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Global Data Marketplace Platform Market to reach USD XX billion by the end of 2029

Global Data Marketplace Platform Market Size study & Forecast, by Component (Platform, Services), by Enterprise Size (Large Enterprises, SMEs), by Type (Personal Data Marketplace Platforms, B2B Data Marketplace Platforms, IoT Data Marketplace Platforms), by End-user (Financial Services, Advertising, Media & Entertainment, Retail & CPG, Healthcare & Life Sciences, Other) and Regional Analysis, 2022-2029

Product Code: ENGE-18220512
Publish Date: 8-10-2022
Page: 200

Global Data Marketplace Platform Market is valued at approximately USD XX billion in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2029. A data marketplace platform is a transactional platform that allows users to buy and sell data, which offers a unique user experience. This platform is a cloud-based service where individuals or businesses can upload data to the cloud. This platform includes the exchange of different types of data, such as demographic, firmographics, business intelligence, and personal data. The Data Marketplace Platform Market is expanding because of factors such as surging demand for the Internet of Things (IoT) connected devices, rising developments in machine-to-machine (M2M) in communications networks, and growing adoption of data marketplace platform across various end-use verticals including retail & consumer goods, and media & entertainment, BFSI, etc.
According to Statista, the number of Internet of Things (IoT) connected devices is expected to reach 29.4 billion devices in 2030 from 8.6 billion devices in the year 2019. Thereby, the rising proliferation of the Internet of Things (IoT) connected devices is exhibiting a positive influence on the market growth worldwide. The rising emphasis on the usage of cloud services, as well as an increasing number of strategic initiatives by the key market players, is creating productive opportunities for market growth in the forthcoming years. However, high initial capital is required and a dearth of skilled professionals stifles market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Data Marketplace Platform Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the space in terms of revenue, owing to the increasing deployment of cutting-edge technologies like artificial intelligence (AI), augmented reality (AR)/ virtual reality (VR) orchestration capabilities, along with the presence of advanced data infrastructure. Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as growing development of IoT technologies, coupled with the increasing penetration of data marketplace platform services in several applications.

Major market players included in this report are:
Acxiom LLC
AWS
Dawex
Quandl
BattleFin
Datatrade
Oracle
Microsoft
Adobe
SAP SE

Recent Developments in the Market:
 In 2020, Aiisma- a data marketplace announced the launch of Aiisma App with Aiihealth feature, which includes health mapping and marketplaces’ location sharing features. This allows users to consensually and anonymously share their behavioral data in exchange for rewards, which is helpful in creating a digital fence against the pandemic.
 in March 2022, Nokia unveils the company’s collaboration with Equideum Health to use Nokia Data Marketplace (NDM) blockchain solutions to facilitate a multi-party ecosystem. This solution enables varied person-centric use cases by connecting innovative technologies in data management, data exchange, and data marketplace.
Global Data Marketplace Platform Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Component, Enterprise Size, Type, End-user, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
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:
Platform
Services
By Enterprise Size:
Large Enterprises
SMEs
By Type:
Personal Data Marketplace Platforms
B2B Data Marketplace Platforms
IoT Data Marketplace Platforms
By End-user:
Financial Services
Advertising, Media & Entertainment
Retail & CPG
Healthcare & Life Sciences
Other
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

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. Data Marketplace Platform Market, by Region, 2019-2029 (USD Billion)
1.2.2. Data Marketplace Platform Market, by Component, 2019-2029 (USD Billion)
1.2.3. Data Marketplace Platform Market, by Enterprise Size, 2019-2029 (USD Billion)
1.2.4. Data Marketplace Platform Market, by Type, 2019-2029 (USD Billion)
1.2.5. Data Marketplace Platform Market, by End-user, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Data Marketplace Platform 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 Data Marketplace Platform Market Dynamics
3.1. Data Marketplace Platform Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Surging demand for the Internet of Things (IoT) connected devices
3.1.1.2. Rising developments for machine-to-machine (M2M) in communications networks
3.1.2. Market Challenges
3.1.2.1. High initial capital is required
3.1.2.2. Dearth of skilled professionals
3.1.3. Market Opportunities
3.1.3.1. Rising emphasis on the usage of cloud service
3.1.3.2. Increasing number of strategic initiatives by the key market players
Chapter 4. Global Data Marketplace Platform 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. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Investment Adoption Model
4.5. Analyst Recommendation & Conclusion
4.6. Top investment opportunity
4.7. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Data Marketplace Platform Market, by Component
6.1. Market Snapshot
6.2. Global Data Marketplace Platform Market by Component, Performance – Potential Analysis
6.3. Global Data Marketplace Platform Market Estimates & Forecasts by Component, 2019-2029 (USD Billion)
6.4. Data Marketplace Platform Market, Sub Segment Analysis
6.4.1. Platform
6.4.2. Services
Chapter 7. Global Data Marketplace Platform Market, by Enterprise Size
7.1. Market Snapshot
7.2. Global Data Marketplace Platform Market by Enterprise Size, Performance – Potential Analysis
7.3. Global Data Marketplace Platform Market Estimates & Forecasts by Enterprise Size, 2019-2029 (USD Billion)
7.4. Data Marketplace Platform Market, Sub Segment Analysis
7.4.1. Large Enterprises
7.4.2. SMEs
Chapter 8. Global Data Marketplace Platform Market, by Type
8.1. Market Snapshot
8.2. Global Data Marketplace Platform Market by Type, Performance – Potential Analysis
8.3. Global Data Marketplace Platform Market Estimates & Forecasts by Type, 2019-2029 (USD Billion)
8.4. Data Marketplace Platform Market, Sub Segment Analysis
8.4.1. Personal Data Marketplace Platforms
8.4.2. B2B Data Marketplace Platforms
8.4.3. IoT Data Marketplace Platforms
Chapter 9. Global Data Marketplace Platform Market, by End-user
9.1. Market Snapshot
9.2. Global Data Marketplace Platform Market by End-user, Performance – Potential Analysis
9.3. Global Data Marketplace Platform Market Estimates & Forecasts by End-user, 2019-2029 (USD Billion)
9.4. Data Marketplace Platform Market, Sub Segment Analysis
9.4.1. Financial Services
9.4.2. Advertising, Media & Entertainment
9.4.3. Retail & CPG
9.4.4. Healthcare & Life Sciences
9.4.5. Other
Chapter 10. Global Data Marketplace Platform Market, Regional Analysis
10.1. Data Marketplace Platform Market, Regional Market Snapshot
10.2. North America Data Marketplace Platform Market
10.2.1. U.S. Data Marketplace Platform Market
10.2.1.1. Component breakdown estimates & forecasts, 2019-2029
10.2.1.2. Enterprise Size breakdown estimates & forecasts, 2019-2029
10.2.1.3. Type breakdown estimates & forecasts, 2019-2029
10.2.1.4. End-user breakdown estimates & forecasts, 2019-2029
10.2.2. Canada Data Marketplace Platform Market
10.3. Europe Data Marketplace Platform Market Snapshot
10.3.1. U.K. Data Marketplace Platform Market
10.3.2. Germany Data Marketplace Platform Market
10.3.3. France Data Marketplace Platform Market
10.3.4. Spain Data Marketplace Platform Market
10.3.5. Italy Data Marketplace Platform Market
10.3.6. Rest of Europe Data Marketplace Platform Market
10.4. Asia-Pacific Data Marketplace Platform Market Snapshot
10.4.1. China Data Marketplace Platform Market
10.4.2. India Data Marketplace Platform Market
10.4.3. Japan Data Marketplace Platform Market
10.4.4. Australia Data Marketplace Platform Market
10.4.5. South Korea Data Marketplace Platform Market
10.4.6. Rest of Asia Pacific Data Marketplace Platform Market
10.5. Latin America Data Marketplace Platform Market Snapshot
10.5.1. Brazil Data Marketplace Platform Market
10.5.2. Mexico Data Marketplace Platform Market
10.6. Rest of The World Data Marketplace Platform Market

Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. Acxiom LLC
11.2.1.1. Key Information
11.2.1.2. Overview
11.2.1.3. Financial (Subject to Data Availability)
11.2.1.4. Product Summary
11.2.1.5. Recent Developments
11.2.2. AWS
11.2.3. Dawex
11.2.4. Quandl
11.2.5. BattleFin
11.2.6. Datatrade
11.2.7. Oracle
11.2.8. Microsoft
11.2.9. Adobe
11.2.10. SAP SE
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

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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:
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