---
updatedAt: 2026-08-27T14:41:47.000Z
agentTools:
  projectIndex: https://documentation.picsellia.com/llms.txt
---

# Summary & Workflow

As a summary, in this first part of the documentation related to the `Datalake`, we discovered how to:

* [Upload or import `Data`](https://documentation.picsellia.com/docs/datalake-import-data) to a `Datalake` from a local drive or from a Cloud-based bucket
* [Visualize `Data`](https://documentation.picsellia.com/docs/datalake-overview), its Properties, and its fixed or [Custom `Metadata`](https://documentation.picsellia.com/docs/datalake-metadata)
* Structure `Data` using [`DataTag`](https://documentation.picsellia.com/docs/datalake-tagging-system)
* Link several versions of the same `Data` together with [`Projections`](https://documentation.picsellia.com/docs/datalake-projections)
* Navigate and pinpoint relevant `Data` in a large `Datalake` using the [Query Language](https://documentation.picsellia.com/docs/datalake-query-language), [`Charts`](https://documentation.picsellia.com/docs/datalake-charts), or [Embeddings exploration](https://documentation.picsellia.com/docs/datalake-explore-your-data-with-embeddings)
* Automate tasks on your `Data` with [`Processings`](https://documentation.picsellia.com/docs/datalake-data-processings)
* [Select a subset of `Data` to create a `DatasetVersion`](https://documentation.picsellia.com/docs/datalake-dataset-creation)

All those actions can also be done programmatically using the [Python SDK](https://documentation.picsellia.com/reference/client).