> For the complete documentation index, see [llms.txt](https://docs.infraon.io/infinity/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.infraon.io/infinity/user-guide/report.md). # Report Data without perspective can be useless. To maximize the use of data, Infraon provides attractive and easily customizable reports that ensure data monitoring is appropriate for everyone within the organization. Infraon reports provide a detailed analysis of the performance and fault-related data collected. Reports include: * Trending, pattern, and summary analysis to analyze past behavior. * Perform trend analysis and pattern analysis with historical data to help predict future behavior. Infraon's default reports are highly configurable and flexible. Collecting, summarizing, and pruning historical data makes long-term data easily manageable. The combination of real-time and historical reporting aids in identifying trends, predicting system behaviour, and making well-informed management decisions to drive future expansions. Infraon's timescale and data fields in the report filter the asset details at a granular level using the columns, timescale orders, and order by. Improvising asset report functionality, providing enhanced data analysis and filtering capabilities. Infraon supports exporting reports and pre-configured auto-reports in PDF/Excel/CSV formats. Advanced real-time and historical reporting capabilities can be customized according to user preferences to help them view essential data. --- # 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. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.infraon.io/infinity/user-guide/report.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.