> For the complete documentation index, see [llms.txt](https://data-tiles.gitbook.io/latttice-how-to-guide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://data-tiles.gitbook.io/latttice-how-to-guide/how-to-guides/data-product-workbench-for-collibra.md). # Data Product Workbench for Collibra While Collibra provides the governance foundation for managing data assets, policies, ownership, and lineage, the Data Product Workbench introduces an operational layer that allows teams to **turn governed data assets into consumable data products** without requiring traditional pipeline development. The workbench allows business users, data engineers, and data stewards to collaborate in the creation of reusable data products that can be securely shared across domains, applications, analytics tools, and AI models. **Purpose** Modern organizations struggle to move from **governed data assets** to **usable data products**. Traditional approaches often require engineering teams to build custom pipelines, transformations, and access layers for every business request. The Data Product Workbench addresses this challenge by providing a **metadata-driven environment** where governed assets from Collibra can be composed into reusable data products. These data products can then be securely accessed by analytics platforms, applications, and AI systems without requiring bespoke engineering work. **Latttice: The Data Product Workbench for Collibra** {% embed url="" %} --- # 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 dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://data-tiles.gitbook.io/latttice-how-to-guide/how-to-guides/data-product-workbench-for-collibra.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.