> For the complete documentation index, see [llms.txt](https://docs.rootcause.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rootcause.ai/more-details/data-management.md).

# Data Management

All analysis in RootCause starts with data. This section covers how to bring data into the platform and what happens to it once it arrives.

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### Getting data in

[**Selecting Data**](/more-details/data-management/uploading-datasets.md)

Upload files — tabular formats (CSV, TSV, Parquet, Excel, ODS, JSON) as well as documents and media (see [File Uploads](/more-details/data-management/uploading-datasets/file-uploads.md) for the full list) — or connect to external databases and APIs. File uploads are instant; connected sources stay in sync automatically.

For step-by-step connector setup, see [Data Connectors](/more-details/data-management/uploading-datasets/data-connectors.md).

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### Preparing for analysis

Once your data is in the platform, two further steps prepare it for causal analysis:

* [**Build Ontology**](/user-guide/ontology-concepts.md) — map column names across datasets to shared concepts so RootCause understands your data structure
* [**Build 360 Table**](/user-guide/data-views.md) — join, filter, and transform datasets into the analysis-ready view your digital twin will use

These are Steps 2 and 3 of the [seven-step workflow](/start-here/workflow.md).