Global Big Data In Healthcare Market Worth USD 105.73 Billion With a CAGR of 13.85%

Introduction

Big Data analysis in healthcare identifies hidden patterns, market trends, unknown relationships, and customer preferences to inform clinical and business decisions. Global need for Big Data solutions for people's health management and business intelligence to optimize health administration and strategy would increase the market. Big data can change current healthcare. Since 1990, technology has grown rapidly. Many healthcare organizations use big data to enhance patient outcomes and promote innovation.

Innovation in big data analytics tools is vital for managing such huge data, creating opportunities for market players to design new software and systems. Digitization of healthcare systems boosts cost and quality of care worldwide. The advances have led to more sophisticated heterogeneous data, especially unstructured data. Big data analytics in healthcare involves analyzing, integrating, and managing huge amounts of data. These data come from EHRs and biomedical records.

Despite being a leading market, big data in healthcare is new. Developing countries' demand for evidence-based clinical care will boost the market. The future of big data in healthcare will be determined by technological breakthroughs from 2022 to 2030.

Market Dynamics

Global Big Data in Healthcare Market: Drivers

• Population health analytics demand rises

Complete patient care and cost-effective prescription procedures are required for population health management. To assess clinical and claims data, they must be combined on the same platform. Future growth of the global market for big data analytics in healthcare is likely to be driven by need for improvements in care management, early sickness prediction, and hospitalization. Citizen health is also crucial to healthcare administration. This requires predictive population health analysis, which is expected to improve big data analytics deployment globally during the projection period.

• Unstructured Medical Data Is Expected to Grow Exponentially, Boosting Demand

Recent advances in metabolomics, epigenomics, proteomics, genomics, pharmacogenomics, and transcriptomics have greatly increased unstructured medical data. Rising importance of data analytics and big data in developing predictive models has opened up new vistas for the worldwide big data sector in healthcare.

Data mining techniques and healthcare IT advancements have boosted the global big data in healthcare market. This market is worldwide. Growing usage of big data in biosciences applications, especially genomic sequencing and drug detection, has boosted the global big data market in healthcare. High-quality big data services and software at reasonable rates have also increased demand in the healthcare sector.

Global Big Data in Healthcare Market: Key Future Opportunities

• Cloud-Based Big Data Techniques' Potential

In recent years, firms in the global healthcare industry have begun to embrace cloud analytics technologies over traditional on-premise business intelligence (BI) systems. As client and customer management becomes more important, greater planning, smart decision-making, and predictive modelling have become commonplace for corporate executives. According to a Harvard Business School study on cloud business analytics, industry participants are focusing more on cloud-based solutions for data discovery and visualization, predictive analytics, big data, and mobile analytics. During the projection period for the global big data in healthcare market, these factors will create profitable opportunities for analytics suppliers.

Regional Overview of Global Big Data in Healthcare Market

North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa make up the Big Data Analytics in Healthcare Market.

North America dominates the worldwide Big Data Analytics in Healthcare Market due to IoT and increased demand for patient data analytical models for better service delivery and regulatory regulations. There's plenty of patient info nearby. Pharma companies have digitized years of R&D data to make it easier to evaluate, while businesses and consumers have digitized patient information.

North America was one of the first regions to digitize, especially the healthcare industry, which generated vast volumes of raw data. AI, IoT, and big data are used in healthcare. eHealth is boosting the market for healthcare big data analytics. A growing trend in the region is the preference for value-based care over pay-for-service, which evaluates the patient's treatment accuracy rate instead of compensating healthcare professionals for completing the process.

Due to big data in healthcare and high spending, Europe is the second-largest market. Strong government R&D and greater usage of smart and connected devices drive big data in healthcare in the region. Digitization forces healthcare organizations to use big data to prevent clinical errors. Sentiment analysis using big data in healthcare is a fast-growing industry due to the rise of European pharmaceutical companies with large volumes of unstructured data.

Asia-Pacific is the fastest-growing emerging market, at 41%. Big data analytics in mobile healthcare has generated significant revenue due to rising internet and smart mobile use. Wearable systems and digital health apps have created a global need for big data in healthcare.

Key Highlights

• The global Big Data in Healthcare market was valued USD million in 2021 and is predicted to reach USD million by 2030, increasing at a CAGR of % from 2022 to 2030.
• The Global Big Data in Healthcare Market by Analytics typeare segmented into: diagnostic, descriptive, prescriptive, and predictive. Descriptive Analytics segment leads the market globally.
• By Applications, the global Big Data in Healthcare market can be broken down into Clinical Analytics, Financial Analytics, Operational Analytics, and Other Applications. Clinical Data Analytics segment has the largest market share.
• By End-User, Research Organizations, Hospitals and Clinics, Finance and Insurance Agencies, and Others are the four main categories that make up the global Big Data in Healthcare market's End-User segmentation. Hospitals segment has the largest share.
• The Global Big Data in Healthcare Market by Geography includes North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa. North America held 37% of the 2021 market. North America is the dominant leader across the globe

Competitive Players

1. IBM Watson Health
2. Google
3. Microsoft
4. Cerner Corporation
5. Epic Systems Corporation
6. Healthix
7. SAS Institute
8. Oracle Health Sciences
9. Allscripts Healthcare Solutions
10. Philips Healthcare
11. Tempus
12. Qualcomm Life
13. GE Healthcare
14. Cloudera
15. CureMetrix

Recent Developments

Recent Developments

• July 2024 - The WHO/Europe introduced the Strategic Partners’ Initiative for Data and Digital Health (SPI-DDH). This collaborative network unites the 53 Member States of the WHO European Region alongside prominent partners in data and digital health. The SPI-DDH is designed to address challenges associated with the digital transformation of health systems, promoting a future where patients and healthcare workers alike can access safe, affordable, and person-centered digital health technologies.

Analyst Opinion

As per our analyst, the big data in healthcare market represents a transformative force with the potential to significantly enhance patient outcomes and operational efficiency. By harnessing advanced analytics, artificial intelligence (AI), and machine learning, the utilization of healthcare data is being revolutionized, resulting in more accurate diagnostics, personalized treatment plans, and streamlined care delivery.

As healthcare providers increasingly invest in these cutting-edge technologies, the market is expected to experience substantial growth. The adoption of big data solutions not only promises to improve the overall quality of care but also optimizes healthcare operations, enabling providers to make informed, data-driven decisions that benefit both patients and institutions alike.

Segmentation

1. By Type
   1. Prescriptive Analytics
   2. Predictive Analytics
   3. Diagnostic Analytics
   4. Descriptive Analytics
2. By Component
   1. Software
   2. Services
3. By Deployment
   1. On-premise
   2. Cloud-based
4. By Applications
   1. Clinical Analysis
   2. Financial Analysis
   3. Operational Analysis
   4. Others
5. By End-User
   1. Hospitals and Clinics
   2. Finance and Insurance Agencies
   3. Research Organizations
   4. Others