> For the complete documentation index, see [llms.txt](https://whitepaper.zarela.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.zarela.io/challenges-and-solutions/data-volume.md). # Data volume It is vital to mention that data completeness and data accuracy is a preliminary requirement for an intelligent system that has been built upon the Artificial Intelligent concepts and using Machine learning and Deep learning techniques. Many intelligent systems are suffering from an absence of sufficient data sets while they could build AI and Machine learning models more easily and quickly. ### Solution for Data volume As the volume of data sets grows, intelligent systems are able to produce more accurate and reliable outcomes. Considering the presence of Proof-of-Contribution that is performed by many Mages, Hubs and Angels within Zarela’s decentralized platform we could expect big bio-signal data being created and Mages could make the most benefit out of this big data and produce better results out of their systems. --- # 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://whitepaper.zarela.io/challenges-and-solutions/data-volume.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.