Big Data Analytics In Healthcare Market
PUBLISHED: 2024 ID: SMRC26873
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Big Data Analytics In Healthcare Market

Big Data Analytics in Healthcare Market Forecasts to 2030 - Global Analysis By Component (Software, Hardware and Services), Deployment Mode (On-premises and Cloud-based), Analytics Type, Application, End User and Geography

4.7 (64 reviews)
4.7 (64 reviews)
Published: 2024 ID: SMRC26873

This report covers the impact of COVID-19 on this global market
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Years Covered

2022-2030

Estimated Year Value (2024)

US $57.1 BN

Projected Year Value (2030)

US $170.7 BN

CAGR (2024-2030)

20%

Regions Covered

North America, Europe, Asia Pacific, South America, and Middle East & Africa

Countries Covered

US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa

Largest Market

North America

Highest Growing Market

Asia Pacific


According to Stratistics MRC, the Global Big Data Analytics in Healthcare Market is accounted for $57.1 billion in 2024 and is expected to reach $170.7 billion by 2030 growing at a CAGR of 20% during the forecast period. Big data analytics in healthcare refers to the process of examining large, complex datasets from various medical sources to uncover patterns, trends, and insights. It involves using advanced analytical tools and techniques to process vast amounts of both structured and unstructured health data. This approach helps healthcare providers improve patient care, optimize operations, predict disease outbreaks, personalize treatments, and reduce costs. By leveraging big data, healthcare organizations can make data-driven decisions, enhance clinical outcomes, and ultimately transform the delivery of healthcare services.  

According to an article published on the National Human Genome Research Institute (NHGRI) website, a branch of the NIH, the role of big data analytics in analyzing large datasets to identify genetic and other factors for personalized medicine approaches are growing significantly.

Market Dynamics:

Driver: 

Rising demand for population health analytics

Population health analytics allows healthcare organizations to analyze large datasets to identify trends, risk factors, and opportunities for intervention across patient populations. This enables more proactive and preventive care approaches, helps optimize resource allocation, and supports value-based care models. As healthcare shifts towards improving outcomes for entire populations rather than just individual patients, the ability to leverage big data for population-level insights has become critical, fueling market growth.

Restraint:

Lack of skilled workforce

Healthcare organizations struggle to find and retain data scientists, analysts, and IT professionals with both technical expertise in big data technologies and domain knowledge of healthcare. This skill gap makes it challenging to fully leverage analytics capabilities and derive actionable insights from healthcare data. The complex nature of healthcare data and strict regulatory requirements further compound the need for uniquely qualified talent, limiting adoption and slowing market expansion.

Opportunity:

Growth of electronic health records (EHRs)

EHRs generate vast amounts of structured and unstructured patient data that can be analyzed to improve clinical decision-making, identify population health trends, and enhance operational efficiency. As EHR systems become more interoperable and data standardization improves, the potential for deriving insights from this rich data source grows. Analytics tools can help healthcare providers extract value from EHR data, driving demand for big data solutions and opening new avenues for improving patient care and outcomes.

Threat:

Data security and privacy concerns

The sensitive nature of healthcare data makes it an attractive target for cyberattacks, and any breaches can have severe consequences for patients and providers. Strict regulations like HIPAA in the US impose hefty penalties for data breaches. The need to ensure robust security measures and maintain patient privacy while still enabling data sharing and analysis creates challenges for implementation. These concerns can make healthcare organizations hesitant to fully embrace big data analytics, potentially limiting market growth.

Covid-19 Impact: 

The COVID-19 pandemic accelerated adoption of big data analytics in healthcare as organizations sought to track the virus spread, predict outbreaks, and optimize resource allocation. It highlighted the value of data-driven decision making in healthcare and spurred investments in analytics capabilities. However, it also strained healthcare IT resources and budgets in some areas.

The software segment is expected to be the largest during the forecast period

The software segment is anticipated to hold the largest market share in big data analytics for healthcare. This dominance is driven by the critical role of software solutions in collecting, processing, and analyzing vast amounts of healthcare data. Analytics software enables healthcare organizations to derive actionable insights from complex datasets, supporting clinical decision-making, population health management, and operational efficiency. The increasing sophistication of analytics algorithms, including AI and machine learning capabilities, further enhances the value proposition of software solutions. As healthcare becomes more data-driven, demand for advanced analytics software continues to grow.

The cloud-based segment is expected to have the highest CAGR during the forecast period

The cloud-based segment is projected to experience the highest growth rate in the big data analytics healthcare market. Cloud solutions offer several advantages that are driving rapid adoption, including scalability, cost-effectiveness, and ease of implementation. Cloud-based analytics platforms allow healthcare organizations to handle large volumes of data without significant upfront infrastructure investments. As concerns about cloud security are addressed and more healthcare-specific cloud solutions emerge, the shift towards cloud-based analytics is accelerating, fueling this segment's high growth rate.

Region with largest share:

North America's dominance in the big data analytics healthcare market is due to its mature healthcare IT infrastructure and high adoption rates of electronic health records, which provide a rich data foundation for analytics. Stringent regulatory requirements around healthcare quality and cost containment incentivize the use of data analytics. The presence of major technology vendors and a culture of innovation foster the development and adoption of advanced analytics solutions. Additionally, significant healthcare spending and investments in digital health initiatives further propel market growth in North America.

Region with highest CAGR:

The Asia Pacific region is poised for the highest growth rate in the big data analytics healthcare market. Rapid digitization of healthcare systems, particularly in countries like China and India, is generating vast amounts of data ripe for analysis. Government initiatives to improve healthcare access and quality are driving investments in health IT infrastructure. The region's large and growing population presents significant opportunities for population health management and predictive analytics. Additionally, the increasing adoption of AI and machine learning technologies in healthcare is accelerating the demand for advanced analytics solutions, contributing to the region's high growth potential.

Key players in the market

Some of the key players in Big Data Analytics in Healthcare market include IBM Corporation, Microsoft Corporation, Oracle Corporation, SAS Institute Inc., SAP SE, Allscripts Healthcare Solutions, Inc., Cerner Corporation, Cognizant Technology Solutions Corporation, Epic Systems Corporation, GE Healthcare, Optum, Inc., Siemens Healthineers AG, Dell Technologies Inc., McKesson Corporation, Hewlett Packard Enterprise (HPE), Tableau Software, LLC, TIBCO Software Inc., and Philips Healthcare.

Key Developments:

In October 2023, Microsoft has launched new healthcare-specific data solutions in Microsoft Fabric to help healthcare organizations unify and analyze data from various sources. These new solutions offer healthcare organizations a unified, safe and responsible approach to their data and AI strategy and enable them to take advantage of the breadth and scale of Microsoft Cloud for Healthcare.

In October 2023, IBM introduced the new IBM Storage Scale System 6000, a cloud-scale global data platform designed to meet today's data intensive and AI workload demands, and the latest offering in the IBM Storage for Data and AI portfolio. The new IBM Storage Scale System 6000 seeks to build on IBM's leadership position with an enhanced high performance parallel file system designed for data intensive use-cases. It provides up to 7M IOPs and up to 256GB/s throughput for read only workloads per system in a 4U (four rack units) footprint.

Components Covered:
• Software
• Hardware
• Services

Deployment Modes Covered:
• On-premises
• Cloud-based

Analytics Types Covered:
• Descriptive Analytics
• Predictive Analytics
• Prescriptive Analytics
• Diagnostic Analytics

Applications Covered:
• Clinical Analytics
• Operational Analytics
• Population Health Analytics
• Fraud Detection and Prevention
• Personalized Medicine
• Other Applications

End Users Covered:
• Hospitals and Clinics
• Payers and Insurance Companies
• Pharmaceutical and Biotechnology Companies
• Research Organizations
• Government Organizations
• Other End Users

Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan        
o China        
o India        
o Australia  
o New Zealand
o South Korea
o Rest of Asia Pacific    
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa 
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa

What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements

Free Customization Offerings: 
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary       
        
2 Preface       
 2.1 Abstract      
 2.2 Stake Holders      
 2.3 Research Scope      
 2.4 Research Methodology      
  2.4.1 Data Mining     
  2.4.2 Data Analysis     
  2.4.3 Data Validation     
  2.4.4 Research Approach     
 2.5 Research Sources      
  2.5.1 Primary Research Sources     
  2.5.2 Secondary Research Sources     
  2.5.3 Assumptions     
        
3 Market Trend Analysis       
 3.1 Introduction      
 3.2 Drivers      
 3.3 Restraints      
 3.4 Opportunities      
 3.5 Threats      
 3.6 Application Analysis      
 3.7 End User Analysis      
 3.8 Emerging Markets      
 3.9 Impact of Covid-19      
        
4 Porters Five Force Analysis       
 4.1 Bargaining power of suppliers      
 4.2 Bargaining power of buyers      
 4.3 Threat of substitutes      
 4.4 Threat of new entrants      
 4.5 Competitive rivalry      
        
5 Global Big Data Analytics in Healthcare Market, By Component       
 5.1 Introduction      
 5.2 Software      
  5.2.1 Data Analytics Software     
  5.2.2 Data Management Software     
  5.2.3 Data Visualization Tools     
 5.3 Hardware      
  5.3.1 Storage     
  5.3.2 Servers     
  5.3.3 Networking     
 5.4 Services      
  5.4.1 Consulting Services     
  5.4.2 Implementation Services     
  5.4.3 Support and Maintenance Services     
        
6 Global Big Data Analytics in Healthcare Market, By Deployment Mode       
 6.1 Introduction      
 6.2 On-premises      
 6.3 Cloud-based      
        
7 Global Big Data Analytics in Healthcare Market, By Analytics Type       
 7.1 Introduction      
 7.2 Descriptive Analytics      
 7.3 Predictive Analytics      
 7.4 Prescriptive Analytics      
 7.5 Diagnostic Analytics      
        
8 Global Big Data Analytics in Healthcare Market, By Application       
 8.1 Introduction      
 8.2 Clinical Analytics      
  8.2.1 Quality Improvement     
  8.2.2 Clinical Decision Support     
  8.2.3 Precision Medicine     
 8.3 Operational Analytics      
  8.3.1 Supply Chain Analytics     
  8.3.2 Workforce Analytics     
  8.3.3 Financial Analytics     
 8.4 Population Health Analytics      
 8.5 Fraud Detection and Prevention      
 8.6 Personalized Medicine      
 8.7 Other Applications      
        
9 Global Big Data Analytics in Healthcare Market, By End User       
 9.1 Introduction      
 9.2 Hospitals and Clinics      
 9.3 Payers and Insurance Companies      
 9.4 Pharmaceutical and Biotechnology Companies      
 9.5 Research Organizations      
 9.6 Government Organizations      
 9.7 Other End Users      
        
10 Global Big Data Analytics in Healthcare Market, By Geography       
 10.1 Introduction      
 10.2 North America      
  10.2.1 US     
  10.2.2 Canada     
  10.2.3 Mexico     
 10.3 Europe      
  10.3.1 Germany     
  10.3.2 UK     
  10.3.3 Italy     
  10.3.4 France     
  10.3.5 Spain     
  10.3.6 Rest of Europe     
 10.4 Asia Pacific      
  10.4.1 Japan     
  10.4.2 China     
  10.4.3 India     
  10.4.4 Australia     
  10.4.5 New Zealand     
  10.4.6 South Korea     
  10.4.7 Rest of Asia Pacific     
 10.5 South America      
  10.5.1 Argentina     
  10.5.2 Brazil     
  10.5.3 Chile     
  10.5.4 Rest of South America     
 10.6 Middle East & Africa      
  10.6.1 Saudi Arabia     
  10.6.2 UAE     
  10.6.3 Qatar     
  10.6.4 South Africa     
  10.6.5 Rest of Middle East & Africa     
        
11 Key Developments       
 11.1 Agreements, Partnerships, Collaborations and Joint Ventures      
 11.2 Acquisitions & Mergers      
 11.3 New Product Launch      
 11.4 Expansions      
 11.5 Other Key Strategies      
        
12 Company Profiling       
 12.1 IBM Corporation      
 12.2 Microsoft Corporation      
 12.3 Oracle Corporation      
 12.4 SAS Institute Inc.      
 12.5 SAP SE      
 12.6 Allscripts Healthcare Solutions, Inc.      
 12.7 Cerner Corporation      
 12.8 Cognizant Technology Solutions Corporation      
 12.9 Epic Systems Corporation      
 12.10 GE Healthcare      
 12.11 Optum, Inc.      
 12.12 Siemens Healthineers AG      
 12.13 Dell Technologies Inc.      
 12.14 McKesson Corporation      
 12.15 Hewlett Packard Enterprise (HPE)      
 12.16 Tableau Software, LLC      
 12.17 TIBCO Software Inc.      
 12.18 Philips Healthcare      
        
List of Tables        
1 Global Big Data Analytics in Healthcare Market Outlook, By Region (2022-2030) ($MN)       
2 Global Big Data Analytics in Healthcare Market Outlook, By Component (2022-2030) ($MN)       
3 Global Big Data Analytics in Healthcare Market Outlook, By Software (2022-2030) ($MN)       
4 Global Big Data Analytics in Healthcare Market Outlook, By Data Analytics Software (2022-2030) ($MN)       
5 Global Big Data Analytics in Healthcare Market Outlook, By Data Management Software (2022-2030) ($MN)       
6 Global Big Data Analytics in Healthcare Market Outlook, By Data Visualization Tools (2022-2030) ($MN)       
7 Global Big Data Analytics in Healthcare Market Outlook, By Hardware (2022-2030) ($MN)       
8 Global Big Data Analytics in Healthcare Market Outlook, By Storage (2022-2030) ($MN)       
9 Global Big Data Analytics in Healthcare Market Outlook, By Servers (2022-2030) ($MN)       
10 Global Big Data Analytics in Healthcare Market Outlook, By Networking (2022-2030) ($MN)       
11 Global Big Data Analytics in Healthcare Market Outlook, By Services (2022-2030) ($MN)       
12 Global Big Data Analytics in Healthcare Market Outlook, By Consulting Services (2022-2030) ($MN)       
13 Global Big Data Analytics in Healthcare Market Outlook, By Implementation Services (2022-2030) ($MN)       
14 Global Big Data Analytics in Healthcare Market Outlook, By Support and Maintenance Services (2022-2030) ($MN)       
15 Global Big Data Analytics in Healthcare Market Outlook, By Deployment Mode (2022-2030) ($MN)       
16 Global Big Data Analytics in Healthcare Market Outlook, By On-premises (2022-2030) ($MN)       
17 Global Big Data Analytics in Healthcare Market Outlook, By Cloud-based (2022-2030) ($MN)       
18 Global Big Data Analytics in Healthcare Market Outlook, By Analytics Type (2022-2030) ($MN)       
19 Global Big Data Analytics in Healthcare Market Outlook, By Descriptive Analytics (2022-2030) ($MN)       
20 Global Big Data Analytics in Healthcare Market Outlook, By Predictive Analytics (2022-2030) ($MN)       
21 Global Big Data Analytics in Healthcare Market Outlook, By Prescriptive Analytics (2022-2030) ($MN)       
22 Global Big Data Analytics in Healthcare Market Outlook, By Diagnostic Analytics (2022-2030) ($MN)       
23 Global Big Data Analytics in Healthcare Market Outlook, By Application (2022-2030) ($MN)       
24 Global Big Data Analytics in Healthcare Market Outlook, By Clinical Analytics (2022-2030) ($MN)       
25 Global Big Data Analytics in Healthcare Market Outlook, By Quality Improvement (2022-2030) ($MN)       
26 Global Big Data Analytics in Healthcare Market Outlook, By Clinical Decision Support (2022-2030) ($MN)       
27 Global Big Data Analytics in Healthcare Market Outlook, By Precision Medicine (2022-2030) ($MN)       
28 Global Big Data Analytics in Healthcare Market Outlook, By Operational Analytics (2022-2030) ($MN)       
29 Global Big Data Analytics in Healthcare Market Outlook, By Supply Chain Analytics (2022-2030) ($MN)       
30 Global Big Data Analytics in Healthcare Market Outlook, By Workforce Analytics (2022-2030) ($MN)       
31 Global Big Data Analytics in Healthcare Market Outlook, By Financial Analytics (2022-2030) ($MN)       
32 Global Big Data Analytics in Healthcare Market Outlook, By Population Health Analytics (2022-2030) ($MN)       
33 Global Big Data Analytics in Healthcare Market Outlook, By Fraud Detection and Prevention (2022-2030) ($MN)       
34 Global Big Data Analytics in Healthcare Market Outlook, By Personalized Medicine (2022-2030) ($MN)       
35 Global Big Data Analytics in Healthcare Market Outlook, By Other Applications (2022-2030) ($MN)       
36 Global Big Data Analytics in Healthcare Market Outlook, By End User (2022-2030) ($MN)       
37 Global Big Data Analytics in Healthcare Market Outlook, By Hospitals and Clinics (2022-2030) ($MN)       
38 Global Big Data Analytics in Healthcare Market Outlook, By Payers and Insurance Companies (2022-2030) ($MN)       
39 Global Big Data Analytics in Healthcare Market Outlook, By Pharmaceutical and Biotechnology Companies (2022-2030) ($MN)       
40 Global Big Data Analytics in Healthcare Market Outlook, By Research Organizations (2022-2030) ($MN)       
41 Global Big Data Analytics in Healthcare Market Outlook, By Government Organizations (2022-2030) ($MN)       
42 Global Big Data Analytics in Healthcare Market Outlook, By Other End Users (2022-2030) ($MN)       
        
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.        

List of Figures

RESEARCH METHODOLOGY


Research Methodology

We at Stratistics opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.

Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.

Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.

Data Mining

The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.

Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.

Data Analysis

From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:

  • Product Lifecycle Analysis
  • Competitor analysis
  • Risk analysis
  • Porters Analysis
  • PESTEL Analysis
  • SWOT Analysis

The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.


Data Validation

The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.

We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.

The data validation involves the primary research from the industry experts belonging to:

  • Leading Companies
  • Suppliers & Distributors
  • Manufacturers
  • Consumers
  • Industry/Strategic Consultants

Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.


For more details about research methodology, kindly write to us at info@strategymrc.com

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