Why location data is critical to smarter data centre planning

But data centres require significant power, water, and connectivity to operate, placing increasing pressure on energy providers, water companies, and telcos. This is why trusted and accurate location data is critical to building more sustainable data centres.

The planning challenge

Many of these centres are being planned for industrial land near water sources, but the challenge lies in the suitability of those sites - from the quality and availability of water, to the treatment and recycling requirements, and the environmental impact of repurposing brownfield land. Understanding what the land was previously used for, and what habitats exist there, is also essential.

At the same time, there’s a growing focus on building new housing, and the surrounding infrastructure needed to support them. They also require analysis of existing roads, substations, and sewers.

The role of location data

Location data can answer critical questions when integrated with utilities, transport, and environmental analysis. This means tech companies, investment firms, and planners can make informed decisions about where to build and where to invest.

For local authorities, it provides the assurance needed to support planning and ensure long-term viability. Stakeholders get reliable insights to decide where to build, in line with government policy while balancing socio-economic benefits and environmental impact for neighbouring communities.

There’s also a real opportunity to use location data more proactively to inform legislation and policy, helping to answer not just where infrastructure should go, but how and why it should be developed.

Future energy networks and sustainability

With the rising demand for data centres, there will also be significant developments in the future energy network. Integrating renewable energy assets into existing systems will be crucial, as well as managing the growth of decentralised energy and ensuring network resilience. This will require smarter planning, and location data will be central to making them viable, especially when mapping terrain stability, and ecological sensitivity.

Data centres present a unique opportunity: location data can help identify areas where waste heat from these facilities could be repurposed to warm nearby homes, supporting government-backed initiatives and helping transition towards circularity in the energy sector for a more sustainable future.

Many of these data centres are being developed by global tech giants and private investment firms as a reliable long-term investment opportunity. However, building in the wrong location can expose facilities to flood risk, grid constraints, and environmental challenges. Effective planning helps prevent assets from becoming stranded and ensures facilities can continue to scale - for example, by considering the availability of renewable energy both now and in the future.

OS data can support this by providing detailed insight into the local environment, including land-use attributes, and help identify suitable locations for solar power. In addition, terrain and buildings data offer a long-term view that enables investors to make confident, data-led decisions that balance growth with sustainability.

Smaller, smarter data centres

On the other end of the data centre spectrum, innovators are developing solutions to reduce environmental impact and improve resilience offering alternatives that work alongside large-scale facilities. An example is SpaceD, a Geovation-backed start-up founded by Pegah Noori khah.

With AI driving exponential demand for data processing, Pegah saw a risk of reversing progress on decarbonisation. In London, for instance, clusters of data centres in the Isle of Dogs consume up to 75% of local electricity, delaying housing projects because grid capacity has been exhausted.

SpaceD’s solution sits at the intersection of energy tech, PropTech, and climate innovation. Its platform aggregates data from electricity grids, fibre connectivity, and the built environment to identify empty commercial sites for smaller, smarter data centres.

By leveraging OS building data alongside global connectivity datasets and grid information, SpaceD runs complex spatial algorithms. These analyses prioritise commercial buildings within local energy networks, aligning with the UK’s shift toward localised energy markets.

Pegah continued: “Take autonomous vehicles and EVs, for example. To reduce strain on local grids and support emergency technologies, we need decentralised data infrastructure. This eases pressure on the grid through smarter timing of data processing – which also generates usable heat – and places smaller data centres closer to where the data is generated. Doing so improves processing efficiency and supports sustainability by optimising energy use, while advancing technologies mean decentralised data centres can increasingly provide decentralised heat where it’s needed.”

Conclusion

The rise of data centres is reshaping the UK’s infrastructure landscape, but it requires an ecosystem where trusted data, effective infrastructure planning, and innovation come together. Using location data alongside emerging technologies could ensure these critical facilities are built in the right places - resilient, efficient, and sustainable. In turn, this enables the growth of AI and digital services, reinforcing the cycle of innovation that drives economic growth. The key to underpinning the future of the UK’s digital economy is getting the location right.