> For the complete documentation index, see [llms.txt](https://docs.sdv.dev/sdmetrics/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/sdmetrics/resources/enterprise/domain-specific-reports.md). # Domain Specific Reports If you are using synthetic data to solve enterprise needs, your project is a great candidate for **SDMetrics Domain Reports**. Domain Reports measure the specific objective that you want to achieve with synthetic data. ## Focus on what matters to your enterprise Synthetic data projects can fail when they evaluate too many metrics and optimize for the wrong ones. The key to adoption is focusing on your project's goals. The table below shows an example of important metrics based on your project requirements. These vary based on the project.

Project Objective	Metric: Boundary Adherence	Metric: Correlation Similarity	Metric: Category Coverage
Software testing using synthetic data	✅ Important	(not important)	✅ Important
Machine learning with synthetic data	(not important)	✅ Important	✅ Important

Domain Reports include our insights on which metrics you should prioritize. ## Save development costs & resources Creating synthetic data that perfectly optimizes every metric can be an expensive endeavor. It can require many rounds of iteration, leading you to complicated approaches. When you focus on only a few, necessary metrics, you can choose a synthetic data model that optimizes just for what you need -- and cuts costs in other areas. ## Join our partner program! The SDMetrics Domain Reports are under development as part of our SDV Premium offering. We're actively looking for key strategic partners who will receive ... :star: Additional metrics that are tailored for your specific synthetic data use case :star: Custom visualizations that you can easily share with your leadership team :star: Feature prioritization & support from the DataCebo team If you're interested in being one of our early partners, click the link below to contact the team. {% 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://docs.sdv.dev/sdmetrics/resources/enterprise/domain-specific-reports.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.