Big Data in Healthcare Market Size is valued at 33.36 Billion in 2024 and is predicted to reach 155.59 Billion by the year 2034 at a 16.8% CAGR during the forecast period for 2025-2034.
Big data healthcare analytics has arisen as a foremost learning technique to deal with the large volume of data in the healthcare sector. The healthcare industry has a bunch of data, and it could benefit from interactive dynamic big data platforms with cutting-edge technologies and tools to improve patient care and services. The ability to conduct comparative effectiveness research to find more clinically appropriate and cost-effective ways to diagnose and treat patients has been characterized as one of the benefits of analytics in healthcare. Big data techniques can improve the quality of healthcare data analysis, and it is beneficial for patients and healthcare organizations.
Major driving factors of the big data in healthcare market are the advancements in healthcare technologies, increasing funding to improve healthcare services, rising patient pool.
The market growth is further attributed to high demand for cost-effective treatments, adoption of mobile healthcare applications, and the fast integration of digital technologies by healthcare organizations. However, the requirement of significant investments to implement big data services and the lack of awareness about the digital-technology based healthcare applications may hinder the market growth over the forecast period.
Big data in healthcare market is segmented into component and services, application, delivery model, healthcare vertical, and region. The component and services segment comprises hardware (data servers and storage, servers, and networking), software (electronic health records, practice management software, revenue cycle management software, and workforce management software), and analytical services (descriptive analytics, prescriptive analytics, and predictive analytics).
The hardware segment is predicted to dominate the market during the forecast years due to the high demand for digital, computer-based healthcare platforms. By application, the market is classified into clinical data analytics (quality care, population health management, clinical decision support, precision medicine, and reporting compliance), financial analytics (claims processing, revenue cycle management software, and risk assessment), and operational analytics (workforce analytics and supply chain analytics).
The clinical data analytics segment leads this market as it provides real-time data analysis and saves cost and time. By delivery model, the market is categorized into on-demand and on the cloud. By healthcare vertical, the market is classified into pharmaceutical, medical devices, healthcare services, and other verticals. The healthcare services are accounted for the highest market share due to the increasing demand for advanced healthcare data management services. Region-wise, the market is studied across North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa.
North America is expected to witness the highest growth in the big data in healthcare market during the forecast years, followed by Asia-Pacific due to the rising adoption of modern technologies and the surging need to handle and analyze massive medical records.
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Report Attribute |
Specifications |
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Market Size Value In 2022 |
USD 33.36 Billion |
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Revenue Forecast In 2031 |
USD 155.59 Billion |
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Growth Rate CAGR |
CAGR of 16.8% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Billion and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Components and Services, By Application, By Delivery Model, By Healthcare Vertical |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico ;The UK; France; Italy; Spain; South Korea; South East Asia |
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Competitive Landscape |
Allscripts Healthcare Solutions, Inc., Aetna, Inc., Cerner Corporation, Cognization Technology Solutions Corporation, Computer Programs and Systems, eClinicalWorks, DELL, GE Healthcare, Health Catalyst, Epic Systems, IBM Corporation, Siemens Healthineers, Xerox Holdings Corporation, Oracle Corporation, McKesson Corporation, MedeAnalytics, Inc., Optum, Philips Healthcare, Tableau Software, Inc., Premier, Inc., SAP ERP, SAS, and other. |
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Customization Scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global Big Data in Healthcare Market Snapshot
Chapter 4. Global Big Data in Healthcare Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: By Applications Estimates & Trend Analysis
5.1. By Applications & Market Share, 2024 & 2034
5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 & 2034 for the following By Applications:
5.2.1. Opportunity Assessment
5.2.2. Clinical Data Analytics
5.2.3. Financial Analytics
5.2.4. Operational Analytics
Chapter 6. Market Segmentation 2: By Products Estimates & Trend Analysis
6.1. By Products & Market Share, 2024 & 2034
6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2021 & 2034 for the following By Products:
6.2.1. Hardware
6.2.1.1. Data and Storage
6.2.1.2. Servers
6.2.1.3. Networking
6.2.2. Software
6.2.2.1. Electronic Health Records
6.2.2.2. Practice Management Software
6.2.2.3. Revenue Cycle Management Software
6.2.2.4. Workforce Management Software
6.2.3. Analytics Services
6.2.3.1. Descriptive Analytics
6.2.3.2. Prescriptive Analytics
6.2.3.3. Predictive Analytics
Chapter 8. Competitive Landscape
8.1. Major Mergers and Acquisitions/Strategic Alliances
8.2. Company Profiles
8.2.1. Aetna, Inc.
8.2.2. Allscripts Healthcare Solutions, Inc.
8.2.3. Cerner Corporation
8.2.4. Cognization Technology Solutions Corporation
8.2.5. Computer Programs and Systems
8.2.6. DELL
8.2.7. Epic Systems
8.2.8. eClinicalWorks
8.2.9. GE Healthcare
8.2.10. Health Catalyst
8.2.11. IBM Corporation
8.2.12. McKesson Corporation
8.2.13. MedeAnalytics, Inc.
8.2.14. Optum
8.2.15. Oracle Corporation
8.2.16. Philips Healthcare
8.2.17. Premier, Inc.
8.2.18. SAP ERP
8.2.19. SAS
8.2.20. Siemens Healthineers
8.2.21. Tableau Software, Inc.
8.2.22. Xerox Holdings Corporation
8.2.23. Other Prominent Players
Global Big Data in Healthcare Market, by Components and Services 2022-2030 (Value US$ Mn)
Global Big Data in Healthcare Market, by Application, 2022-2030 (Value US$ Mn)
Global Big Data in Healthcare Market, by Delivery Model, 2022-2030 (Value US$ Mn)
Global Big Data in Healthcare Market, by Healthcare Vertical, 2022-2030 (Value US$ Mn)
Global Big Data in Healthcare Market, by Region, 2022-2030 (Value US$ Mn)
North America Big Data in Healthcare Market, by Country, 2022-2030 (Value US$ Mn)
Europe Big Data in Healthcare Market, by Country, 2022-2030 (Value US$ Mn)
Asia Pacific Big Data in Healthcare Market, by Country, 2022-2030 (Value US$ Mn)
Latin America Big Data in Healthcare Market, by Country, 2022-2030 (Value US$ Mn)
Middle East & Africa Big Data in Healthcare Market, by Country, 2022-2030 (Value US$ Mn)
Competitive Landscape
Latest Strategic Developments
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
