Norway Data Center Market Size and Share
Market Overview
| Study Period | 2018 - 2030 |
|---|---|
| Base Year For Estimation | 2024 |
| Forecast Data Period | 2025 - 2030 |
| Market Size (2025) | USD 1.15 Billion |
| Market Size (2030) | USD 2.08 Billion |
| Growth Rate (2025 - 2030) | 12.58% CAGR |
| Market Concentration | Medium |
Major Players
*Disclaimer: Major Players sorted in no particular order Image © Mordor Intelligence. Reuse requires attribution under CC BY 4.0. |
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Norway Data Center Market Analysis by Mordor Intelligence
The Norway Data Center Market size is estimated at USD 1.15 billion in 2025, and is expected to reach USD 2.08 billion by 2030, at a CAGR of 12.58% during the forecast period (2025-2030). In terms of IT load capacity, the market is expected to grow from 0.77 thousand megawatt in 2025 to 1.99 thousand megawatt by 2030, at a CAGR of 21.03% during the forecast period (2025-2030). The market segment shares and estimates are calculated and reported in terms of MW. This sustained expansion underscores Norway’s emergence as a preferred location for AI and high-performance computing (HPC) clusters because operators can secure near-zero-carbon electricity and exploit naturally cool ambient temperatures that keep power usage effectiveness (PUE) ratios below 1.2.[1]Statistics Norway, “Weak growth in the Norwegian economy in 2024,” ssb.no Norway’s 96% renewable power mix, abundant hydropower surplus and favorable grid tariffs invite hyperscale projects such as OpenAI’s USD 2 billion Stargate campus and Microsoft’s Fairwater-class facilities.[2]IO Plus, “OpenAI to open its first AI datacenter in Europe,” ioplus.nl Operators also benefit from dense submarine and terrestrial fiber routes that reduce latency for trans-Atlantic traffic. Tier 4 design adoption is accelerating as mission-critical AI workloads demand higher fault tolerance, while heat-re-use schemes that channel waste heat into municipal district-heating grids support circular-economy goals.[3]Cloudberry Clean Energy ASA, “Second quarter and first half-year report 2024,” cloudberry.no Escalating construction costs and grid-connection delays remain the chief restraints but have not derailed announced capacity pipelines.
Key Report Takeaways
- By data-center size, massive facilities led with 37.20% of Norway data center market share in 2024; mega facilities are projected to register a 22.40% CAGR to 2030.
- By tier standard, Tier 3 accounted for 78.65% share of the Norway data center market size in 2024, while Tier 4 is forecast to expand at a 23.10% CAGR through 2030.
- By data-center type, colocation held 85.02% of Norway data center market share in 2024; hyperscale and self-built campuses are expected to advance at a 21.60% CAGR to 2030.
- By end user industry, IT and Telecom represented 45.94% revenue share in 2024 in the Norway data center market; BFSI workloads will grow fastest at 23.18% CAGR through 2030.
- By hotspot, Oslo captured 39.29% of the Norway data center market size in 2024 in the Norway data center market, whereas Vestland is on track for the highest 22.50% CAGR up to 2030.
Norway Data Center Market Trends and Insights
Drivers Impact Analysis
| Driver | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
|---|---|---|---|
| Abundant renewable hydro-power availability lowers PUE | +4.2% | National, with concentration in Vestland and northern regions | Long term (≥ 4 years) |
| Cool Nordic climate cuts annual cooling OPEX | +3.8% | National, with enhanced benefits in northern locations | Medium term (2-4 years) |
| Government incentives and pro-digital policies | +2.9% | National, with targeted regional programs | Medium term (2-4 years) |
| Dense international submarine and terrestrial fibre routes | +3.5% | Coastal regions, particularly Oslo and Vestland | Long term (≥ 4 years) |
| Surge in AI/HPC clusters leveraging Norway's green energy | +5.1% | National, with focus on grid-accessible locations | Short term (≤ 2 years) |
| Data-localisation demand for oil-and-gas digital-twin workloads | +2.2% | National, with emphasis on offshore-connected regions | Medium term (2-4 years) |
| Source: Mordor Intelligence | |||
Abundant Renewable Hydropower Availability Lowers PUE
Norway’s electricity matrix is 96% hydropower, enabling operators to lock in long-term renewable power-purchase agreements at competitive tariffs that support sustainable expansion. Cloudberry Clean Energy reported realized prices of NOK 0.59/kWh in the higher-priced NO-2 and NO-5 zones during Q2 2024, illustrating how producers pivot toward regions with strong data-center demand. The forthcoming national data-center strategy scheduled for spring 2025 is expected to formalize renewable-sourcing requirements and streamline concession processes. Nevertheless, utilities oversee roughly 8,500 MW of reserved capacity, making proximity to unconstrained substations a decisive site-selection criterion.
Cool Nordic Climate Cuts Annual Cooling OPEX
Ambient temperatures permit free-air or seawater cooling for much of the year and drive mechanical-cooling savings of up to 60% versus conventional chiller systems. Green Mountain’s fjord-water setup and Lefdal Mine Datacenter’s in-mine design illustrate how operators pair geographic advantages with liquid-cooling technology to serve dense AI racks while curbing energy overhead. The cooling edge becomes more pronounced as GPU-rich clusters such as OpenAI’s Stargate scale above 20 MW per hall.
Government Incentives and Pro-Digital Policies
Norway’s Digital Norway program waives equipment tax and expedites permitting for qualifying campuses, and the spring 2025 data-center strategy is expected to maintain investor-friendly terms while adding clarity on foreign-ownership screening. Political stability, one of the highest worldwide, underpins 20-year PPAs and multi-decade site leases. Sovereign-AI initiatives led by Telenor require facilities that meet Tier 4 uptime and zero-trust security parameters, stimulating demand for high-resilience builds.
Dense International Submarine and Terrestrial Fiber Routes
Multiple cable systems, HAVFRUE, NO-UK, HAVSIL and the forthcoming Arctic Way, connect Norway to North America, northern Europe and Asia, positioning the country as a low-latency hub for media streaming and cloud back-haul. Oslo’s OS-IX internet exchange concentrates 80% of Norway’s traffic and hosts more than 60 networks, supporting four IXPs, while Bulk Infrastructure’s 14.4 MW campus offers direct on-ramp to these networks. Far North Fiber’s planned trans-Arctic route would further enhance redundancy and latency profiles.
Restraints Impact Analysis
| Restraint | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
|---|---|---|---|
| Escalating construction costs and wage inflation | -2.8% | National, with higher impact in Oslo and urban areas | Short term (≤ 2 years) |
| Grid-connection delays and capacity constraints | -3.2% | National, with acute pressure in high-demand regions | Medium term (2-4 years) |
| Scarcity of suitably zoned land near metro areas | -1.5% | Oslo and major metropolitan areas | Medium term (2-4 years) |
| Prospective EFTA carbon tax on embodied emissions | -1.8% | National, with higher impact on new construction projects | Long term (≥ 4 years) |
| Source: Mordor Intelligence | |||
Escalating Construction Costs and Wage Inflation
Norwegian construction wages rose 5.7% in 2024, overshooting CPI and enlarging the budget envelope for data-center developers. Veidekke, Norway’s largest builder, logged NOK 41.4 billion revenue in 2024 but warned that higher steel and cement prices, amplified by NOK depreciation and EFTA carbon-border tariffs, compel tighter cost discipline. These factors can elongate payback horizons and push smaller entrants to partner with capital-rich investors.
Grid-Connection Delays and Capacity Constraints
Utilities are juggling 8,500 MW of reserved load, which elongates lead times for new substations and necessitates complex queue-management negotiations. Projects such as Cloudberry’s Sundby hydropower site are being throttled to 90% of intended output until reinforcements materialize. Developers increasingly pursue sites adjacent to under-utilized transmission corridors or consider on-site generation hybrids paired with battery storage to accelerate energization schedules.
Segment Analysis
By Data Center Size: Mega Facilities Drive Hyperscale Transition
Mega sites are scaling at a 22.40% CAGR to 2030 as hyperscalers consolidate AI and HPC capacity in contiguous campuses that simplify operations and deliver sub-1.2 PUE. In 2024, Massive facilities controlled 37.20% of Norway data center market share, but the pipeline is tilting toward Mega builds above 150 MW. Operators negotiate dedicated 132 kV feeders and deploy closed-loop liquid cooling to support racks exceeding 80 kW.
OpenAI’s Stargate blueprint demonstrates the cost-efficiency of clustering 100,000 GPUs under a single roof, while Bitdeer’s 175 MW Tydal campus illustrates how blockchain compute providers are also gravitating to large-format halls. The Norway data center market size for sub-1 MW edge sites remains steady for telecom edge caches and offshore oil-and-gas telemetry, yet their proportional weight will decline as AI demand escalates.
Note: Segment shares of all individual segments available upon report purchase
By Tier Standard: Tier 4 Growth Reflects Mission-Critical Demands
Tier 3 dominated with 78.65% share in 2024, mirroring enterprise colocation norms, yet Tier 4 is expanding at 23.10% CAGR because BFSI and sovereign-AI applications require 99.995% uptime. Norway data center market size additions through 2030 are expected to skew toward Tier 4 in Vestland and Oslo where dual-grid feeds and on-site 72-hour fuel storage can be engineered.
Telenor’s sovereign-AI factory specifies Tier 4 N+N power paths and 24/7 on-site security, reflecting how regulatory emphasis on data localization propels higher redundancy standards. Tier 1 and Tier 2 footprints remain relevant for cost-sensitive edge nodes in remote oil-field locations but capture diminishing Norway data center market share over the outlook period.
By Data Center Type: Hyperscale Expansion Challenges Colocation Dominance
Colocation retained 85.02% of Norway data center market share in 2024 because enterprises still outsource server rooms to multi-tenant providers. Hyperscale and self-build campuses, however, will rise at 21.60% CAGR, powered by cloud service providers and AI labs demanding above 50 MW blocks. This shift is already visible in Google’s Norway ground-breaking ceremony and Microsoft’s regional intake queue.
Colocation operators are responding with build-to-suit agreements and modular suites that can be converted to hyperscale footprints. Edge-optimized facilities cater to oil-and-gas digital twins that process real-time sensor data close to offshore rigs, keeping latency under 10 ms. While these facilities diversify the Norway data center industry, they will not eclipse the growth momentum of hyperscale builds.
Note: Segment shares of all individual segments available upon report purchase
By End User Industry: BFSI Growth Driven by Sovereign AI Requirements
IT and Telecom services held 45.94% revenue share in 2024 because cloud, CDN, and telco operators anchor most colocation capacity. BFSI is racing ahead at a 23.18% CAGR as banks deploy AI-driven risk analytics and adhere to stricter data localization rules introduced in 2024. The Norway data center market size allocated to BFSI workloads is forecast to double by 2030, as algorithmic trading and digital-asset custody migrate to GPU clusters hosted in Tier 4 data centers.
Manufacturing, notably oil and gas majors, continues to upload digital twin workloads that consume 5 GB/s of sensor feeds. Government agencies migrate sensitive databases to sovereign clouds that ensure residency within national borders, and media-streaming platforms expand edge caches to meet the demand for 4K streaming during global sporting events.
Geography Analysis
Oslo remains the country’s digital nerve center, aggregating 39.29% of installed IT load in 2024 and handling roughly 80% of domestic traffic through OS-IX. Financial institutions, ministries and telecom headquarters favor its sub-5 ms round-trip latency to end users. Capacity additions, however, face constraints linked to real-estate scarcity, municipal height limits and rising land-improvement levies.
Vestland, already endowed with surplus hydropower, inexpensive industrial plots and direct HAVSIL and NO-UK cable access, is clocking the fastest 22.50% CAGR. Local municipalities champion district-heating loops that absorb server-hall heat to warm adjacent housing projects, and over 50% of the regional workforce holds tertiary degrees, assuring talent continuity for facility operations. Hyperscalers exploit these advantages to deploy single-campus clusters exceeding 200 MW while benefiting from grid tariffs pegged below NOK 0.70/kWh.
Rest-of-Norway locations such as Narvik and Tydal leverage Arctic temperatures that drive PUE to 1.10 or lower. OpenAI’s Stargate in Narvik and Bitdeer’s 175 MW site in Trøndelag illustrate the frontier-region boom. These geographies often interlink with hydro reservoirs delivering firm baseload and can fast-track grid connections by tapping under-utilized 132 kV transmission spurs. Operators see value in distributing edge nodes across these locales to serve offshore rigs and research institutes that demand low-latency compute but cannot justify full hyperscale footprints.
Competitive Landscape
Market concentration is moderate: the top five operators, Green Mountain, Bulk Infrastructure, Lefdal Mine Datacenter, Digiplex, and Greenbyte, held an estimated 48% power capacity in 2024. Domestic incumbents differentiate through low-carbon energy, fjord-water or mine-water cooling, and ISO 27001/27701 compliance frameworks. Green Mountain’s SVG1-Stavanger campus delivers 24 MW via seawater cooling and has signed 10-year renewable PPAs with Statkraft to guarantee carbon-free electricity. Lefdal Mine utilizes underground caverns that provide a stable 8 °C ambient air temperature and direct seawater heat exchange, thereby reducing fan energy consumption and seismic risk.
Hyperscalers are redrawing the landscape. OpenAI and Microsoft anchor multi-hundred-MW pipelines, while Google’s Norway facility broadens its European zone footprint. Colocation incumbents respond by adding pre-fabricated data halls and courting AI tenants with liquid-cooling compatibility. Supply-chain partnerships with ABB, Schneider Electric, and Vertiv accelerate deployment timelines, and automation platforms deliver predictive maintenance and energy-optimization algorithms that hold operating expense flat even as rack densities climb.
The technology stack converges on direct-to-chip liquid cooling, white-space airflow analytics and battery energy-storage systems that smooth grid-imbalance fees. Operators secure SBTi validation for net-zero pathways and tap green-bond markets for expansion capital. These dynamics collectively nudge the Norway data center market toward larger, more energy-efficient and AI-optimized architectures.
Norway Data Center Industry Leaders
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Green Mountain AS
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Bitdeer Technologies Group
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Bulk Infrastructure Group AS
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STACK INFRASTRUCTURE
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Microsoft Corporation
- *Disclaimer: Major Players sorted in no particular order
Recent Industry Developments
- August 2025: OpenAI confirmed a USD 2 billion commitment for the Stargate campus in Narvik, targeting 290 MW and 100,000 GPUs by 2026, executed via a 50-50 joint venture with Nscale and Aker.
- May 2025: Å Energi filed for NOK 400 million (USD 37 million) Kaggefoss hydropower upgrade to reinforce local grid stability.
- April 2025: Bitdeer received approval for its 175 MW Tydal campus, energizing 70 MW with full ramp-up slated for mid-2025.
- February 2025: Google broke ground on a new Norwegian data-center site, citing renewable power and free cooling advantages.
Norway Data Center Market Report Scope
Oslo, Vestland are covered as segments by Hotspot. Large, Massive, Medium, Mega, Small are covered as segments by Data Center Size. Tier 1 and 2, Tier 3, Tier 4 are covered as segments by Tier Type. Non-Utilized, Utilized are covered as segments by Absorption.| Large |
| Massive |
| Medium |
| Mega |
| Small |
| Tier 1 and 2 |
| Tier 3 |
| Tier 4 |
| Hyperscale / Self-Built | ||
| Enterprise / Edge | ||
| Colocation | Non-Utilized | |
| Utilized | Retail Colocation | |
| Wholesale Colocation | ||
| BFSI |
| IT and ITES |
| E-Commerce |
| Government |
| Manufacturing |
| Media and Entertainment |
| Telecom |
| Other End Users |
| Oslo |
| Vestland |
| Rest of Norway |
| By Data Center Size | Large | ||
| Massive | |||
| Medium | |||
| Mega | |||
| Small | |||
| By Tier Standard | Tier 1 and 2 | ||
| Tier 3 | |||
| Tier 4 | |||
| By Data Center Type | Hyperscale / Self-Built | ||
| Enterprise / Edge | |||
| Colocation | Non-Utilized | ||
| Utilized | Retail Colocation | ||
| Wholesale Colocation | |||
| By End User Industry | BFSI | ||
| IT and ITES | |||
| E-Commerce | |||
| Government | |||
| Manufacturing | |||
| Media and Entertainment | |||
| Telecom | |||
| Other End Users | |||
| By Hotspot | Oslo | ||
| Vestland | |||
| Rest of Norway | |||
Market Definition
- IT LOAD CAPACITY - The IT load capacity or installed capacity, refers to the amount of energy consumed by servers and network equipments placed in a rack installed. It is measured in megawatt (MW).
- ABSORPTION RATE - It denotes the extend to which the data center capacity has been leased out. For instance, a 100 MW DC has leased out 75 MW, then absorption rate would be 75%. It is also referred as utilization rate and leased-out capacity.
- RAISED FLOOR SPACE - It is an elevated space build over the floor. This gap between the original floor and the elevated floor is used to accommodate wiring, cooling, and other data center equipment. This arrangement assist in having proper wiring and cooling infrastructure. It is measured in square feet (ft^2).
- DATA CENTER SIZE - Data Center Size is segmented based on the raised floor space allocated to the data center facilities. Mega DC - # of Racks must be more than 9000 or RFS (raised floor space) must be more than 225001 Sq. ft; Massive DC - # of Racks must be in between 9000 and 3001 or RFS must be in between 225000 Sq. ft and 75001 Sq. ft; Large DC - # of Racks must be in between 3000 and 801 or RFS must be in between 75000 Sq. ft and 20001 Sq. ft; Medium DC # of Racks must be in between 800 and 201 or RFS must be in between 20000 Sq. ft and 5001 Sq. ft; Small DC - # of Racks must be less than 200 or RFS must be less than 5000 Sq. ft.
- TIER TYPE - According to Uptime Institute the data centers are classified into four tiers based on the proficiencies of redundant equipment of the data center infrastructure. In this segment the data center are segmented as Tier 1,Tier 2, Tier 3 and Tier 4.
- COLOCATION TYPE - The segment is segregated into 3 categories namely Retail, Wholesale and Hyperscale Colocation service. The categorization is done based on the amount of IT load leased out to potential customers. Retail colocation service has leased capacity less than 250 kW; Wholesale colocation services has leased capacity between 251 kW and 4 MW and Hyperscale colocation services has leased capacity more than 4 MW.
- END CONSUMERS - The Data Center Market operates on a B2B basis. BFSI, Government, Cloud Operators, Media and Entertainment, E-Commerce, Telecom and Manufacturing are the major end-consumers in the market studied. The scope only includes colocation service operators catering to the increasing digitalization of the end-user industries.
| Keyword | Definition |
|---|---|
| Rack Unit | Generally referred as U or RU, it is the unit of measurement for the server unit housed in the racks in the data center. 1U is equal to 1.75 inches. |
| Rack Density | It defines the amount of power consumed by the equipment and server housed in a rack. It is measured in kilowatt (kW). This factor plays a critical role in data center design and, cooling and power planning. |
| IT Load Capacity | The IT load capacity or installed capacity, refers to the amount of energy consumed by servers and network equipment placed in a rack installed. It is measured in megawatt (MW). |
| Absorption Rate | It denotes how much of the data center capacity has been leased out. For instance, if a 100 MW DC has leased out 75 MW, then the absorption rate would be 75%. It is also referred to as utilization rate and leased-out capacity. |
| Raised Floor Space | It is an elevated space built over the floor. This gap between the original floor and the elevated floor is used to accommodate wiring, cooling, and other data center equipment. This arrangement assists in having proper wiring and cooling infrastructure. It is measured in square feet/meter. |
| Computer Room Air Conditioner (CRAC) | It is a device used to monitor and maintain the temperature, air circulation, and humidity inside the server room in the data center. |
| Aisle | It is the open space between the rows of racks. This open space is critical for maintaining the optimal temperature (20-25 °C) in the server room. There are primarily two aisles inside the server room, a hot aisle and a cold aisle. |
| Cold Aisle | It is the aisle wherein the front of the rack faces the aisle. Here, chilled air is directed into the aisle so that it can enter the front of the racks and maintain the temperature. |
| Hot Aisle | It is the aisle where the back of the racks faces the aisle. Here, the heat dissipated from the equipment’s in the rack is directed to the outlet vent of the CRAC. |
| Critical Load | It includes the servers and other computer equipment whose uptime is critical for data center operation. |
| Power Usage Effectiveness (PUE) | It is a metric which defines the efficiency of a data center. It is calculated by: (𝑇𝑜𝑡𝑎𝑙 𝐷𝑎𝑡𝑎 𝐶𝑒𝑛𝑡𝑒𝑟 𝐸𝑛𝑒𝑟𝑔𝑦 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛)/(𝑇𝑜𝑡𝑎𝑙 𝐼𝑇 𝐸𝑞𝑢𝑖𝑝𝑚𝑒𝑛𝑡 𝐸𝑛𝑒𝑟𝑔𝑦 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛). Further, a data center with a PUE of 1.2-1.5 is considered highly efficient, whereas, a data center with a PUE >2 is considered highly inefficient. |
| Redundancy | It is defined as a system design wherein additional component (UPS, generators, CRAC) is added so that in case of power outage, equipment failure, the IT equipment should not be affected. |
| Uninterruptible Power Supply (UPS) | It is a device that is connected in series with the utility power supply, storing energy in batteries such that the supply from UPS is continuous to IT equipment even during utility power is snapped. The UPS primarily supports the IT equipment only. |
| Generators | Just like UPS, generators are placed in the data center to ensure an uninterrupted power supply, avoiding downtime. Data center facilities have diesel generators and commonly, 48-hour diesel is stored in the facility to prevent disruption. |
| N | It denotes the tools and equipment required for a data center to function at full load. Only "N" indicates that there is no backup to the equipment in the event of any failure. |
| N+1 | Referred to as 'Need plus one', it denotes the additional equipment setup available to avoid downtime in case of failure. A data center is considered N+1 when there is one additional unit for every 4 components. For instance, if a data center has 4 UPS systems, then for to achieve N+1, an additional UPS system would be required. |
| 2N | It refers to fully redundant design wherein two independent power distribution system is deployed. Therefore, in the event of a complete failure of one distribution system, the other system will still supply power to the data center. |
| In-Row Cooling | It is the cooling design system installed between racks in a row where it draws warm air from the hot aisle and supplies cool air to the cold aisle, thereby maintaining the temperature. |
| Tier 1 | Tier classification determines the preparedness of a data center facility to sustain data center operation. A data center is classified as Tier 1 data center when it has a non-redundant (N) power component (UPS, generators), cooling components, and power distribution system (from utility power grids). The Tier 1 data center has an uptime of 99.67% and an annual downtime of <28.8 hours. |
| Tier 2 | A data center is classified as Tier 2 data center when it has a redundant power and cooling components (N+1) and a single non-redundant distribution system. Redundant components include extra generators, UPS, chillers, heat rejection equipment, and fuel tanks. The Tier 2 data center has an uptime of 99.74% and an annual downtime of <22 hours. |
| Tier 3 | A data center having redundant power and cooling components and multiple power distribution systems is referred to as a Tier 3 data center. The facility is resistant to planned (facility maintenance) and unplanned (power outage, cooling failure) disruption. The Tier 3 data center has an uptime of 99.98% and an annual downtime of <1.6 hours. |
| Tier 4 | It is the most tolerant type of data center. A Tier 4 data center has multiple, independent redundant power and cooling components and multiple power distribution paths. All IT equipment are dual powered, making them fault tolerant in case of any disruption, thereby ensuring interrupted operation. The Tier 4 data center has an uptime of 99.74% and an annual downtime of <26.3 minutes. |
| Small Data Center | Data center that has floor space area of ≤ 5,000 Sq. ft or the number of racks that can be installed is ≤ 200 is classified as a small data center. |
| Medium Data Center | Data center which has floor space area between 5,001-20,000 Sq. ft, or the number of racks that can be installed is between 201-800, is classified as a medium data center. |
| Large Data Center | Data center which has floor space area between 20,001-75,000 Sq. ft, or the number of racks that can be installed is between 801-3,000, is classified as a large data center. |
| Massive Data Center | Data center which has floor space area between 75,001-225,000 Sq. ft, or the number of racks that can be installed is between 3001-9,000, is classified as a massive data center. |
| Mega Data Center | Data center that has a floor space area of ≥ 225,001 Sq. ft or the number of racks that can be installed is ≥ 9001 is classified as a mega data center. |
| Retail Colocation | It refers to those customers who have a capacity requirement of 250 kW or less. These services are majorly opted by small and medium enterprises (SMEs). |
| Wholesale Colocation | It refers to those customers who have a capacity requirement between 250 kW to 4 MW. These services are majorly opted by medium to large enterprises. |
| Hyperscale Colocation | It refers to those customers who have a capacity requirement greater than 4 MW. The hyperscale demand primarily originates from large-scale cloud players, IT companies, BFSI, and OTT players (like Netflix, Hulu, and HBO+). |
| Mobile Data Speed | It is the mobile internet speed a user experiences via their smartphones. This speed is primarily dependent on the carrier technology being used in the smartphone. The carrier technologies available in the market are 2G, 3G, 4G, and 5G, where 2G provides the slowest speed while 5G is the fastest. |
| Fiber Connectivity Network | It is a network of optical fiber cables deployed across the country, connecting rural and urban regions with high-speed internet connection. It is measured in kilometer (km). |
| Data Traffic per Smartphone | It is a measure of average data consumption by a smartphone user in a month. It is measured in gigabyte (GB). |
| Broadband Data Speed | It is the internet speed that is supplied over the fixed cable connection. Commonly, copper cable and optic fiber cable are used in both residential and commercial use. Here, optic cable fiber provides faster internet speed than copper cable. |
| Submarine Cable | A submarine cable is a fiber optic cable laid down at two or more landing points. Through this cable, communication and internet connectivity between countries across the globe is established. These cables can transmit 100-200 terabits per second (Tbps) from one point to another. |
| Carbon Footprint | It is the measure of carbon dioxide generated during the regular operation of a data center. Since, coal, and oil & gas are the primary source of power generation, consumption of this power contributes to carbon emissions. Data center operators are incorporating renewable energy sources to curb the carbon footprint emerging in their facilities. |
Research Methodology
Mordor Intelligence follows a four-step methodology in all our reports.
- Step-1: Identify Key Variables: In order to build a robust forecasting methodology, the variables and factors identified in Step-1 are tested against available historical market numbers. Through an iterative process, the variables required for market forecast are set and the model is built on the basis of these variables.
- Step-2: Build a Market Model: Market-size estimations for the forecast years are in nominal terms. Inflation is not a part of the pricing, and the average selling price (ASP) is kept constant throughout the forecast period for each country.
- Step-3: Validate and Finalize: In this important step, all market numbers, variables and analyst calls are validated through an extensive network of primary research experts from the market studied. The respondents are selected across levels and functions to generate a holistic picture of the market studied.
- Step-4: Research Outputs: Syndicated Reports, Custom Consulting Assignments, Databases & Subscription Platforms
