What is a Data Center?

Master Shot Studios
2 days ago
7 min read

A data center includes several key components that work together to keep data safe and accessible:

Servers: These powerful computers store and process data. They run applications, websites, and services.
Storage Systems: Devices that hold data long-term, such as hard drives and solid-state drives.
Networking Equipment: Switches, routers, and cables connect servers to each other and to the internet.
Power Supply: Backup generators and uninterruptible power supplies (UPS) ensure continuous operation during power outages.
Cooling Systems: Servers generate heat, so cooling units maintain optimal temperatures to prevent overheating.
Security Systems: Physical barriers, surveillance cameras, and access controls protect the facility from unauthorized entry.

(Equinix Editor, 2022; Jonker & Gomstyn, n.d.).

What Does a Data Center Do?

Data centers support almost every online activity. They act as the backbone of the internet and cloud computing, like when you

send an email
perform a search
post on social media
stream a video
purchase products online
use an AI-powered assistant, like ChatGPT or Google Gemini

AI applications require massive amounts of data and computing power to achieve high-speed, low-latency performance.

Data centers:

provide the infrastructure to train AI models
deliver AI services to users

Without data centers, AI would not be able to analyze data or respond in real time.

Businesses, local governments, schools, hospitals, and more rely on data centers to store records and run essential services.

(Das et al., 2025; Jonker & Gomstyn, n.d.)

Eye-level view of rows of server racks inside a data center — Interior of a data center showing server racks and cooling systems

Different Types of Data Centers

Data centers come in various sizes and types depending on their purpose:

Enterprise Data Centers: Owned and operated by a single company to support its internal operations.
Colocation Data Centers: Facilities where multiple businesses rent space to house their servers.
Cloud Data Centers: Run by cloud service providers like Amazon Web Services or Microsoft Azure, offering scalable resources to many users.
Edge Data Centers: Smaller centers located closer to users to reduce latency and improve speed for applications like gaming or video streaming.

Each type serves different needs but shares the goal of managing data efficiently.

(Equinix Editor, 2022; Jonker & Gomstyn, n.d.)

How Data Centers Support AI and Communities

AI depends heavily on data centers for both training and deployment. Training AI models requires

processing huge datasets
demands powerful servers and fast storage

For example:

AI can analyze traffic patterns to reduce congestion.
Healthcare providers use AI to assist in diagnostics.
Educational platforms use AI to personalize learning experiences.

(Equinix Editor, 2022; Han et al., 2025; Olawade et al., 2023)

Challenges Facing Data Centers

Running a data center involves several challenges:

Energy Consumption

Data centers are "energy-intensive facilities" depending on cooling systems and power backups to prevent downtime (Guidi et al., 2024; Jonker & Gomstyn, n.d.).
"Because data centers handle many types of workloads, it’s difficult to distinguish the exact share of their total electricity demand that comes from AI alone. But a typical AI-focused hyperscaler annually consumes as much electricity as 100,000 households. They can significantly strain power grids" (Leppert, 2025).
"Currently there are no legally binding energy standards that apply explicitly to operation of data centers in the private sector" (Offutt & Zhu, 2025).
"Some projections show that data center energy consumption could double or triple by 2028, accounting for up to 12% of U.S. electricity use" (Offutt and Zhu, 2025).
"Goldman Sachs anticipates that AI will drive a 165% increase in data center electricity demand by 2030" (Jonker & Gomstyn, n.d.).

Water Consumption

Data center water consumption raises concerns of water scarcity and freshwater conservation, especially at local levels (Lei and Masanet, 2022, Mytton 2021; M.A.B. Siddik et al., 2021 as cited in Lei et al., 2025).
Data centers consume a significant amount of water directly for cooling and conditioning (Lei and Masanet, 2022, as cited in Lei et al., 2025; Jonker & Gomstyn, n.d.).
"A medium-sized data center can consume up to roughly 110 million gallons of water per year for cooling purposes, equivalent to the annual water usage of approximately 1,000 households" (Yañez-Barnuevo, 2025).
"Google's data centers in The Dalles, Oregon, consumed 355 million gallons of water in 2021, representing 29% of the city's total water consumption, which has raised concerns about local water stress" (Oregon Tech, 2023 as cite in Lei et al., 2025, para. 1).
"The large volume of wastewater from data centers may overwhelm existing local facilities, which were not designed to handle such a high volume" (Yañez-Barnuevo, 2025).
Further research and sustainability practices are required to analyze workload water consumption and promote water conservation in data centers, such as innovative water management techniques to reduce water consumption (Lei et al., 2025; Yañez-Barnuevo, 2025).

Environmental Impacts

"Electricity generation has a significant environmental impact, with various forms of generation affecting air quality, water resources, and ecosystems" (Guidi et al., 2024, p. 2).
"Virginia, Texas, and Oregon had the highest CO2e emissions attributable to data centers" (Guidi et al., 2024, p. 7).
"When making decisions on when or where to operate a new data center, it will be important to use consequential methods that model the change in total emissions as a consequence of an intervention" (Guidi et al., 2024, p. 15; Han et al., 2025).
A major source of on-site pollution is the dependency on diesel backup generator (Han et al., 2025).
Data centers emit “noise and light pollution" such as, "minute vibrations of hard disks, the rumbling of air chillers, the cranking of diesel generators, the mechanical spinning of fans, and strong lighting around the data center for security purposes" (Google LLC, 2023; Mitchell, 2025). Local noise ordinances can determine ambient noise levels for sensitive locations (Google LLC, 2023).
E-waste contains harmful chemicals, heavy metals, and composites that can leach into the soil, waterways, or air if disposal and recycling are not managed carefully
"Since 2014, all of Apple’s data centers have run completely on renewable energy through various combinations of biogas fuel cells, hydropower, solar power and wind power" (Jonker & Gomstyn, n.d., para. 30).

Scalability

The rapid growth of data centers places significant strain on local and regional electric grids (Offutt & Zhu, 2025).
Localized data center surges can outpace grid capacity and complicate future scalability (Leppert, 2025).
The water intensity of data center cooling systems and identifies regional water scarcity as a major barrier to scalable expansion (Lei et al., 2025).
Scalability is constrained not only by technology but also by localized environmental tolerance (Guidi et al., 2024).
Community-level health considerations increasingly shape regulatory and social limits to scalability (Han et al., 2025).

Security

As data centers expand within local communities, perceived risks related to data misuse and privacy can trigger opposition and influence regulatory scrutiny (Leppert, 2025).
Expanding facilities increases the number of access points and security dependencies, complicating scalability at the local level (Lindsay & Hoadley, 2024).
As data centers expand within local communities, perceived risks related to data misuse and privacy can trigger opposition and influence regulatory scrutiny (Leppert, 2025).

What To Understand About Data Centers

For those new to the topic, here are some practical points:

Data centers are essential for everyday internet use.
They store and process data for websites, apps, and AI.
Different types of data centers serve different needs.
Energy efficiency, environmental impacts, and security are top priorities for both communities and businesses.
The growth of AI increases the demand for advanced data centers.

What Communities and Officials Can Do

Require Transparency

Ask for clear disclosures from data center operators about energy use, water consumption, emissions, and emergency response plans.
Support public reporting requirements so operational impacts are regularly shared with residents and local governments.
Encourage open community forums where residents can ask questions and voice concerns before approvals are granted.
Ensure information is accessible, not just technical, so all community members can understand proposed developments.

Advocate for Sustainability

Support requirements for energy efficiency and renewable energy integration to reduce strain on local grids.
Encourage water-efficient cooling technologies, especially in water-stressed or drought-prone regions.
Push for sustainability benchmarks tied to permits and expansion approvals.
Advocate for long-term environmental planning, not just short-term economic gains.
Participate in zoning hearings and planning meetings to ensure community voices are included.
Encourage setback, noise, and land-use standards that protect nearby residential and agricultural areas.

Community Engagement for Safety and Ethical Responsibility

Work with local representatives to balance economic development with public health, safety, and environmental protection.
Educate ourselves about how data centers operate and their local impacts.
Monitor policy developments and proposed expansions in our area.
Build coalitions with neighborhood groups, environmental organizations, and local businesses.
Recognize that responsible growth benefits everyone, while unmanaged expansion can create lasting community challenges.

Sources

Das, I., Das, P., Debnath, P., Chanda, M., & Nath, S. (2025). A survey on congestion control in large data centers. In Power Devices and Internet of Things for Intelligent System Design (pp. 25–86). Wiley. https://doi.org/10.1002/9781394311613.ch2

Equinix Editor. (2022, October 13). What is a data center? What are different types of data centers? Equinix Blog. https://blog.equinix.com/blog/2022/10/13/what-is-a-data-center-what-are-different-types-of-data-centers/

Google LLC. (2023). Virginia data center economic impact report. https://static.googleusercontent.com/media/www.google.com/en/about/datacenters/static/pdf/google-va-impact-report.pdf

Guidi, G., Dominici, F., Gilmour, J., Butler, K., Bell, E., Delaney, S., & Bargagli-Stoffi, F. J. (2024). Environmental burden of United States data centers in the artificial intelligence era (arXiv:2411.09786) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2411.09786

Han, Y., Wu, Z., Li, P., Wierman, A., & Ren, S. (2025). The unpaid toll: Quantifying and addressing the public health impact of data centers (arXiv:2412.06288) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2412.06288

Jonker, A., & Gomstyn, A. (n.d.). What is an AI data center? IBM Think. https://www.ibm.com/think/topics/ai-data-center

Lindsay, J. R., & Hoadley, D. S. (2024, November 22). Cybersecurity issues for data centers (CRS In Focus No. IF12959). Congressional Research Service. https://www.congress.gov/crs-product/IF12959

Lei, N., Lu, J., Shehabi, A., & Masanet, E. (2025). The water use of data center workloads: A review and assessment of key determinants. Resources, Conservation and Recycling, 219, 108310. https://doi.org/10.1016/j.resconrec.2025.108310

Leppert, R. (2025, October 24). What we know about energy use at U.S. data centers amid the AI boom. Pew Research Center. https://www.pewresearch.org/short-reads/2025/10/24/what-we-know-about-energy-use-at-us-data-centers-amid-the-ai-boom/

Mitchell, S. (2025, March 18). The staggering ecological impacts of computation and the cloud. MIT News. https://computing.mit.edu/news/the-staggering-ecological-impacts-of-computation-and-the-cloud/ (computing.mit.edu

Offutt, M. C., & Zhu, L. (2025, August 26). Data centers and their energy consumption: Frequently asked questions (CRS Report No. R48646). Congressional Research Service. https://www.congress.gov/crs-product/R48646

Olawade, D. B., Wada, O. J., David-Olawade, A. C., Kunonga, E., Abaire, O., & Ling, J. (2023). Using artificial intelligence to improve public health: A narrative review. Frontiers in Public Health, 11, Article 1196397. https://doi.org/10.3389/fpubh.2023.1196397

Yañez-Barnuevo, M. (2025, June 25). Data centers and water consumption. Environmental and Energy Study Institute (EESI). https://www.eesi.org/articles/view/data-centers-and-water-consumption

Shannon is a forward-thinking digital strategist and educator who drives purposeful, AI-informed, student-centered innovation in higher education. Shannon is pursuing an EdD at Wilkes University, researching AI adoption, digital transformation strategies, and organizational culture in higher education institutions. As Chief Creative Officer of Master Shot Studios, she blends storytelling and technology to produce impactful content for businesses and nonprofits.