> For the complete documentation index, see [llms.txt](https://knowledge.aterio.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://knowledge.aterio.io/data-products/data-centers/use-cases.md). # Use Cases #### **IT Infrastructure Planning** Optimize data center placement, capacity, and timing using Aterio’s detailed project-level data—including development stage, power estimates, and square footage. Site selection and capacity planning are informed by real-time insights into where hyperscale and colocation facilities are expanding across the U.S. **Energy Consumption Analysis** Leverage Aterio’s modeled power demand by site and operator to analyze regional energy needs, load profiles, and sustainability gaps. The dataset supports utilities, grid planners, and ESG teams in understanding the operational footprint of current and future data center clusters. **Market Analysis** Assess competitive density and future supply by analyzing Aterio’s inventory of announced, under-construction, and active data centers. Filter by provider, location, or megawatt scale to identify underserved markets, regional saturation, or strategic partnership opportunities. **Policy Analysis** Support state and federal energy, land use, and infrastructure policy by tracking where data center growth is concentrated and how much power it will require. Aterio’s dataset enables proactive planning around energy resilience, water usage, and emissions associated with digital infrastructure. --- # 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://knowledge.aterio.io/data-products/data-centers/use-cases.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.