Data Management Glossary
Data Center Emissions
Data center emissions are the greenhouse gas (GHG) emissions produced by data centers during their operations. Data centers consume significant amounts of energy to power and cool their IT infrastructure, and this energy consumption often leads to the generation of carbon dioxide (CO2) and other GHG emissions. See Data Center Consolidation and Data Storage Costs.)
What contributes to data center emissions?
Traditionally the factors contributing to data center emissions have focused on the IT operations management of the physical location(s) such as:
- Electricity Consumption: The primary source of emissions in data centers is the electricity consumed to power the IT equipment, cooling systems, lighting, and other supporting infrastructure. The majority of data centers rely on electricity generated from fossil fuel sources such as coal, natural gas, or oil, which results in the release of CO2 and other GHGs.
- Cooling Systems: Data centers require cooling systems to maintain optimal operating temperatures for their IT equipment. Traditional cooling methods, such as air conditioning and refrigeration, consume significant amounts of energy, contributing to emissions. However, more energy-efficient cooling technologies, such as free cooling or liquid cooling, can help reduce emissions associated with cooling.
- Backup Power: Data centers often rely on backup power systems, such as diesel generators, to ensure continuous operations in case of a power outage. The use of backup power systems can contribute to emissions, especially if they run on fossil fuels.
- Infrastructure Efficiency: The energy efficiency of data center infrastructure plays a crucial role in emissions. Inefficient equipment, power distribution systems, and cooling mechanisms result in higher energy consumption and emissions. Implementing energy-efficient technologies and optimizing infrastructure can help reduce emissions.
Strategies to mitigate data center emissions
Again, with the focus on the physical operations of the data center, traditional strategies to reduce data center emissions include:
- Energy Efficiency: Improving energy efficiency within data centers can significantly reduce emissions. This includes using energy-efficient IT equipment, optimizing cooling systems, implementing advanced power management techniques, and adopting server virtualization to maximize resource utilization.
- Renewable Energy: Transitioning to renewable energy sources, such as solar, wind, or hydroelectric power, can help reduce the carbon footprint of data centers. Many organizations are investing in renewable energy projects or purchasing renewable energy credits to offset their electricity consumption.
- Data Center Design: Implementing energy-efficient data center designs, including proper airflow management, efficient equipment layout, and insulation, can optimize energy usage and reduce emissions.
- Lifecycle Management: Proper lifecycle management of IT equipment, including responsible disposal and recycling, can help minimize the environmental impact and emissions associated with data center operations.
- Carbon Offsetting: Some organizations choose to offset their emissions by investing in carbon offset projects. These projects aim to reduce or remove CO2 from the atmosphere, such as through reforestation or renewable energy projects.
Despite the shift to the cloud and increasingly hybrid and consolidated data centers, emissions continue to be a major a concern as the demand for lower cost data storage in the face of massive unstructured data growth as well as the demand processing power and high performance continues to grow. And while the industry continues to focus on sustainability by adopting energy-efficient practices, leveraging renewable energy sources, and seeking new ways to reduce emissions, the environmental impact of data center emissions cannot be denied.
Data Management and Data Center Emissions
It is only recently that enterprise IT organizations have been to focus on unstructured data management, as opposed to storage management, as a means to reduce data center emissions. In a post on the Azure Storage blog, the point is made about the true cost of traditional file data. The post points out that storage is only 25% of file data costs:
When looking at the storage cost of file data, you need to consider that the cost of file data is at least three to four times higher than the cost of the file storage itself. The reason is that beyond storage, IT teams must also protect it with backups and replicate it for disaster recovery.
The point is that with better data management practices, data growth will be managed, emissions (and costs) will be reduced.
Read the eBook: 8 Ways to Reduce File Storage and Backup Costs.
Data Center Emissions FAQs
How is AI driving a new wave of data center emissions?
AI has fundamentally changed the energy consumption profile of the data center industry. Training large AI models requires enormous amounts of compute, and a single large AI model training run can consume 50 gigawatt-hours of electricity, enough to power a major US city for several days. The power required to train these models is estimated to double annually as organizations compete to develop larger and more capable AI systems.
The IEA projects that global data center electricity consumption will reach 945 TWh by 2030 in its central scenario, with AI’s share of data center power use potentially rising from under 15% recently to 35-50% by 2030. US data centers already account for more than 4% of total US electricity consumption, with 56% of that power derived from fossil fuels. For enterprise IT leaders with sustainability mandates, the AI buildout is creating direct tension between AI program investment and emissions reduction commitments.
Source: IEA Energy and AI report 2025
Source: Congress.gov Data Centers and Energy Consumption FAQ 2025
Source: Carbon Brief data center emissions analysis 2025
How does unstructured data growth contribute to data center emissions and what can organizations do about it?
Most enterprise sustainability programs focus on data center infrastructure: switching to renewable energy, improving cooling efficiency, and optimizing hardware utilization. What they less commonly address is the data itself. Unstructured data, which now represents 80-90% of all enterprise data and grows at 55-65% annually, is one of the primary drivers of storage infrastructure expansion. Every petabyte of cold, inactive unstructured data sitting on primary flash-based NAS requires power to store, power to cool, and additional power to back up, replicate, and protect. Storage is only 25% of file data costs: IT teams must also protect it with backups and replicate it for disaster recovery, meaning the total energy footprint of unstructured data is three to four times higher than the storage footprint alone.
Reducing the unstructured data footprint through intelligent data lifecycle management is one of the most direct levers available to enterprise IT teams seeking to reduce data center emissions without compromising data availability or AI readiness. Organizations that tier cold unstructured data to lower-power cloud or object storage reduce the energy consumed by primary NAS systems, reduce backup and replication workloads, and free primary storage capacity for AI workloads that genuinely require high-performance infrastructure. Komprise customers consistently reclaim 70% or more of primary NAS capacity through intelligent tiering, which translates directly to a smaller active storage footprint and lower associated energy consumption.
Source: Microsoft Azure true cost of file storage blog
Source: Komprise State of Unstructured Data Management reports
What is the connection between data lifecycle management and reducing data center emissions?
Data lifecycle management determines how long data occupies high-energy primary storage before being moved to lower-energy tiers or deleted. Most enterprise organizations lack systematic lifecycle management for unstructured data, which means data accumulates on primary storage indefinitely by default. A file that was actively used three years ago and has not been accessed since continues to consume primary storage power, cooling, and backup energy for as long as it remains on primary storage, regardless of whether it has any remaining business value.
Effective data lifecycle management addresses this by applying automated, policy-based rules that continuously identify and act on data based on its actual value and access patterns. Tiering cold data to cloud or object storage reduces the energy burden on primary NAS environments. Identifying and removing ROT data eliminates the energy cost of storing data with no remaining value. Classifying and governing sensitive data prevents unnecessary copies and replicas that compound storage and energy footprints. Komprise Intelligent Data Management supports all three approaches through continuous lifecycle automation, with the Global Metadatabase providing the unified visibility needed to make informed decisions about what data should stay, what should be tiered, and what should be retired.
How can Komprise help organizations reduce their data center emissions footprint through unstructured data management?
Komprise addresses data center emissions through the same capabilities that reduce storage costs, because energy consumption and storage cost are closely correlated. Every terabyte of data tiered from primary flash-based NAS to lower-power cloud or object storage reduces the energy consumed by that primary storage system, the cooling required to maintain it, and the backup and replication workloads that protect it.
Komprise scans across all NAS and cloud storage environments to identify cold and inactive data, quantifying exactly how much primary storage capacity is occupied by data that has not been accessed within defined thresholds. Komprise Intelligent Tiering then moves that cold data to lower-cost, lower-energy cloud or object storage automatically based on policy, with users continuing to access tiered data transparently via Dynamic Links. For organizations building sustainability reporting, the Global Metadatabase provides an auditable record of all data movements, classification decisions, and lifecycle actions, supporting the data lineage and governance documentation that ESG reporting increasingly requires. Reducing the active storage footprint of unstructured data is one of the most practical and immediately measurable contributions that enterprise IT can make to an organization’s overall emissions reduction program.