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Data Center Community Benefits

Case study · Infrastructure

A Policy & Data Exploration

What
What major data centers have committed to host communities, and what landed.
Stack
Python scrapers on GitHub Actions with NLP extraction; static site on Pages.
Status
LIVE
Dates
Published May 2026 · Updated June 2026
Links
Live site · Source code

Background

What tangible community benefits are major data centers actually delivering, and how does that compare to what they promised?

This catalogs what operators have publicly committed to host communities — and what those commitments look like once a campus is running. That gap is leverage. A county negotiating its first data-center agreement can see the community funds, renewable microgrids, and water-recycling investments won elsewhere — and ask for them before zoning approval, not after.

It also serves the build. Capacity only goes up fast when host communities come out clearly ahead of the load on their grid and water. The deals that actually got built are the useful template, for both sides.

A Look Inside

Each view shown on mobile and desktop — tap any image to open the live site.

A company-by-theme matrix of what major operators have publicly committed to host communities (mobile) A company-by-theme matrix of what major operators have publicly committed to host communities (desktop)
A company-by-theme matrix of what major operators have publicly committed to host communities — jobs, energy, water, tax revenue, grants, and infrastructure.
The Ratepayer Protection Pledge tracker: which hyperscalers committed on March 4, 2026 to pay for their own grid upgrades (mobile) The Ratepayer Protection Pledge tracker: which hyperscalers committed on March 4, 2026 to pay for their own grid upgrades (desktop)
The Ratepayer Protection Pledge tracker: which hyperscalers committed on March 4, 2026 to pay for their own grid upgrades — not ratepayers — and whether those commitments are showing up project by project.

How It Works

I vibe-coded this: I described the pipeline to an AI agent, let it scaffold the scrapers and extraction logic, then iterated until I trusted the output. The stack is intentionally dull and serverless, so there's nothing to keep alive day to day:

[View the Live Dashboard] | [View the Code]


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