Converged Data Platform Market Size and Share: 2031 Key Findings
The Converged Data Platform Market is expected to register a CAGR of 14.3% from 2023 to 2031, with a market size expanding from US$ XX million in 2023 to US$ XX Million by 2031.
The report is segmented By Type (VMware, KVM, Hyper-V), Application (Virtual Desktop Infrastructure, Server Virtualization, Data Protection), Industry (Healthcare, Government, Education, IT & Telecom, Others). The global analysis is further broken-down at regional level and major countries. The report offers the value in USD for the above analysis and segments
Purpose of the ReportThe report Converged Data Platform Market by The Insight Partners aims to describe the present landscape and future growth, top driving factors, challenges, and opportunities. This will provide insights to various business stakeholders, such as:
- Technology Providers/Manufacturers: To understand the evolving market dynamics and know the potential growth opportunities, enabling them to make informed strategic decisions.
- Investors: To conduct a comprehensive trend analysis regarding the market growth rate, market financial projections, and opportunities that exist across the value chain.
- Regulatory bodies: To regulate policies and police activities in the market with the aim of minimizing abuse, preserving investor trust and confidence, and upholding the integrity and stability of the market.
Converged Data Platform Market Segmentation
Type- VMware
- KVM
- Hyper-V
- Virtual Desktop Infrastructure
- Server Virtualization
- Data Protection
- Healthcare
- Government
- Education
- IT & Telecom
- Others
- North America
- Europe
- Asia-Pacific
- South and Central America
- Middle East and Africa
- North America
- Europe
- Asia-Pacific
- South and Central America
- Middle East and Africa
Strategic Insights
Converged Data Platform Market Growth Drivers- Growing Need for Unified Data Management: One of the primary drivers for the converged data platform market is the growing need for unified data management across organizations. Businesses today generate data from various sources, including IoT devices, social media, and traditional databases. Traditional data management approaches often lead to data silos, hindering efficient data access and analysis. Converged data platforms provide a holistic solution by integrating multiple data sources into a single framework, enabling organizations to manage, analyze, and derive insights from their data seamlessly and efficiently.
- Increasing Importance of Real-Time Decision-Making: In today's fast-paced business environment, the ability to make real-time decisions is crucial for success. This necessity drives the demand for converged data platforms that can process and analyze data in real time. Organizations need to respond quickly to market changes, customer preferences, and operational challenges. Converged data platforms streamline data workflows and enable real-time analytics, allowing organizations to act on insights swiftly and improve overall agility in their operations.
- Growing Focus on Data Governance and Compliance: With the increasing volume of data generated and the rise of stringent data regulations, there is a growing trend towards enhancing data governance and compliance within converged data platforms. Organizations are prioritizing solutions that ensure data quality, security, and compliance with regulations like GDPR and CCPA. Converged data platforms that offer built-in governance features, such as data lineage tracking and access controls, are becoming essential for organizations to manage their data responsibly and minimize risks associated with data breaches and non-compliance.
- Growing Emphasis of Companies on Implementig Cloud-Based Solutions: A notable trend in the converged data platform market is the increasing adoption of cloud-based solutions. Organizations are moving away from on-premises systems to cloud environments due to their scalability, flexibility, and cost-effectiveness. Cloud-based converged data platforms allow businesses to store and manage vast amounts of data without the burden of maintaining physical infrastructure. This trend enables organizations to easily scale their data management capabilities as their data needs grow, leading to enhanced operational efficiency and reduced IT overhead.
- Growing Development of Industry-Specific Solutions: The converged data platform market presents opportunities for the development of industry-specific solutions tailored to the unique needs of various sectors. Different industries, such as healthcare, finance, and retail, have distinct data management challenges and regulatory requirements. By creating customized solutions that address these specific needs, providers can differentiate themselves in the market and deliver enhanced value to their clients, fostering long-term partnerships and customer loyalty.
- Rising Opportunites in Developing Nations: There is a significant opportunity for converged data platform providers to expand their offerings into emerging markets. As businesses in these regions increasingly recognize the importance of data-driven decision-making, the demand for effective data management solutions is on the rise. By tailoring their products and services to meet the unique needs of these markets, such as affordability and scalability, providers can tap into a growing customer base and drive revenue growth.
Market Report Scope
Key Selling Points
- Comprehensive Coverage: The report comprehensively covers the analysis of products, services, types, and end users of the Converged Data Platform Market, providing a holistic landscape.
- Expert Analysis: The report is compiled based on the in-depth understanding of industry experts and analysts.
- Up-to-date Information: The report assures business relevance due to its coverage of recent information and data trends.
- Customization Options: This report can be customized to cater to specific client requirements and suit the business strategies aptly.
The research report on the Converged Data Platform Market can, therefore, help spearhead the trail of decoding and understanding the industry scenario and growth prospects. Although there can be a few valid concerns, the overall benefits of this report tend to outweigh the disadvantages.
REGIONAL FRAMEWORK
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Report Coverage
Revenue forecast, Company Analysis, Industry landscape, Growth factors, and Trends
Segment Covered
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Regional Scope
North America, Europe, Asia Pacific, Middle East & Africa, South & Central America
Country Scope
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Frequently Asked Questions
The report can be delivered in PDF/PPT format; we can also share excel dataset based on the request
Edge computing and distributed data processing to play a significant role in the global converged data platform market in the coming years
The Converged Data Platform Market is estimated to witness a CAGR of 14.3% from 2023 to 2031
Exponential data growth and complexity and digital transformation and advanced analytics requirements are the major factors driving the converged data platform market
1. INTRODUCTION
1.1. SCOPE OF THE STUDY
1.2. THE INSIGHT PARTNERS RESEARCH REPORT GUIDANCE
1.3. MARKET SEGMENTATION
1.3.1 Converged Data Platform - By Hypervisor type
1.3.2 Converged Data Platform - By Component
1.3.3 Converged Data Platform - By Industry
1.3.4 Converged Data Platform - By Region
1.3.4.1 By Country
2. KEY TAKEAWAYS
3. RESEARCH METHODOLOGY
4. CONVERGED DATA PLATFORM LANDSCAPE
4.1. OVERVIEW
4.2. PEST ANALYSIS
4.2.1 North America - Pest Analysis
4.2.2 Europe - Pest Analysis
4.2.3 Asia-Pacific - Pest Analysis
4.2.4 Middle East and Africa - Pest Analysis
4.2.5 South and Central America - Pest Analysis
4.3. ECOSYSTEM ANALYSIS
4.4. EXPERT OPINIONS
5. CONVERGED DATA PLATFORM - KEY MARKET DYNAMICS
5.1. KEY MARKET DRIVERS
5.2. KEY MARKET RESTRAINTS
5.3. KEY MARKET OPPORTUNITIES
5.4. FUTURE TRENDS
5.5. IMPACT ANALYSIS OF DRIVERS AND RESTRAINTS
6. CONVERGED DATA PLATFORM - GLOBAL MARKET ANALYSIS
6.1. CONVERGED DATA PLATFORM - GLOBAL MARKET OVERVIEW
6.2. CONVERGED DATA PLATFORM - GLOBAL MARKET AND FORECAST TO 2028
6.3. MARKET POSITIONING
7. CONVERGED DATA PLATFORM - REVENUE AND FORECASTS TO 2028 - HYPERVISOR TYPE
7.1. OVERVIEW
7.2. HYPERVISOR TYPE MARKET FORECASTS AND ANALYSIS
7.3. VMWARE
7.3.1. Overview
7.3.2. VMware Market Forecast and Analysis
7.4. KVM
7.4.1. Overview
7.4.2. KVM Market Forecast and Analysis
7.5. HYPER-V
7.5.1. Overview
7.5.2. Hyper-V Market Forecast and Analysis
8. CONVERGED DATA PLATFORM - REVENUE AND FORECASTS TO 2028 - COMPONENT
8.1. OVERVIEW
8.2. COMPONENT MARKET FORECASTS AND ANALYSIS
8.3. SOFTWARE
8.3.1. Overview
8.3.2. Software Market Forecast and Analysis
8.4. SERVICES
8.4.1. Overview
8.4.2. Services Market Forecast and Analysis
9. CONVERGED DATA PLATFORM - REVENUE AND FORECASTS TO 2028 - INDUSTRY
9.1. OVERVIEW
9.2. INDUSTRY MARKET FORECASTS AND ANALYSIS
9.3. BFSI
9.3.1. Overview
9.3.2. BFSI Market Forecast and Analysis
9.4. HEALTHCARE
9.4.1. Overview
9.4.2. Healthcare Market Forecast and Analysis
9.5. GOVERNMENT
9.5.1. Overview
9.5.2. Government Market Forecast and Analysis
9.6. EDUCATION
9.6.1. Overview
9.6.2. Education Market Forecast and Analysis
9.7. IT AND TELECOM
9.7.1. Overview
9.7.2. IT and telecom Market Forecast and Analysis
10. CONVERGED DATA PLATFORM REVENUE AND FORECASTS TO 2028 - GEOGRAPHICAL ANALYSIS
10.1. NORTH AMERICA
10.1.1 North America Converged Data Platform Overview
10.1.2 North America Converged Data Platform Forecasts and Analysis
10.1.3 North America Converged Data Platform Forecasts and Analysis - By Hypervisor type
10.1.4 North America Converged Data Platform Forecasts and Analysis - By Component
10.1.5 North America Converged Data Platform Forecasts and Analysis - By Industry
10.1.6 North America Converged Data Platform Forecasts and Analysis - By Countries
10.1.6.1 United States Converged Data Platform
10.1.6.1.1 United States Converged Data Platform by Hypervisor type
10.1.6.1.2 United States Converged Data Platform by Component
10.1.6.1.3 United States Converged Data Platform by Industry
10.1.6.2 Canada Converged Data Platform
10.1.6.2.1 Canada Converged Data Platform by Hypervisor type
10.1.6.2.2 Canada Converged Data Platform by Component
10.1.6.2.3 Canada Converged Data Platform by Industry
10.1.6.3 Mexico Converged Data Platform
10.1.6.3.1 Mexico Converged Data Platform by Hypervisor type
10.1.6.3.2 Mexico Converged Data Platform by Component
10.1.6.3.3 Mexico Converged Data Platform by Industry
10.2. EUROPE
10.2.1 Europe Converged Data Platform Overview
10.2.2 Europe Converged Data Platform Forecasts and Analysis
10.2.3 Europe Converged Data Platform Forecasts and Analysis - By Hypervisor type
10.2.4 Europe Converged Data Platform Forecasts and Analysis - By Component
10.2.5 Europe Converged Data Platform Forecasts and Analysis - By Industry
10.2.6 Europe Converged Data Platform Forecasts and Analysis - By Countries
10.2.6.1 Germany Converged Data Platform
10.2.6.1.1 Germany Converged Data Platform by Hypervisor type
10.2.6.1.2 Germany Converged Data Platform by Component
10.2.6.1.3 Germany Converged Data Platform by Industry
10.2.6.2 France Converged Data Platform
10.2.6.2.1 France Converged Data Platform by Hypervisor type
10.2.6.2.2 France Converged Data Platform by Component
10.2.6.2.3 France Converged Data Platform by Industry
10.2.6.3 Italy Converged Data Platform
10.2.6.3.1 Italy Converged Data Platform by Hypervisor type
10.2.6.3.2 Italy Converged Data Platform by Component
10.2.6.3.3 Italy Converged Data Platform by Industry
10.2.6.4 United Kingdom Converged Data Platform
10.2.6.4.1 United Kingdom Converged Data Platform by Hypervisor type
10.2.6.4.2 United Kingdom Converged Data Platform by Component
10.2.6.4.3 United Kingdom Converged Data Platform by Industry
10.2.6.5 Russia Converged Data Platform
10.2.6.5.1 Russia Converged Data Platform by Hypervisor type
10.2.6.5.2 Russia Converged Data Platform by Component
10.2.6.5.3 Russia Converged Data Platform by Industry
10.2.6.6 Rest of Europe Converged Data Platform
10.2.6.6.1 Rest of Europe Converged Data Platform by Hypervisor type
10.2.6.6.2 Rest of Europe Converged Data Platform by Component
10.2.6.6.3 Rest of Europe Converged Data Platform by Industry
10.3. ASIA-PACIFIC
10.3.1 Asia-Pacific Converged Data Platform Overview
10.3.2 Asia-Pacific Converged Data Platform Forecasts and Analysis
10.3.3 Asia-Pacific Converged Data Platform Forecasts and Analysis - By Hypervisor type
10.3.4 Asia-Pacific Converged Data Platform Forecasts and Analysis - By Component
10.3.5 Asia-Pacific Converged Data Platform Forecasts and Analysis - By Industry
10.3.6 Asia-Pacific Converged Data Platform Forecasts and Analysis - By Countries
10.3.6.1 Australia Converged Data Platform
10.3.6.1.1 Australia Converged Data Platform by Hypervisor type
10.3.6.1.2 Australia Converged Data Platform by Component
10.3.6.1.3 Australia Converged Data Platform by Industry
10.3.6.2 China Converged Data Platform
10.3.6.2.1 China Converged Data Platform by Hypervisor type
10.3.6.2.2 China Converged Data Platform by Component
10.3.6.2.3 China Converged Data Platform by Industry
10.3.6.3 India Converged Data Platform
10.3.6.3.1 India Converged Data Platform by Hypervisor type
10.3.6.3.2 India Converged Data Platform by Component
10.3.6.3.3 India Converged Data Platform by Industry
10.3.6.4 Japan Converged Data Platform
10.3.6.4.1 Japan Converged Data Platform by Hypervisor type
10.3.6.4.2 Japan Converged Data Platform by Component
10.3.6.4.3 Japan Converged Data Platform by Industry
10.3.6.5 South Korea Converged Data Platform
10.3.6.5.1 South Korea Converged Data Platform by Hypervisor type
10.3.6.5.2 South Korea Converged Data Platform by Component
10.3.6.5.3 South Korea Converged Data Platform by Industry
10.3.6.6 Rest of Asia-Pacific Converged Data Platform
10.3.6.6.1 Rest of Asia-Pacific Converged Data Platform by Hypervisor type
10.3.6.6.2 Rest of Asia-Pacific Converged Data Platform by Component
10.3.6.6.3 Rest of Asia-Pacific Converged Data Platform by Industry
10.4. MIDDLE EAST AND AFRICA
10.4.1 Middle East and Africa Converged Data Platform Overview
10.4.2 Middle East and Africa Converged Data Platform Forecasts and Analysis
10.4.3 Middle East and Africa Converged Data Platform Forecasts and Analysis - By Hypervisor type
10.4.4 Middle East and Africa Converged Data Platform Forecasts and Analysis - By Component
10.4.5 Middle East and Africa Converged Data Platform Forecasts and Analysis - By Industry
10.4.6 Middle East and Africa Converged Data Platform Forecasts and Analysis - By Countries
10.4.6.1 South Africa Converged Data Platform
10.4.6.1.1 South Africa Converged Data Platform by Hypervisor type
10.4.6.1.2 South Africa Converged Data Platform by Component
10.4.6.1.3 South Africa Converged Data Platform by Industry
10.4.6.2 Saudi Arabia Converged Data Platform
10.4.6.2.1 Saudi Arabia Converged Data Platform by Hypervisor type
10.4.6.2.2 Saudi Arabia Converged Data Platform by Component
10.4.6.2.3 Saudi Arabia Converged Data Platform by Industry
10.4.6.3 U.A.E Converged Data Platform
10.4.6.3.1 U.A.E Converged Data Platform by Hypervisor type
10.4.6.3.2 U.A.E Converged Data Platform by Component
10.4.6.3.3 U.A.E Converged Data Platform by Industry
10.4.6.4 Rest of Middle East and Africa Converged Data Platform
10.4.6.4.1 Rest of Middle East and Africa Converged Data Platform by Hypervisor type
10.4.6.4.2 Rest of Middle East and Africa Converged Data Platform by Component
10.4.6.4.3 Rest of Middle East and Africa Converged Data Platform by Industry
10.5. SOUTH AND CENTRAL AMERICA
10.5.1 South and Central America Converged Data Platform Overview
10.5.2 South and Central America Converged Data Platform Forecasts and Analysis
10.5.3 South and Central America Converged Data Platform Forecasts and Analysis - By Hypervisor type
10.5.4 South and Central America Converged Data Platform Forecasts and Analysis - By Component
10.5.5 South and Central America Converged Data Platform Forecasts and Analysis - By Industry
10.5.6 South and Central America Converged Data Platform Forecasts and Analysis - By Countries
10.5.6.1 Brazil Converged Data Platform
10.5.6.1.1 Brazil Converged Data Platform by Hypervisor type
10.5.6.1.2 Brazil Converged Data Platform by Component
10.5.6.1.3 Brazil Converged Data Platform by Industry
10.5.6.2 Argentina Converged Data Platform
10.5.6.2.1 Argentina Converged Data Platform by Hypervisor type
10.5.6.2.2 Argentina Converged Data Platform by Component
10.5.6.2.3 Argentina Converged Data Platform by Industry
10.5.6.3 Rest of South and Central America Converged Data Platform
10.5.6.3.1 Rest of South and Central America Converged Data Platform by Hypervisor type
10.5.6.3.2 Rest of South and Central America Converged Data Platform by Component
10.5.6.3.3 Rest of South and Central America Converged Data Platform by Industry
11. INDUSTRY LANDSCAPE
11.1. MERGERS AND ACQUISITIONS
11.2. AGREEMENTS, COLLABORATIONS AND JOIN VENTURES
11.3. NEW PRODUCT LAUNCHES
11.4. EXPANSIONS AND OTHER STRATEGIC DEVELOPMENTS
12. CONVERGED DATA PLATFORM, KEY COMPANY PROFILES
12.1. VMWARE INC
12.1.1. Key Facts
12.1.2. Business Description
12.1.3. Products and Services
12.1.4. Financial Overview
12.1.5. SWOT Analysis
12.1.6. Key Developments
12.2. SIMPLIVITY CORPORATION
12.2.1. Key Facts
12.2.2. Business Description
12.2.3. Products and Services
12.2.4. Financial Overview
12.2.5. SWOT Analysis
12.2.6. Key Developments
12.3. SCALE COMPUTING
12.3.1. Key Facts
12.3.2. Business Description
12.3.3. Products and Services
12.3.4. Financial Overview
12.3.5. SWOT Analysis
12.3.6. Key Developments
12.4. NUTANIX INC
12.4.1. Key Facts
12.4.2. Business Description
12.4.3. Products and Services
12.4.4. Financial Overview
12.4.5. SWOT Analysis
12.4.6. Key Developments
12.5. PIVOT3
12.5.1. Key Facts
12.5.2. Business Description
12.5.3. Products and Services
12.5.4. Financial Overview
12.5.5. SWOT Analysis
12.5.6. Key Developments
12.6. NIMBOXX INC.
12.6.1. Key Facts
12.6.2. Business Description
12.6.3. Products and Services
12.6.4. Financial Overview
12.6.5. SWOT Analysis
12.6.6. Key Developments
12.7. CISCO SYSTEMS, INC.
12.7.1. Key Facts
12.7.2. Business Description
12.7.3. Products and Services
12.7.4. Financial Overview
12.7.5. SWOT Analysis
12.7.6. Key Developments
12.8. MAXTA INC
12.8.1. Key Facts
12.8.2. Business Description
12.8.3. Products and Services
12.8.4. Financial Overview
12.8.5. SWOT Analysis
12.8.6. Key Developments
12.9. GRIDSTORE, INC
12.9.1. Key Facts
12.9.2. Business Description
12.9.3. Products and Services
12.9.4. Financial Overview
12.9.5. SWOT Analysis
12.9.6. Key Developments
12.10. IBM
12.10.1. Key Facts
12.10.2. Business Description
12.10.3. Products and Services
12.10.4. Financial Overview
12.10.5. SWOT Analysis
12.10.6. Key Developments
12.11. HEWLETT PACKARD ENTERPRISE COMPANY
12.11.1. Key Facts
12.11.2. Business Description
12.11.3. Products and Services
12.11.4. Financial Overview
12.11.5. SWOT Analysis
12.11.6. Key Developments
13. APPENDIX
13.1. ABOUT THE INSIGHT PARTNERS
13.2. GLOSSARY OF TERMS
1.Vmware Inc
2.Simplivity Corporation
3.Scale Computing
4.Nutanix Inc
5.Pivot3
6.Nimboxx Inc.
7.Cisco Systems, Inc.
8.Maxta Inc
9.Gridstore, Inc
10.IBM
11.Hewlett Packard Enterprise Company
The Insight Partners performs research in 4 major stages: Data Collection & Secondary Research, Primary Research, Data Analysis and Data Triangulation & Final Review.
- Data Collection and Secondary Research:
As a market research and consulting firm operating from a decade, we have published many reports and advised several clients across the globe. First step for any study will start with an assessment of currently available data and insights from existing reports. Further, historical and current market information is collected from Investor Presentations, Annual Reports, SEC Filings, etc., and other information related to company’s performance and market positioning are gathered from Paid Databases (Factiva, Hoovers, and Reuters) and various other publications available in public domain.
Several associations trade associates, technical forums, institutes, societies and organizations are accessed to gain technical as well as market related insights through their publications such as research papers, blogs and press releases related to the studies are referred to get cues about the market. Further, white papers, journals, magazines, and other news articles published in the last 3 years are scrutinized and analyzed to understand the current market trends.
- Primary Research:
The primarily interview analysis comprise of data obtained from industry participants interview and answers to survey questions gathered by in-house primary team.
For primary research, interviews are conducted with industry experts/CEOs/Marketing Managers/Sales Managers/VPs/Subject Matter Experts from both demand and supply side to get a 360-degree view of the market. The primary team conducts several interviews based on the complexity of the markets to understand the various market trends and dynamics which makes research more credible and precise.
A typical research interview fulfils the following functions:
- Provides first-hand information on the market size, market trends, growth trends, competitive landscape, and outlook
- Validates and strengthens in-house secondary research findings
- Develops the analysis team’s expertise and market understanding
Primary research involves email interactions and telephone interviews for each market, category, segment, and sub-segment across geographies. The participants who typically take part in such a process include, but are not limited to:
- Industry participants: VPs, business development managers, market intelligence managers and national sales managers
- Outside experts: Valuation experts, research analysts and key opinion leaders specializing in the electronics and semiconductor industry.
Below is the breakup of our primary respondents by company, designation, and region:
Once we receive the confirmation from primary research sources or primary respondents, we finalize the base year market estimation and forecast the data as per the macroeconomic and microeconomic factors assessed during data collection.
- Data Analysis:
Once data is validated through both secondary as well as primary respondents, we finalize the market estimations by hypothesis formulation and factor analysis at regional and country level.
- 3.1 Macro-Economic Factor Analysis:
We analyse macroeconomic indicators such the gross domestic product (GDP), increase in the demand for goods and services across industries, technological advancement, regional economic growth, governmental policies, the influence of COVID-19, PEST analysis, and other aspects. This analysis aids in setting benchmarks for various nations/regions and approximating market splits. Additionally, the general trend of the aforementioned components aid in determining the market's development possibilities.
- 3.2 Country Level Data:
Various factors that are especially aligned to the country are taken into account to determine the market size for a certain area and country, including the presence of vendors, such as headquarters and offices, the country's GDP, demand patterns, and industry growth. To comprehend the market dynamics for the nation, a number of growth variables, inhibitors, application areas, and current market trends are researched. The aforementioned elements aid in determining the country's overall market's growth potential.
- 3.3 Company Profile:
The “Table of Contents” is formulated by listing and analyzing more than 25 - 30 companies operating in the market ecosystem across geographies. However, we profile only 10 companies as a standard practice in our syndicate reports. These 10 companies comprise leading, emerging, and regional players. Nonetheless, our analysis is not restricted to the 10 listed companies, we also analyze other companies present in the market to develop a holistic view and understand the prevailing trends. The “Company Profiles” section in the report covers key facts, business description, products & services, financial information, SWOT analysis, and key developments. The financial information presented is extracted from the annual reports and official documents of the publicly listed companies. Upon collecting the information for the sections of respective companies, we verify them via various primary sources and then compile the data in respective company profiles. The company level information helps us in deriving the base number as well as in forecasting the market size.
- 3.4 Developing Base Number:
Aggregation of sales statistics (2020-2022) and macro-economic factor, and other secondary and primary research insights are utilized to arrive at base number and related market shares for 2022. The data gaps are identified in this step and relevant market data is analyzed, collected from paid primary interviews or databases. On finalizing the base year market size, forecasts are developed on the basis of macro-economic, industry and market growth factors and company level analysis.
- Data Triangulation and Final Review:
The market findings and base year market size calculations are validated from supply as well as demand side. Demand side validations are based on macro-economic factor analysis and benchmarks for respective regions and countries. In case of supply side validations, revenues of major companies are estimated (in case not available) based on industry benchmark, approximate number of employees, product portfolio, and primary interviews revenues are gathered. Further revenue from target product/service segment is assessed to avoid overshooting of market statistics. In case of heavy deviations between supply and demand side values, all thes steps are repeated to achieve synchronization.
We follow an iterative model, wherein we share our research findings with Subject Matter Experts (SME’s) and Key Opinion Leaders (KOLs) until consensus view of the market is not formulated – this model negates any drastic deviation in the opinions of experts. Only validated and universally acceptable research findings are quoted in our reports.
We have important check points that we use to validate our research findings – which we call – data triangulation, where we validate the information, we generate from secondary sources with primary interviews and then we re-validate with our internal data bases and Subject matter experts. This comprehensive model enables us to deliver high quality, reliable data in shortest possible time.
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