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Global Telecom Cloud Market to reach USD 104.47 billion by the end of 2030

Global Telecom Cloud Market Size study & Forecast, by Component (Solution, Services) by Deployment Type (Private, Public, Hybrid) by Service Model (Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS)), by Application (Network, Data Storage, and Computing, Traffic Management, Cloud Migration, Others), by Enterprise Size (Large Enterprises, SMEs) and Regional Analysis, 2023-2030

Product Code: ICTBC-25062614
Publish Date: 20-02-2024
Page: 200

Global Telecom Cloud Market is valued at approximately USD 24.46 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 19.9% over the forecast period 2023-2030. Telecom Cloud is the utilization of cloud computing technologies and services within the telecommunications industry to enhance and streamline various aspects of network infrastructure, operations, and service delivery. This innovative approach involves migrating traditional telecommunications functions, such as network management, storage, and communication services, to virtualized and scalable cloud environments. By leveraging cloud resources, telecom operators can achieve greater flexibility, scalability, and cost-effectiveness in managing their networks and services. The Telecom Cloud Market is expanding because of factors such as rising Network Virtualization and SDN Adoption, rollout of 5G networks and proliferation of connected devices and mobile data traffic.

The escalating proliferation of connected devices and the surge in mobile data traffic are pivotal drivers propelling the growth of the Telecom Cloud Market. As the number of connected devices continues to multiply, ranging from smartphones and tablets to IoT devices, there is an unprecedented demand for scalable and efficient network infrastructure. Telecom Cloud solutions offer a dynamic and cost-effective approach to managing the increasing data traffic by providing virtualized and flexible resources. This enables telecom operators to accommodate the diverse needs of connected devices and deliver seamless connectivity. As per Ericsson’s projections, the global total mobile data traffic is anticipated to persist in its upward trajectory, potentially reaching 131 exabytes per month by the conclusion of 2024. This signifies a substantial 30% compound annual growth rate spanning from 2018 to 2024. Moreover, Ericsson foresees that by 2024, 5G networks would bear the load of approximately 35% of the overall mobile data traffic. In addition, the rise of cloud-native in the telecommunication industry and strategic partnerships between telecom operators and cloud service providers are creating new opportunities for market growth. However, a potential risk in data security stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Telecom Cloud Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022. The market in the region is poised for substantial growth, primarily fueled by the swift adoption of 5G technology. The strong presence of key players in both the telecom industry and cloud computing sector is anticipated to further drive market expansion throughout the forecast period. Moreover , the U.S. is projected to secure a significant share, attributed to the escalating demand for digital data, which is witnessing rapid growth and constant evolution. Asia Pacific is expected to grow significantly over the forecast period. The expanding mobile audience is set to drive market expansion in China and India. The rollout of 5G in India has opened significant opportunities, prompting telecommunication service and infrastructure providers to actively pursue cloud solutions. This strategic focus is poised to contribute to India’s digital transformation and economic strength, consequently bolstering the Asia Pacific market. In South Korea, collaborations within the telecommunication sector are underway, reflecting a proactive approach to tap into future opportunities and drive growth.

Major market player included in this report are:
VMware, Inc.
International Business Machine Corporation
Telefonaktiebolaget LM Ericsson
Cisco Systems, Inc.
Google LLC (Alphabet LLC)
Huawei Technologies Co., Ltd.
Amazon Web Services, Inc.
Microsoft Corporation
Oracle Corporation
Deutsche Telekom

Recent Developments in the Market:
Ø In February 2023, Snowflake Inc., a leading data cloud company, introduced the Telecom Data Cloud, a specialized offering designed to provide industry-specific data insights that empower clients to make informed decisions. This innovative solution is playing a pivotal role in the modernization of telecommunication networks, enhancing operational efficiency, and ultimately maximizing revenue for the clients.
Ø In June 2022, Huawei Technologies Co., Ltd. unveiled its latest initiatives for communication service operators, aiming to expedite service operations, amplify network value, and drive innovation in services. The company is dedicated to facilitating the expansion of telecom cloud services and harnessing the potential of network services for enhanced operational capabilities.

Global Telecom Cloud Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Component, Deployment Type, Service Model, Application, Enterprise Size, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:
By Deployment Type:
By Service Model:
Software as a Service (SaaS)
Platform as a Service (PaaS)
Infrastructure as a Service (IaaS)
By Application:
Data Storage, and Computing
Traffic Management
Cloud Migration
Enterprise Size:
Large Enterprises
By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Telecom Cloud Market, by Region, 2020-2030 (USD Billion)
1.2.2. Telecom Cloud Market, by Component, 2020-2030 (USD Billion)
1.2.3. Telecom Cloud Market, by Deployment Type, 2020-2030 (USD Billion)
1.2.4. Telecom Cloud Market, by Service Model, 2020-2030 (USD Billion)
1.2.5. Telecom Cloud Market, by Application, 2020-2030 (USD Billion)
1.2.6. Telecom Cloud Market, by Enterprise Size, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Telecom Cloud Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Telecom Cloud Market Dynamics
3.1. Telecom Cloud Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Rising Network Virtualization and SDN Adoption Rollout of 5G networks Proliferation of connected devices and mobile data traffic
3.1.2. Market Challenges Potential risk in data security
3.1.3. Market Opportunities Rise of cloud-native in the telecommunication industry Strategic partnerships between telecom operators and cloud service providers
Chapter 4. Global Telecom Cloud Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Telecom Cloud Market, by Component
5.1. Market Snapshot
5.2. Global Telecom Cloud Market by Component, Performance – Potential Analysis
5.3. Global Telecom Cloud Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
5.4. Telecom Cloud Market, Sub Segment Analysis
5.4.1. Solution
5.4.2. Services
Chapter 6. Global Telecom Cloud Market, by Deployment Type
6.1. Market Snapshot
6.2. Global Telecom Cloud Market by Deployment Type, Performance – Potential Analysis
6.3. Global Telecom Cloud Market Estimates & Forecasts by Deployment Type 2020-2030 (USD Billion)
6.4. Telecom Cloud Market, Sub Segment Analysis
6.4.1. Private
6.4.2. Public
6.4.3. Hybrid
Chapter 7. Global Telecom Cloud Market, by Service Model
7.1. Market Snapshot
7.2. Global Telecom Cloud Market by Service Model, Performance – Potential Analysis
7.3. Global Telecom Cloud Market Estimates & Forecasts by Service Model 2020-2030 (USD Billion)
7.4. Telecom Cloud Market, Sub Segment Analysis
7.4.1. Software as a Service (SaaS)
7.4.2. Platform as a Service (PaaS)
7.4.3. Infrastructure as a Service (IaaS)
Chapter 8. Global Telecom Cloud Market, by Application
8.1. Market Snapshot
8.2. Global Telecom Cloud Market by Application, Performance – Potential Analysis
8.3. Global Telecom Cloud Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
8.4. Telecom Cloud Market, Sub Segment Analysis
8.4.1. Network, Data Storage, and Computing
8.4.2. Traffic Management
8.4.3. Cloud Migration
8.4.4. Others
Chapter 9. Global Telecom Cloud Market, by Enterprise Size
9.1. Market Snapshot
9.2. Global Telecom Cloud Market by Enterprise Size, Performance – Potential Analysis
9.3. Global Telecom Cloud Market Estimates & Forecasts by Enterprise Size 2020-2030 (USD Billion)
9.4. Telecom Cloud Market, Sub Segment Analysis
9.4.1. Large Enterprises
9.4.2. SMEs
Chapter 10. Global Telecom Cloud Market, Regional Analysis
10.1. Top Leading Countries
10.2. Top Emerging Countries
10.3. Telecom Cloud Market, Regional Market Snapshot
10.4. North America Telecom Cloud Market
10.4.1. U.S. Telecom Cloud Market Component breakdown estimates & forecasts, 2020-2030 Deployment Type breakdown estimates & forecasts, 2020-2030 Service Model breakdown estimates & forecasts, 2020-2030 Application breakdown estimates & forecasts, 2020-2030 Enterprise Size breakdown estimates & forecasts, 2020-2030
10.4.2. Canada Telecom Cloud Market
10.5. Europe Telecom Cloud Market Snapshot
10.5.1. U.K. Telecom Cloud Market
10.5.2. Germany Telecom Cloud Market
10.5.3. France Telecom Cloud Market
10.5.4. Spain Telecom Cloud Market
10.5.5. Italy Telecom Cloud Market
10.5.6. Rest of Europe Telecom Cloud Market
10.6. Asia-Pacific Telecom Cloud Market Snapshot
10.6.1. China Telecom Cloud Market
10.6.2. India Telecom Cloud Market
10.6.3. Japan Telecom Cloud Market
10.6.4. Australia Telecom Cloud Market
10.6.5. South Korea Telecom Cloud Market
10.6.6. Rest of Asia Pacific Telecom Cloud Market
10.7. Latin America Telecom Cloud Market Snapshot
10.7.1. Brazil Telecom Cloud Market
10.7.2. Mexico Telecom Cloud Market
10.8. Middle East & Africa Telecom Cloud Market
10.8.1. Saudi Arabia Telecom Cloud Market
10.8.2. South Africa Telecom Cloud Market
10.8.3. Rest of Middle East & Africa Telecom Cloud Market

Chapter 11. Competitive Intelligence
11.1. Key Company SWOT Analysis
11.1.1. Company 1
11.1.2. Company 2
11.1.3. Company 3
11.2. Top Market Strategies
11.3. Company Profiles
11.3.1. VMware, Inc. Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
11.3.2. International Business Machine Corporation
11.3.3. Telefonaktiebolaget LM Ericsson
11.3.4. Cisco Systems, Inc.
11.3.5. Google LLC (Alphabet LLC)
11.3.6. Huawei Technologies Co., Ltd.
11.3.7. Amazon Web Services, Inc.
11.3.8. Microsoft Corporation
11.3.9. Oracle Corporation
11.3.10. Deutsche Telekom
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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