> For the complete documentation index, see [llms.txt](https://docs.sdv.dev/rdt/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sdv.dev/rdt/rdt-reversible-data-transforms.md). # RDT: Reversible Data Transforms How much effort are you spending in cleaning and processing your data? RDT (Reversible Data Transforms) is a [Python library](https://github.com/sdv-dev/RDT) that translates between real world data and cleaned, numerical data that's ready for data science. ![](https://2225246359-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVGX92M819eIp0rMg5elc%2Fuploads%2FUTGsaoq8ummfcIFB72i9%2Frdt_hypertransformer-transforming-into-numerical-data-and-back_June%2003%202025.png?alt=media\&token=4ed03e04-48d8-45f3-84f1-0a558e38948b) ## More than a formatting library Cleaning and formatting raw data is a foundational element of RDT. But you can use the library to do much more. ### :1234: Statistical Processing Normalize your data using statistical processes. This is especially useful for data science and machine learning projects. ![](https://2225246359-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVGX92M819eIp0rMg5elc%2Fuploads%2FkFEz1qGsTm53Y2ZoiNCQ%2Frdt_statistical_processing.png?alt=media\&token=95b5ee01-41c6-4d42-be9e-f66266b3fba6) ### :unlock: Anonymizing Sensitive Data Protect sensitive data while preserving the overall data format. Using RDTs, you can remove and anonymize Personal Identifiable Information. Use it to generate random, fake values that look like the original ones. ![](https://2225246359-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVGX92M819eIp0rMg5elc%2Fuploads%2FUADe4W76xAf5iO2im0NE%2Frdt_reversible-data-transforms-anonymizing-sensitive-data_June%2002%202025.png?alt=media\&token=2e604799-2797-4a35-b147-eb4b08a9dd33) ### :gem: Extracting Deeper Meaning Licensed users can extract deeper concepts that are embedded inside the data. This is particularly useful for complex data types that have a rich, real-world meaning. ![](https://2225246359-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FVGX92M819eIp0rMg5elc%2Fuploads%2FuO3UPPXnoOEJyXijFtuC%2Frdt_reversible-data-transforms-extracting-deeper-meaning_June%2002%202025.png?alt=media\&token=8a7cfb88-6559-4f60-8f0a-a1319a93604d) ## Use Cases We created RDTs with the goal of **generating synthetic data**. The RDT library transforms the raw data for machine learning, and then reverse transforms machine-generated data to match the original. Synthetic data remains a top use case for RDT today. {% hint style="info" %} If you'd like to use RDT for synthetic data, we recommend installing the [sdv library](https://sdv.dev/SDV/getting_started/install.html). It will automatically download RDT, along with other libraries to support synthetic data generation & evaluation. {% endhint %} RDT can be useful beyond the synthetic data space. You can use RDT for statistical preprocessing, contextual anonymization, or adding differential privacy as standalone projects. For more information, see [Use Cases](/rdt/resources/use-cases.md). ## Owned & Maintained by DataCebo The RDT library is a part of the [Synthetic Data Vault Project](https://sdv.dev/), first created at MIT's [Data to AI Lab](http://dai.lids.mit.edu/) in 2016. After 4 years of research and traction with enterprise, we created DataCebo in 2020 with the goal of growing the project. Today, [DataCebo](https://datacebo.com/) is the proud developer of the SDV, the largest ecosystem for synthetic data generation & evaluation. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. 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