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Global Composable Infrastructure Market to reach USD XXX billion by 2027.

Global Composable Infrastructure Market Size study, by Product Type (software, Hardware), by Vertical (BFSI, IT and telecom, Government, Healthcare, Manufacturing, others), and Regional Forecasts 2021-2027

Product Code: ICTBC-48752325
Publish Date: 26-08-2021
Page: 200

Global Composable Infrastructure Market is valued approximately at USD XXX billion in 2020 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2021-2027. In composable infrastructure, the storage and networking resources get abstracted from the physical locations which can be managed through the software via web-based interface. The global Composable Infrastructure market is being driven by high adoption of virtualization, growing need to bridge the gap between traditional and new IT infrastructure, and increasing investments in data center technologies. Furthermore, increase in adoption of composable infrastructure solutions and emergence of hybrid cloud will provide new opportunities for the global Composable Infrastructure industry. For instance, according to the report of International European Agency, the demand for data and digital services is anticipated to have an exponential growth in coming years, by the global internet traffic estimated to be double by year 2022 at 4.2 trillion gigabytes. The number of internet users through mobiles is expected to increase from 3.8 billion in year 2019 to 5 billion by year 2025, whereas the connections of Internet of Things (IoT) is projected to double from 12 billion in year 2019 to 25 billion by year 2025. As a result, increased internet penetration, growth in internet traffic and high adoption of IoT connections will serve as a catalyst for the Composable Infrastructure industry in the future. However, choice of hypervisor being vendor-dependent and single point of failure, may impede market growth over the forecast period of 2021-2027.

Asia Pacific, North America, Europe, Latin America, and Rest of the World are the key region considered for the regional analysis of global composable market. The presence of well-established players and growing demand for enterprise applications with the advent of new technologies in the region makes the North America leading region across the world in terms of market share. Whereas Asia Pacific is also anticipated to exhibit the highest growth rate over the forecast period 2021-2027 due to increasing population and increasing focus of enterprises on in-house data centers in China and India countries in the region..
Major market player included in this report are:

HGST
HPE
Dell EMC
Lenovo
Drivescale
Tidalscale
One stop systems
Liquid
Cloudistics
QCT

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 eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available 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 Product Type:
Software
Hardware
By Vertical:
BFSI
IT and telecom
Government
Healthcare
Manufacturing
Others

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019
Base year – 2020
Forecast period – 2021 to 2027.

Target Audience of the Global Composable Infrastructure Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2027 (USD Billion)
1.2.1. Composable Infrastructure Market , by Region, 2019-2027 (USD Billion)
1.2.2. Composable Infrastructure Market , by Product Type, 2019-2027 (USD Billion)
1.2.3. Composable Infrastructure Market , by Vertical , 2019-2027 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Composable Infrastructure Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Composable Infrastructure Market Dynamics
3.1. Composable Infrastructure Market Impact Analysis (2019-2027)
3.1.1. Market Drivers
3.1.1.1. High adoption of virtualization
3.1.1.2. Growing need to bridge the gap between traditional and new IT infrastructure
3.1.1.3. Increasing investments in data centre technologies
3.1.2. Market Restraint
3.1.2.1. Choice of hypervisor being vendor-dependent
3.1.2.2. Single point of failure
3.1.3. Market Opportunities
3.1.3.1. Increase in adoption of composable infrastructure solutions
3.1.3.2. Emergence of hybrid cloud
Chapter 4. Global Composable Infrastructure 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
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2027)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
Chapter 5. Global Composable Infrastructure Market , by Product Type
5.1. Market Snapshot
5.2. Global Composable Infrastructure Market by Product Type, Performance – Potential Analysis
5.3. Global Composable Infrastructure Market Estimates & Forecasts by Product Type 2018-2027 (USD Billion)
5.4. Composable Infrastructure Market , Sub Segment Analysis
5.4.1. Software
5.4.2. Hardware
Chapter 6. Global Composable Infrastructure Market , by Vertical
a. Market Snapshot
6.1. Global Composable Infrastructure Market by Vertical, Performance – Potential Analysis
6.2. Global Composable Infrastructure Market Estimates & Forecasts by Vertical 2018-2027 (USD Billion)
6.3. Composable Infrastructure Market , Sub Segment Analysis
6.3.1. BFSI
6.3.2. IT and telecom
6.3.3. Government
6.3.4. Healthcare
6.3.5. Manufacturing
6.3.6. Others
Chapter 7. Global Composable Infrastructure Market , Regional Analysis
7.1. Composable Infrastructure Market , Regional Market Snapshot
7.2. North America Composable Infrastructure Market
7.2.1. U.S. Composable Infrastructure Market
7.2.1.1. Product Type breakdown estimates & forecasts, 2018-2027
7.2.1.2. Vertical breakdown estimates & forecasts, 2018-2027
7.2.2. Canada Composable Infrastructure Market
7.3. Europe Composable Infrastructure Market Snapshot
7.3.1. U.K. Composable Infrastructure Market
7.3.2. Germany Composable Infrastructure Market
7.3.3. France Composable Infrastructure Market
7.3.4. Spain Composable Infrastructure Market
7.3.5. Italy Composable Infrastructure Market
7.3.6. Rest of Europe Composable Infrastructure Market
7.4. Asia-Pacific Composable Infrastructure Market Snapshot
7.4.1. China Composable Infrastructure Market
7.4.2. India Composable Infrastructure Market
7.4.3. Japan Composable Infrastructure Market
7.4.4. Australia Composable Infrastructure Market
7.4.5. South Korea Composable Infrastructure Market
7.4.6. Rest of Asia Pacific Composable Infrastructure Market
7.5. Latin America Composable Infrastructure Market Snapshot
7.5.1. Brazil Composable Infrastructure Market
7.5.2. Mexico Composable Infrastructure Market
7.6. Rest of The World Composable Infrastructure Market
Chapter 8. Competitive Intelligence
8.1. Top Market Strategies
8.2. Company Profiles
8.2.1. HGST
8.2.1.1. Key Information
8.2.1.2. Overview
8.2.1.3. Financial (Subject to Data Availability)
8.2.1.4. Product Summary
8.2.1.5. Recent Developments
8.2.2. HPE
8.2.3. Dell EMC
8.2.4. Lenovo
8.2.5. Drivescale
8.2.6. Tidalscale
8.2.7. One stop systems
8.2.8. Liquid
8.2.9. Cloudistics
8.2.10. QCT

Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes
9.3. Research Assumption

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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:
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