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Datasets are the foundation of how DataLinks organizes and understands your information. Each dataset represents a structured table of data that can later be cleaned, connected, and queried by AI. If you’re new to DataLinks, you may want to start with the explanatory article Datasets and Namespaces to learn how datasets fit within namespaces and the broader DataLinks structure.

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Create a dataset in the web platform

If you prefer a simple, guided setup, you can create a dataset directly in the DataLinks web platform. Follow these steps:
  1. Log in to your DataLinks account.
  2. In the left navigation menu, click Create a New Dataset.
  3. Enter a name for your dataset. Choose something descriptive, such as “customer_transactions_2025.”
    Use underscores, not spaces, when creating names.
  4. Select or enter a namespace to assign the dataset to. The namespace helps organize related datasets and controls access and context.
  5. Use the toggle to set visibility to Private or Public.
  6. Click Create dataset and upload data to finish.
Your dataset will appear in your list of available datasets and will be ready for ingestion and cleaning.

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Create a dataset with the API or SDK

For users managing large amounts of data or integrating DataLinks into automated workflows, creating datasets through the API or SDK is the most efficient option. You can use either:
  • A script that calls the DataLinks API endpoint: POST Create new dataset
  • Or the DataLinks SDK, which simplifies dataset creation in just a few lines of code.
For detailed instructions and code examples, visit the API reference for Create New Dataset.

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Next steps

Once your dataset is created, you can:
  • Ingest data into it using the Ingest Data API or the web upload feature.
  • Preview or validate data before committing changes.
  • Begin linking datasets through DataLinks’ automatic connection features.
Creating a dataset is your first step toward transforming raw data into an intelligent, connected knowledge layer ready for AI and analysis.