> For the complete documentation index, see [llms.txt](https://docs.whaly.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.whaly.io/data-management/explorations.md). # Explorations This section helps you understand what explorations are and how you can use them to achieve your goals. ## What are explorations? Exploration are a combinations of datasets, relationships and aggregations put together so that your data consumer can safely combine data and create reports without relying on technical expertise. This help you: * Boost data adoption by providing a product to your end users * Make your user more data savvy by giving them tools they understand * Maintain your company metric layer by controlling how data is being queried * Reduce maintenance when definition change - when updating a metric or a dimension all reports are subsequently updated with your changes. An exploration is the entry point to create charts in Whaly. --- # 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.whaly.io/data-management/explorations.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.