Data Centre Cable Assemblies Market (By Type: Power Cable Assemblies, Copper Data Cable Assemblies, and Fiber Optic Cable Assemblies; By Application: Power Distribution, Server and Network Connectivity, and Others; By Region: North America, Europe, Asia Pacific, and LAMEA) Industry Size, Share, Growth, Trends 2025 to 2034
The global data centre cable assemblies market size was valued at USD 267 million in 2024, is projected to reach approximately USD 447.5 million by 2034. This growth, driven by rising cloud computing adoption and data centre infrastructure expansion, is expected at a CAGR of 5.3%.
| Reports Attributes | Statistics |
| Market Size in 2024 | USD 267 Million |
| Market Size in 2025 | USD 281.15 Million |
| Market Size in 2031 | USD 383.27 Million |
| Market Size by 2034 | USD 447.5 Million |
| CAGR 2025 to 2034 | 5.3% |
| Base Year | 2024 |
| Forecast Period | 2025 to 2034 |
The data centre cable assemblies market is witnessing strong growth as digital transformation accelerates across industries and data traffic surges amid the proliferation of AI, IoT, and 5G technologies. Cable assemblies comprising pre-terminated copper and fiber-optic cables are critical components for ensuring high-performance connectivity, low latency, and reliable network operations in modern data centres. The increasing deployment of hyperscale and edge data centres, along with the demand for efficient power and data management infrastructure, is fueling market expansion.
However, high initial setup costs, space constraints, and complex maintenance requirements act as restraints for market growth. The need for skilled professionals for installation and configuration, along with the growing challenge of managing dense cabling networks, can also limit adoption in smaller facilities.
The data centre cable assemblies market is expected to grow more rapidly as artificial intelligence AI and automation transform network infrastructure design and management. Artificial intelligence enables predictive maintenance of cabling systems, detecting signal degradation or connector failures before they impact performance. Machine learning algorithms optimize network routing and bandwidth allocation, improving energy efficiency and reducing latency.
| Regions | Shares (%) |
| North America | 25% |
| Asia Pacific | 45% |
| Europe | 20% |
| LAMEA | 10% |
| Segments | Shares (%) |
| Power Cable Assemblies | 20% |
| Copper Data Cable Assemblies | 35% |
| Fiber Optic Cable Assemblies | 45% |
| Segments | Shares (%) |
| Power Distribution | 35% |
| Server and Network Connectivity | 55% |
| Others | 10% |
Published by Shubham Desale
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