Pigment.

  • Check for exact matches in spelling, capitalization, and spacing.

  • Use the preview in Nexadata to confirm everything is aligned before submitting the pipeline.


Tips and Best Practices

  • Use Views for pre-filtered datasets or predefined logic in Pigment.

  • Choose the correct Block Type based on the target Pigment structure.

  • Validate columns early to avoid output errors and ensure schema alignment.

  • Leverage Payload Builder only for advanced use cases with custom formatting needs.

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