For AI agents: the complete documentation index is available at https://docs.dataplatform.ovh.net/llms.txt, the full documentation bundle is available at https://docs.dataplatform.ovh.net/llms-full.txt, and this page is available as Markdown at https://docs.dataplatform.ovh.net/landing-page-tutorials-data-export.md.
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  • Data export & management

    The edges of a project: what leaves it, and who reaches it.

    Exports, external access and permissions

    Exporting folders with a custom date builds export paths that carry the run date, which is what downstream systems and archives usually expect. Setting role conditions on one bucket narrows an IAM role to a single bucket rather than the whole Lakehouse, using CEL conditions. Custom event handling actions let an outside system trigger a workflow with a payload, which is the inbound half of the same integration problem.

    Accessing buckets with S31-compatible tools covers the other direction, reading and writing project buckets from the AWS CLI, Rclone, NodeJS or Python instead of from the interface.

    Together they cover data lifecycle work: scheduling exports, shaping their layout, reaching data from outside, and keeping permissions tight around all of it.

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