The data center infrastructure management market is estimated at USD 1,962.3 million in 2024 from USD 1,755.2 million in 2023. The landscape is forecasted to show a CAGR of 11.8% from 2024 to 2034. The sector is set to surpass a valuation of USD 5,986.7 million from 2024 to 2034.
With growth of data centers managing diverse components becomes harder. Servers, networking, and energy systems also add to the complexity. DCIM solutions provide the essential gear to screen, manipulate, and optimize these additives efficiently, ensuring easy operations and decreasing the risk of downtime.
The rising energy expenses and growing awareness of environmental effect, data centers are below weight to come to be greater strength-green. DCIM equipment help monitor and optimize electricity usage, perceive inefficiencies, and put in force measures to reduce standard power consumption, contributing to lower operational costs and a smaller carbon footprint.
Global Data Center Infrastructure Management Industry Assessment
| Attributes | Key Insights |
|---|---|
| Historical Size, 2023 | USD 1,755.2 million |
| Estimated Size, 2024 | USD 1,962.3 million |
| Projected Size, 2034 | USD 5,986.7 million |
| Value-based CAGR (2024 to 2034) | 11.8% |
Integrating AI and gadget gaining knowledge of into DCIM solutions offers unlimited possibilities for predictive protection and automatic selection-making. AI analytics are expecting capacity failures and optimize aid allocation, improving general facts center performance and decreasing downtime.
There is a growing emphasis on sustainable practices in the statistics internal industry. Trends including the use of renewable energy sources, superior cooling solutions, and green building practices have become more frequent. DCIM solutions play an essential role in monitoring and managing with these sustainability tasks, assisting records centers gain their environmental visions.
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This below table presents the expected CAGR for the Global data center infrastructure management market over several semi-annual periods spanning from 2023 to 2033. In the first half (H1) of the year from 2023 to 2033, the business is predicted to surge at a CAGR of 9.4%, followed by a slightly higher growth rate of 10.0% in the second half (H2) of the same year.
| Particular | Value CAGR |
|---|---|
| H1 | 9.4% (2023 to 2033) |
| H2 | 10.0% (2023 to 2033) |
| H1 | 12.1% (2024 to 2034) |
| H2 | 11.7% (2024 to 2034) |
Moving into the subsequent period, from H1 2024 to H2 2034, the CAGR is projected to increase slightly to 12.1% in the first half from 2024-2034 and remain relatively moderate at 11.7% in the second half 2024-2034. In the first half (H1) 2024 the market witnessed a decrease of 60 BPS while in the second half (H2) 2024 the market witnessed an increase of 40 BPS.
Rapid Growth in Data Generation from IoT and Digital Services Necessitates Efficient Management for Data Center Infrastructure
IoT gadgets constantly acquire and transmit evidences, even as virtual offerings which include social media, e-trade, and cloud applications generate sizable quantities of statistics day by day. This inflow of information demand for statistics facilities to address massive and ever-growing volumes of facts. Efficient control of this statistics is vital to ensure that it's far stored securely, processed successfully, and reachable when wanted.
DCIM solutions provide the necessary tools to manipulate this statistics inflow, imparting visibility and control over data center operations to save blocks, optimize performance, and make certain records integrity.
Moreover, the diverse nature of statistics generated by way of IoT and digital services gives unique demanding situations. IoT gadgets, as an instance, regularly produce real-time data that desires immediately processing, while digital offerings generate huge documents requiring giant storage potential. DCIM solutions assist information facilities to evolve to these numerous needs with the aid of offering dynamic aid allocation, secure data control practices, and better scalability.
Increasing Demand for Real-time Monitoring and Analytics to Optimize Data Center Operations
Real-time tracking enables data internal operators to track the reputation of vital infrastructure components, consisting of energy, cooling, and network systems, in real-time. This visibility is critical for detecting variances, preventing ability and ensuring the fresh operation of records facilities. Real-time analytics further enhance this functionality by analyzing the enlarged data to provide actionable insights, assisting operators to make informed selections quick and optimize useful resource utilization.
Additionally, real-time monitoring and analytics are vital for maintaining high service levels and assembly stringent SLAs (Service Level Agreements). By constantly monitoring the fitness and performance of the infrastructure, data centers can proactively deal with troubles before they amplify into main troubles, thereby minimizing downtime and improving reliability.
Leveraging AI for Predictive Analytics and Automation is Driving Advancements in Data Center Infrastructure Management
AI-driven predictive analytics permit information internal operators to predict capacity difficulties before they occur, bearing in mind proactive upkeep and minimizing downtime. By reading large quantities of early and real-time records, AI can pick out patterns and traits that human operators might pass over, supplying early warnings of device failures, power variances, or cooling inefficiencies. This predictive capability guarantees that data centers can maintain most reliable overall performance and reliability, reducing the chance of sudden outages and improving normal performance.
In addition to predictive analytics, AI-driven automation is transforming how information centers are managed. Automation tools powered with the aid of AI can carry out ordinary obligations, such as useful resource provisioning, configuration control, and incident reaction, with minimal social intervention.
High Implementation Costs and Complexity is Significant Limitations
Establishing a robust DCIM system demand for significant in advance investment in each hardware and software. Data centers need to spend money on advanced monitoring gear, sensors, and software program systems which could manage the complicated necessities of present day infrastructure control.
These costs can be prohibitive, mainly for smaller groups or people with restrained budgets. Beyond the initial buy, there are ongoing prices related to software program licensing, renovation, and upgrades that could add to the economic problem. This financial constraint can deter many corporations from adopting comprehensive DCIM solutions, aside their capability advantages.
Additionally, the implementation procedure itself may be useful resource-extensive and time-ingesting. Integrating DCIM solutions into present data center environments frequently demand for extensive customization to make sure compatibility with legacy structures and workflows.
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The data center infrastructure management industry recorded a CAGR of 9.7% during the historical period between 2019 and 2023. The growth of data center infrastructure management industry was positive as it reached a value of USD 1,755.2 million in 2023 from USD 1,242.0 million in 2019.
During this era, businesses more and more prioritized the optimization in their data center operations, aiming to enhance efficiency, minimize prices, and ensure seamless overall performance. The adoption of DCIM solutions surged as groups sought complete tools to reveal, control, and optimize their complex data center infrastructures. Factors along with the growing volume of records generated, the shift in the direction of cloud computing, and the developing importance of records protection and compliance in addition driven the demand for superior DCIM technology.
Looking in advance from 2024 to 2034, the call for forecast for DCIM is predicted to preserve its upward trajectory, though with a few super shifts and trends. The speedy expansion of digital ecosystems, pushed by way of rising technologies like artificial intelligence (AI), Internet of Things (IoT), side computing, and 5G networks, will power the need for greater and adaptable DCIM solutions.
Data facilities will look an increasing number of complicated challenges, which include handling hybrid and multi-cloud environments, optimizing power intake, ensuring regulatory compliance, and enhancing cybersecurity measures.
Tier 1 carriers within the DCIM are normally huge, set up businesses with an enormous global presence and a wide range of comprehensive DCIM solutions. These companies often have robust design popularity, vast consumer bases, and a history of successful deployments in large-scale data center locations. Vendors in DCIM market include, Schneider Electric, IBM Corporation, Cisco Systems, Hewlett Packard Enterprise (HPE) and Vertiv Group Corporation.
Tier 2 vendors inside the DCIM are generally mid-sized agencies or divisions of larger corporations that offer specialized DCIM solutions concentrated on specific enterprise segments or technological niches. While they not have the equal international attain as Tier 1 vendors, Tier 2 providers regularly excel in providing tailored solutions and personalized customer support. Vendors in DCIM include, Nlyte Software, Panduit Corporation, Sunbird Software and Device42.
Tier 3 providers inside the DCIM are usually smaller agencies or startups that focus on niche areas or offer progressive solutions with specific functions. These vendors additionally have a more confined geographic presence but exceedingly competitive in particular segments. Tier 3 providers frequently differentiate themselves via specialization, agility, and a focus on emerging technologies.
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This below section covers the industry analysis for the data center infrastructure management market for different countries. This country-specific insights highlight the dynamics and growth opportunities within the data center infrastructure management market. The United States' continued dominance reflects its mature landscape and ongoing advancements in data center technologies.
India's rising prominence highlights the evolving landscape in South Asia and Pacific, driven by digital initiatives and increasing demand for efficient data center management solutions. The United States is anticipated to remain at the forefront in North America, with a value share of 68.4% through 2034. In South Asia & Pacific, India is projected to witness a CAGR of 8.6% by 2034.
| Countries | Value CAGR (2024 to 2034) |
|---|---|
| India | 15.1% |
| China | 13.5% |
| United States | 8.6% |
| Germany | 5.4% |
USA data center infrastructure management market is poised to exhibit a CAGR of 8.6% between 2024 and 2034. The country boasts advanced technological infrastructure that includes robust networking capabilities and modern data center technologies. This supports sophisticated DCIM solutions deployment and enable efficient data center resource management, monitoring, and optimization.
Several investments in data center modernization also drive growth. Companies in various industries upgrade facilities for scalability and reliability. They also seek energy efficiency, boosting advanced DCIM solutions adoption.
Germany holds around 20.8% share by 2034 in Western Europe data center infrastructure management industry amounting to a valuation of USD 67.3 million by 2034.
Germany claims an advanced technological infrastructure, including high-speed connectivity, data center facilities, and cloud computing capabilities. These technological assets enable the deployment of sophisticated DCIM solutions that provide real-time monitoring, automation, and optimization of data center operations.
Germany maintains demanding regulatory standards, particularly regarding data protection, security, and environmental sustainability. Compliance with these standards drives the adoption of robust DCIM solutions that ensure regulatory adherence and risk mitigation.
China has skilled a first frequency virtual transformation over the past few many years, with big investments in era infrastructure, such as excessive-pace networks, cloud computing offerings, and information data centers. This technological proficiency has enabled Chinese organizations to embrace superior DCIM solutions for optimizing their data in middle operations.
With a growing emphasis on performance, scalability, and reliability, Chinese businesses are increasingly turning to DCIM equipment to manipulate their complicated IT environments successfully. China is expected to continue its dominance and it currently holds around 62.9% share of the East Asia data center infrastructure management industry.
This section contains information about the leading segments in the industry. By solution, software segment is estimated to grow at a CAGR of 12.9% throughout 2034. Additionally, by industry, IT and telecommunications segment is projected to expand at 12.7% till 2034.
| Solution | Hardware |
|---|---|
| Value Share (2034) | 42.9% |
The hardware segment dominates the market in terms of revenue and will account for almost 42.9% of the market share in 2034. The essential role plays in managing and optimizing data center operations. Hardware components such as sensors, servers, networking equipment, and storage devices are essential for collecting data, monitoring performance, and ensuring efficient resource utilization within data centers.
As data centers continue to evolve with technological advancements like IoT and edge computing, hardware remains a fundamental stake in supporting their functionalities and driving growth in the DCIM market.
| Industry | IT & Telecommunications Venues |
|---|---|
| Value Share (2034) | 22.8% |
The IT and telecommunications venues segment is forecast to account for a revenue of over USD 23,577.87 million in the data center infrastructure management market by 2034 end. Data center infrastructure management plays an essential role in delivering notifications, alerts, and updates to users regarding system status, software updates, security alerts, and service interruptions. These messages are helpful in keeping users informed about critical IT proceedings in real-time, certifying smooth operations and prompt perseverance of any issues.
Key players operating in the data center infrastructure management market are investing in advanced technologies and also entering into partnerships. Key data center infrastructure management providers have also been acquiring smaller players to grow their presence to further penetrate the market across multiple regions.
Recent Industry Developments in Data Center Infrastructure Management Market
The industry is divided into cloud-based and on-premises messaging platform.
The sector is segregated into large enterprises and small and medium enterprises.
The industry is classified by BFSI, retail, healthcare, travel and hospitality, IT and telecommunications and others.
A regional analysis has been carried out in key countries of North America, Latin America, Asia Pacific, Middle East and Africa (MEA), and Europe.
The industry is projected to witness CAGR of 3.8% between 2024 and 2034.
The landscape stood at USD 68,611.80 million in 2023.
The valuation is anticipated to reach USD 103,411.71 million by 2034 end.
South Asia & Pacific is set to record the highest CAGR of 6.2% in the assessment period.
AT&T, Twilio, Telynet, Vonage, Genesys, Monty Mobile, Sinch, Infobip and Unifonic.
1. Executive Summary | Data Center Infrastructure Management Market
1.1. Global Market Outlook
1.2. Summary of Statistics
1.3. Key Market Characteristics & Attributes
1.4. FMI Analysis and Recommendations
2. Market Overview
2.1. Market Coverage / Taxonomy
2.2. Market Definition / Scope / Limitations
3. Market Risks and Trends Assessment
3.1. Risk Assessment
3.1.1. COVID-19 Crisis and Impact on Demand
3.1.2. COVID-19 Impact Benchmark with Previous Crisis
3.1.3. Impact on Market Value (US$ Million)
3.1.4. Assessment by Key Countries
3.1.5. Assessment by Key Market Segments
3.1.6. Action Points and Recommendation for Suppliers
3.2. Key Trends Impacting the Market
3.3. Formulation and Product Development Trends
4. Market Background
4.1. Market, by Key Countries
4.2. Market Opportunity Assessment (US$ Million)
4.2.1. Total Available Market
4.2.2. Serviceable Addressable Market
4.2.3. Serviceable Obtainable Market
4.3. Market Scenario Forecast
4.3.1. Demand in Optimistic Scenario
4.3.2. Demand in Likely Scenario
4.3.3. Demand in Conservative Scenario
4.4. Investment Feasibility Analysis
4.4.1. Investment in Established Markets
4.4.1.1. In Short Term
4.4.1.2. In Long Term
4.4.2. Investment in Emerging Markets
4.4.2.1. In Short Term
4.4.2.2. In Long Term
4.5. Forecast Factors - Relevance & Impact
4.5.1. Top Companies Historical Growth
4.5.2. Growth in Automation, By Country
4.5.3. Adoption Rate, By Country
4.6. Market Dynamics
4.6.1. Market Driving Factors and Impact Assessment
4.6.2. Prominent Market Challenges and Impact Assessment
4.6.3. Market Opportunities
4.6.4. Prominent Trends in the Global Market & Their Impact Assessment
5. Key Success Factors
5.1. Manufacturers’ Focus on Low Penetration High Growth Markets
5.2. Banking on with Segments High Incremental Opportunity
5.3. Peer Benchmarking
6. Global Market Demand Analysis 2015 to 2021 and Forecast, 2022 to 2032
6.1. Historical Market Analysis, 2015 to 2021
6.2. Current and Future Market Projections, 2022 to 2032
6.3. Y-o-Y Growth Trend Analysis
7. Global Market Value Analysis 2015 to 2021 and Forecast, 2022 to 2032
7.1. Historical Market Value (US$ Million) Analysis, 2015 to 2021
7.2. Current and Future Market Value (US$ Million) Projections, 2022 to 2032
7.2.1. Y-o-Y Growth Trend Analysis
7.2.2. Absolute $ Opportunity Analysis
8. Global Market Analysis 2015 to 2021 and Forecast 2022 to 2032, By Component
8.1. Introduction / Key Findings
8.2. Historical Market Value (US$ Million) and Analysis By Component, 2015 to 2021
8.3. Current and Future Market Value (US$ Million) and Analysis and Forecast By Component, 2022 to 2032
8.3.1. Solution
8.3.2. Services
8.4. Market Attractiveness Analysis By Component
9. Global Market Analysis 2015 to 2021 and Forecast 2022 to 2032, By Application
9.1. Introduction / Key Findings
9.2. Historical Market Value (US$ Million) and Analysis By Application, 2015 to 2021
9.3. Current and Future Market Value (US$ Million) and Analysis and Forecast By Application, 2022 to 2032
9.3.1. Asset Management
9.3.2. Capacity Planning
9.3.3. Power Monitoring
9.3.4. Environmental Monitoring
9.3.5. BI and Analytics
9.3.6. Others (Automated Workflow and Change Management, and Auditing and Reporting)
9.4. Market Attractiveness Analysis By Application
10. Global Market Analysis 2015 to 2021 and Forecast 2022 to 2032, By Deployment Model
10.1. Introduction / Key Findings
10.2. Historical Market Value (US$ Million) and AnalysisBy Deployment Model, 2015 to 2021
10.3. Current and Future Market Value (US$ Million) and Analysis and ForecastBy Deployment Model, 2022 to 2032
10.3.1. On-premises
10.3.2. Cloud
10.4. Market Attractiveness AnalysisBy Deployment Model
11. Global Market Analysis 2015 to 2021 and Forecast 2022 to 2032, By Data Center Type
11.1. Introduction / Key Findings
11.2. Historical Market Value (US$ Million) and Analysis By Data Center Type, 2015 to 2021
11.3. Current and Future Market Value (US$ Million) and Analysis and Forecast By Data Center Type, 2022 to 2032
11.3.1. Enterprise Data Center
11.3.2. Managed Data Center
11.3.3. Colocation Data Center
11.3.4. Cloud and Edge Data Center
11.4. Market Attractiveness Analysis By Data Center Type
12. Global Market Analysis 2015 to 2021 and Forecast 2022 to 2032, By Vertical
12.1. Introduction / Key Findings
12.2. Historical Market Value (US$ Million) and Analysis By Vertical, 2015 to 2021
12.3. Current and Future Market Value (US$ Million) and Analysis and Forecast By Vertical, 2022 to 2032
12.3.1. BFSI
12.3.2. Government and Public Sector
12.3.3. IT and ITeS
12.3.4. Manufacturing
12.3.5. Healthcare and Life Sciences
12.3.6. Telecommunications
12.3.7. Others (Retail and eCommerce, Education, and Media and Entertainment)
12.4. Market Attractiveness Analysis By Vertical
13. Global Market Analysis 2015 to 2021 and Forecast 2022 to 2032, By Region
13.1. Introduction
13.2. Historical Market Value (US$ Million) and Analysis By Region, 2015 to 2021
13.3. Current Market Size (US$ Million) & Analysis and Forecast By Region, 2022 to 2032
13.3.1. North America
13.3.2. Latin America
13.3.3. Europe
13.3.4. Asia Pacific
13.3.5. Middle East and Africa (MEA)
13.4. Market Attractiveness Analysis By Region
14. North America Market Analysis 2015 to 2021 and Forecast 2022 to 2032
14.1. Introduction
14.2. Pricing Analysis
14.3. Historical Market Value (US$ Million) and Trend Analysis By Market Taxonomy, 2015 to 2021
14.4. Market Value (US$ Million) & Forecast By Market Taxonomy, 2022 to 2032
14.4.1. By Country
14.4.1.1. United States of America
14.4.1.2. Canada
14.4.1.3. Rest of North America
14.4.2. By Deployment Model
14.4.3. By Component
14.4.4. By Application
14.4.5. By Data Center Type
14.4.6. By Vertical
14.5. Market Attractiveness Analysis
14.5.1. By Country
14.5.2. By Deployment Model
14.5.3. By Component
14.5.4. By Application
14.5.5. By Data Center Type
14.5.6. By Vertical
15. Latin America Market Analysis 2015 to 2021 and Forecast 2022 to 2032
15.1. Introduction
15.2. Pricing Analysis
15.3. Historical Market Value (US$ Million) and Trend Analysis By Market Taxonomy, 2015 to 2021
15.4. Market Value (US$ Million) & Forecast By Market Taxonomy, 2022 to 2032
15.4.1. By Country
15.4.1.1. Brazil
15.4.1.2. Mexico
15.4.1.3. Rest of Latin America
15.4.2. By Deployment Model
15.4.3. By Component
15.4.4. By Application
15.4.5. By Data Center Type
15.4.6. By Vertical
15.5. Market Attractiveness Analysis
15.5.1. By Country
15.5.2. By Deployment Model
15.5.3. By Component
15.5.4. By Application
15.5.5. By Data Center Type
15.5.6. By Vertical
16. Europe Market Analysis 2015 to 2021 and Forecast 2022 to 2032
16.1. Introduction
16.2. Pricing Analysis
16.3. Historical Market Value (US$ Million) and Trend Analysis By Market Taxonomy, 2015 to 2021
16.4. Market Value (US$ Million) & Forecast By Market Taxonomy, 2022 to 2032
16.4.1. By Country
16.4.1.1. Germany
16.4.1.2. France
16.4.1.3. United Kingdom
16.4.1.4. Italy
16.4.1.5. Russia
16.4.1.6. Rest of Europe
16.4.2. By Deployment Model
16.4.3. By Component
16.4.4. By Application
16.4.5. By Data Center Type
16.4.6. By Vertical
16.5. Market Attractiveness Analysis
16.5.1. By Country
16.5.2. By Deployment Model
16.5.3. By Component
16.5.4. By Application
16.5.5. By Data Center Type
16.5.6. By Vertical
17. Asia Pacific Market Analysis 2015 to 2021 and Forecast 2022 to 2032
17.1. Introduction
17.2. Pricing Analysis
17.3. Historical Market Value (US$ Million) and Trend Analysis By Market Taxonomy, 2015 to 2021
17.4. Market Value (US$ Million) & Forecast By Market Taxonomy, 2022 to 2032
17.4.1. By Country
17.4.1.1. China
17.4.1.2. Japan
17.4.1.3. South Korea
17.4.1.4. Rest of Asia Pacific
17.4.2. By Deployment Model
17.4.3. By Component
17.4.4. By Application
17.4.5. By Data Center Type
17.4.6. By Vertical
17.5. Market Attractiveness Analysis
17.5.1. By Country
17.5.2. By Deployment Model
17.5.3. By Component
17.5.4. By Application
17.5.5. By Data Center Type
17.5.6. By Vertical
18. Middle East and Africa Market Analysis 2015 to 2021 and Forecast 2022 to 2032
18.1. Introduction
18.2. Pricing Analysis
18.3. Historical Market Value (US$ Million) and Trend Analysis By Market Taxonomy, 2015 to 2021
18.4. Market Value (US$ Million) & Forecast By Market Taxonomy, 2022 to 2032
18.4.1. By Country
18.4.1.1. GCC Countries
18.4.1.2. South Africa
18.4.1.3. Turkey
18.4.1.4. Rest of Middle East and Africa
18.4.2. By Deployment Model
18.4.3. By Component
18.4.4. By Application
18.4.5. By Data Center Type
18.4.6. By Vertical
18.5. Market Attractiveness Analysis
18.5.1. By Country
18.5.2. By Deployment Model
18.5.3. By Component
18.5.4. By Application
18.5.5. By Data Center Type
18.5.6. By Vertical
19. Key Countries Market Analysis 2015 to 2021 and Forecast 2022 to 2032
19.1. Introduction
19.1.1. Market Value Proportion Analysis, By Key Countries
19.1.2. Global Vs. Country Growth Comparison
19.2. US Market Analysis
19.2.1. Value Proportion Analysis by Market Taxonomy
19.2.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.2.2.1. By Deployment Model
19.2.2.2. By Component
19.2.2.3. By Application
19.2.2.4. By Data Center Type
19.2.2.5. By Vertical
19.3. Canada Market Analysis
19.3.1. Value Proportion Analysis by Market Taxonomy
19.3.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.3.2.1. By Deployment Model
19.3.2.2. By Component
19.3.2.3. By Application
19.3.2.4. By Data Center Type
19.3.2.5. By Vertical
19.4. Mexico Market Analysis
19.4.1. Value Proportion Analysis by Market Taxonomy
19.4.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.4.2.1. By Deployment Model
19.4.2.2. By Component
19.4.2.3. By Application
19.4.2.4. By Data Center Type
19.4.2.5. By Vertical
19.5. Brazil Market Analysis
19.5.1. Value Proportion Analysis by Market Taxonomy
19.5.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.5.2.1. By Deployment Model
19.5.2.2. By Component
19.5.2.3. By Application
19.5.2.4. By Data Center Type
19.5.2.5. By Vertical
19.6. Germany Market Analysis
19.6.1. Value Proportion Analysis by Market Taxonomy
19.6.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.6.2.1. By Deployment Model
19.6.2.2. By Component
19.6.2.3. By Application
19.6.2.4. By Data Center Type
19.6.2.5. By Vertical
19.7. France Market Analysis
19.7.1. Value Proportion Analysis by Market Taxonomy
19.7.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.7.2.1. By Deployment Model
19.7.2.2. By Component
19.7.2.3. By Application
19.7.2.4. By Data Center Type
19.7.2.5. By Vertical
19.8. Italy Market Analysis
19.8.1. Value Proportion Analysis by Market Taxonomy
19.8.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.8.2.1. By Deployment Model
19.8.2.2. By Component
19.8.2.3. By Application
19.8.2.4. By Data Center Type
19.8.2.5. By Vertical
19.9. Russia Market Analysis
19.9.1. Value Proportion Analysis by Market Taxonomy
19.9.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.9.2.1. By Deployment Model
19.9.2.2. By Component
19.9.2.3. By Application
19.9.2.4. By Data Center Type
19.9.2.5. By Vertical
19.10. UK Market Analysis
19.10.1. Value Proportion Analysis by Market Taxonomy
19.10.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.10.2.1. By Deployment Model
19.10.2.2. By Component
19.10.2.3. By Application
19.10.2.4. By Data Center Type
19.10.2.5. By Vertical
19.11. China Market Analysis
19.11.1. Value Proportion Analysis by Market Taxonomy
19.11.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.11.2.1. By Deployment Model
19.11.2.2. By Component
19.11.2.3. By Application
19.11.2.4. By Data Center Type
19.11.2.5. By Vertical
19.12. Japan Market Analysis
19.12.1. Value Proportion Analysis by Market Taxonomy
19.12.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.12.2.1. By Deployment Model
19.12.2.2. By Component
19.12.2.3. By Application
19.12.2.4. By Data Center Type
19.12.2.5. By Vertical
19.13. South Korea Market Analysis
19.13.1. Value Proportion Analysis by Market Taxonomy
19.13.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.13.2.1. By Deployment Model
19.13.2.2. By Component
19.13.2.3. By Application
19.13.2.4. By Data Center Type
19.13.2.5. By Vertical
19.14. GCC Countries Market Analysis
19.14.1. Value Proportion Analysis by Market Taxonomy
19.14.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.14.2.1. By Deployment Model
19.14.2.2. By Component
19.14.2.3. By Application
19.14.2.4. By Data Center Type
19.14.2.5. By Vertical
19.15. South Africa Market Analysis
19.15.1. Value Proportion Analysis by Market Taxonomy
19.15.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.15.2.1. By Deployment Model
19.15.2.2. By Component
19.15.2.3. By Application
19.15.2.4. By Data Center Type
19.15.2.5. By Vertical
19.16. Turkey Market Analysis
19.16.1. Value Proportion Analysis by Market Taxonomy
19.16.2. Value & Analysis and Forecast by Market Taxonomy, 2015 to 2032
19.16.2.1. By Deployment Model
19.16.2.2. By Component
19.16.2.3. By Application
19.16.2.4. By Data Center Type
19.16.2.5. By Vertical
19.16.3. Competition Landscape and Player Concentration in the Country
20. Market Structure Analysis
20.1. Market Analysis by Tier of Companies
20.2. Market Concentration
20.3. Market Share Analysis of Top Players
20.4. Market Presence Analysis
20.4.1. By Regional Footprint of Players
20.4.2. Product Footprint by Players
21. Competition Analysis
21.1. Competition Dashboard
21.2. Competition Benchmarking
21.3. Competition Deep Dive
21.3.1. ABB
21.3.1.1. Overview
21.3.1.2. Product Portfolio
21.3.1.3. Sales Footprint
21.3.1.4. Strategy Overview
21.3.2. CommScope
21.3.2.1. Overview
21.3.2.2. Product Portfolio
21.3.2.3. Sales Footprint
21.3.2.4. Strategy Overview
21.3.3. Cormant
21.3.3.1. Overview
21.3.3.2. Product Portfolio
21.3.3.3. Sales Footprint
21.3.3.4. Strategy Overview
21.3.4. Delta Electronics
21.3.4.1. Overview
21.3.4.2. Product Portfolio
21.3.4.3. Sales Footprint
21.3.4.4. Strategy Overview
21.3.5. Device42
21.3.5.1. Overview
21.3.5.2. Product Portfolio
21.3.5.3. Sales Footprint
21.3.5.4. Strategy Overview
21.3.6. Eaton
21.3.6.1. Overview
21.3.6.2. Product Portfolio
21.3.6.3. Sales Footprint
21.3.6.4. Strategy Overview
21.3.7. FNT Software
21.3.7.1. Overview
21.3.7.2. Product Portfolio
21.3.7.3. Sales Footprint
21.3.7.4. Strategy Overview
21.3.8. Graphical Networks
21.3.8.1. Overview
21.3.8.2. Product Portfolio
21.3.8.3. Sales Footprint
21.3.8.4. Strategy Overview
21.3.9. GreenField Software
21.3.9.1. Overview
21.3.9.2. Product Portfolio
21.3.9.3. Sales Footprint
21.3.9.4. Strategy Overview
21.3.10. Hyperview
21.3.10.1. Overview
21.3.10.2. Product Portfolio
21.3.10.3. Sales Footprint
21.3.10.4. Strategy Overview
22. Assumptions and Acronyms Used
23. Research Methodology
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Data Center Infrastructure Management Market
