Choosing the right data centre isn’t just a logistical decision, it’s a strategic one. A smart location boosts website performance, minimises downtime, and strengthens security. A poor choice, on the other hand, can cause headaches from slow load times to
compliance issues and inefficiencies. In the age of AI, this decision becomes even more critical, factoring in data sovereignty, compliance with local regulations, and the need for reduced latency.
Essential factors for choosing the right location
The effective operation of data centres hinges on several critical factors, with proximity to users and businesses playing a key role in enhancing performance. Hosting data near most users improves load times and leads to a smoother user experience. Tools like Google Analytics can pin-point user locations, helping businesses pick the best sites. Plus,
a nearby data centre makes management easier while partnering with the right provider can reduce the necessity for frequent physical visits.
Content Delivery Networks (CDNs) play a starring role in data centre performance. By distributing content across multiple locations, CDNs significantly speed-up delivery and reduce latency – especially for heavy data like images and videos. Even if the main data centre is located far from users, a good CDN can enhance overall website
performance.
Risk management is essential. Environmental factors like natural disasters can lead to severe service interruptions. Therefore, selecting locations based on their susceptibility to extreme weather conditions and incorporating protective measures such as fire suppression and climate control systems can mitigate these risks. Additionally, well-designed data centres include backup solutions and disaster recovery plans to ensure minimal disruption in case of emergencies.
Security is non-negotiable. From physical security like video surveillance and biometric access to prevent cyber threats, data centres must be locked down. Compliance with legal and industry standards, such as the General Data Protection Regulation (GDPR) and Payment Card Industry Data Security Standard (PCI DSS), is also vital to ensure data
protection and avoid legal complications. Finally, ensuring high uptime through multiple redundancies and backup systems is essential for maintaining continuous service, allowing data centres to operate effectively and support the increasing demands of modern digital
infrastructure.
Choosing the right data centre requires evaluating multiple factors, including location, security, compliance, and risk management. As such, organisations should work with providers that offer robust security measures, industry certifications, and redundancy systems to ensure optimal performance and reliability. By carefully assessing these
considerations, companies can select data centres that meet their needs and provide a stable, secure foundation for their online operations.
NEW EMERGING LOCATIONS FOR DATA CENTRES
AI-driven demand is leading to the rise of unconventional data centre locations. Previously overlooked regions like the United Arab Emirates (UAE), Africa (particularly Nigeria), and Eastern Europe are now gaining attention as prime data centre hubs due to several advantages, including reliable power supplies and affordable real estate.
The UAE’s investment in renewable energy supports stable power for data centres while African countries tap into renewable energy potential while the key factor making Eastern European countries attractive for hosting data centres is their ability to offer competitive energy costs. High urban land prices have made data centre expansion costly in
traditional locations. In contrast, Africa and Eastern Europe provide spacious and affordable alternatives, making them financially viable options for businesses.
Pro-business policies and supportive government regulations further enhance these regions’ appeal to investors and data centre operators. Additionally, fast-growing markets like Indonesia, India, and Malaysia are rapidly expanding their data centre infrastructure with significant investments in large-scale facilities to meet AI-driven demand.
DECENTRALISED CO-LOCATION AND DISTRIBUTED POWER SOURCES
A significant shift is occurring in data centre infrastructure, with many organisations adopting decentralised models instead of relying solely on hyperscale cloud facilities.
Enterprises continue to prioritise on-premise data centres for enhanced security, lower latency, and greater control over sensitive information.
The growth of edge computing is expanding capacity by bringing smaller regional data centres closer to end users. Technologies like 5G and the Internet of Things (IoT) are fuelling the demand for real-time data processing at the edge. Additionally, modular data centres–built using containers, prefabricated blocks, or mobile servers–enable businesses
to customise capacity based on specific needs.
This distributed approach helps overcome challenges associated with large, centralised facilities, such as long setup times, high latency, and location constraints. It also improves reliability by leveraging geographic redundancy while ensuring better alignment with local power grids and sustainability policies.
To further optimise distributed architecture, data centres are decentralising their energy sources. Rooftop solar panels offer clean supplementary power, while battery storage systems preserve surplus renewable energy for peak usage and nighttime operations. Additionally, fuel cells provide a dependable 24/7 electricity supply by efficiently
converting onsite fuel into power without producing harmful emissions.
THE RISE OF DECENTRALISED CO-LOCATION
Decentralised co-location is an emerging trend in which enterprise servers, private, and hybrid clouds are hosted across multiple third-party data centres instead of a single centralised facility. The pandemic accelerated this shift, driving demand for regional co-location to improve latency, ease network congestion, and lower backhaul costs. With more professionals working remotely and moving away from expensive urban centres, regional co-location sites are becoming essential to meet the growing needs of cloud and edge computing.
As cloud adoption expands, modern applications require low-latency and high-throughput infrastructure to ensure optimal performance. This is particularly vital for emerging technologies like 5G, IoT, driverless cars, and remote surgeries, which depend on ultra-fast processing speeds. A centralised cloud model struggles to meet these demands due to
distance-related latency, making a distributed approach necessary. The increased broadband speeds available to businesses and households have shifted the bottleneck to hyperscale data centres, further reinforcing the need to move data closer to end users. Unlike traditional co-location facilities, regional edge co-location centres serve as the
critical link between centralised cloud systems and end users. These facilities are purpose-built with high connectivity, proximity to major population centres, and integration with local internet exchanges. By processing data locally, they significantly reduce latency and enhance application responsiveness.
Companies like Proximity are investing heavily in decentralisation, opening multiple regional co-location sites across the United Kingdom (UK). Their strategy focuses on bringing data centres closer to 95% of the population, with a target of establishing 20 regional edge facilities within 15 miles of major UK conurbations. These sites provide
direct points of presence for enterprise clients, cloud providers, and mobile network operators, ensuring high-speed access and seamless connectivity.
Decentralised data centres offer several advantages, including improved energy efficiency. Smaller regional facilities typically require less cooling and power, reducing their overall carbon footprint. By leveraging geographically diverse locations, they can tap into renewable energy sources and use natural cooling methods such as ambient air or
water. This minimises dependency on traditional power grids and enhances system resiliency.
Operationally, decentralised co-location enhances security and disaster resilience by distributing resources across multiple locations. This reduces the risk of service disruption from localised failures or cyberattacks. Additionally, such systems are inherently more scalable and flexible, allowing organisations to expand or contract their infrastructure as needed without major capital investments. These efficiencies lead to significant cost savings in energy consumption, cooling, and resource allocation.
The importance of location extends beyond traditional data centres; it significantly influences AI factories that depend on data-driven processes to enhance manufacturing intelligence and stimulate economic activity. As data emerges as a pivotal resource, data centres will play a critical role in powering the future industrialisation of AI factories. By creating a robust value chain for manufacturing intelligence, these AI factories, supported by strategically located data centres, will drive future economies forward. Additionally, the
selected locations for these facilities will spur the development and modernisation of their respective regions, leading to improved amenities and infrastructure. This transformation will not only facilitate innovative manufacturing practices but also generate job opportunities, as skilled individuals will be essential for operating and managing these advanced facilities, shaping a more dynamic and prosperous economic landscape.
Why a data centre strategy is essential to power sovereign AI?
A well-defined data centre strategy is crucial for organisations (or sovereign states) to ensure scalability, performance, cost efficiency, security, disaster recovery, and seamless cloud integration. It aligns IT infrastructure with business goals, creating a resilient digital
foundation.
The first step in developing a data centre strategy is to clearly define business objectives and requirements, which is essential for creating an effective plan. Key considerations include performance, scalability, security, compliance, and cost management.
To shape the strategy effectively, organisations should begin by understanding workload requirements, identifying necessary applications, and assessing performance and security needs to plan the infrastructure accordingly. Selecting a reliable cloud provider is crucial; this involves evaluating providers based on their reliability, security measures, compliance capabilities, scalability, and pricing models.
Data governance and compliance must also be prioritised, ensuring regulatory adherence through effective data classification, encryption, access controls, and audit trails. Establishing seamless connectivity and network integration is necessary for optimising on-premises and cloud interactions.
Scalability and elasticity can be achieved through auto-scaling and load balancing, allowing the infrastructure to adjust dynamically to varying demands. Furthermore, implementing solid disaster recovery solutions, alongside defining Recovery Point Objectives (RPO) and
Recovery Time Objectives (RTO), ensures business continuity.
Cost optimisation strategies, such as resource monitoring and rightsizing, are important for managing expenses effectively. Security is another critical area, necessitating measures like multi-factor authentication and role-based access, complemented by security services
from providers. Additionally, ongoing performance monitoring using analytics tools helps track resource utilisation and latency.
Organisations should also plan for secure data migration and ensure interoperability to avoid vendor lock-in. Finally, effective vendor management, including clear Service Level Agreements (SLAs) and performance monitoring, is essential, along with a commitment to
continuous optimisation and adaptation to evolving business needs.
A robust data centre strategy ensures long-term efficiency, security, and adaptability in cloud and hybrid environments and can help sovereign nations take control of their data while building AI systems that can help them realise the most value from that data.
