> For the complete documentation index, see [llms.txt](https://biggeo.gitbook.io/datalab/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://biggeo.gitbook.io/datalab/my-library/import-data/overview.md).

# Overview

Importing data sources is the first step in bringing external datasets into the BigGeo ecosystem through **Datalab**. Once a dataset is imported into Datalab, it becomes available for indexing, use in map visualizations in **Datascape**, creation of **marketplace listings**, or packaging into **data products** for commercial or partner distribution.

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## What Is Importing?

Importing is the process of securely connecting your cloud data storage (e.g., AWS, Azure, GCP, Snowflake) to Datalab and selecting the files you want to bring into the platform. These files can include structured formats such as CSV or Parquet, and may contain both geospatial and non-geospatial data.

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## Why Import?

By importing your data into Datalab, you can:

* **Index it** to prepare it for spatial visualization.
* **Enable it** for use in **Datascape map templates**.
* **Convert it** into data products and publish to the **BigGeo Marketplace**.
* **Automate data delivery** with scheduled ETL updates.
* **Use it** in private or public sales channels using access keys or marketplace listings.

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## Import Once, Use Everywhere

Once data is imported, it’s accessible across the BigGeo platform:

* **Datalab** – Manage, clean, index, and monetize.
* **Datascape** – Visualize and interact with the dataset through maps.
* **Marketplace** – Offer your dataset to buyers with pricing, samples, and access control.

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## Next Steps

After importing a dataset, you’ll typically:

1. **Index** the dataset (select primary keys and geospatial columns).
2. **Enable compute** (hot or cold depending on performance needs).
3. **Configure** the dataset into products or listings.
4. **Use in maps** through Datascape map templates.

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## FAQs

<details>

<summary><strong>What storage types can I import from?</strong></summary>

You can import from AWS (S3), Microsoft Azure Blob Storage, Google Cloud Storage, and Snowflake.

</details>

<details>

<summary><strong>What file formats are supported?</strong></summary>

Datalab supports structured formats like CSV and Parquet.

</details>

<details>

<summary><strong>Is imported data visible immediately in Datascape?</strong></summary>

Imported data will be visible in Datascape after indexing, but only **hot compute** datasets can be used on maps.

</details>

<details>

<summary><strong>Can I update imported datasets?</strong></summary>

Yes, with ETL automation, you can schedule your dataset to update on a regular basis.

</details>