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Big data analytics in healthcare refers to the process of gathering, processing, and analyzing large, complex health-related datasets from various sources such as electronic health records, medical devices, and genomic data. Using advanced analytical techniques such as machine learning and predictive modeling, it identifies patterns, trends, and insights that can enhance patient outcomes and optimize healthcare operations. This approach supports improved decision-making, personalized treatments, and more efficient healthcare delivery.

The primary types of analytics in healthcare big data include descriptive, predictive, prescriptive, and diagnostic analytics. Descriptive analytics focuses on examining historical data to summarize past events, such as tracking patient outcomes, treatment trends, and hospital admissions. These analytics solutions can be implemented in on-premise, cloud-based, or hybrid environments and applied to various areas such as clinical analytics, financial analytics, operational analytics, and research analytics. Key end users include hospitals and clinics, healthcare payers, research organizations, pharmaceuticals, and biotechnology companies.

The big data analytics in healthcare market research report is one of a series of new reports from The Business Research Company that provides big data analytics in healthcare market statistics, including big data analytics in the healthcare industry, global market size, regional shares, competitors with a big data analytics in healthcare market share, detailed big data analytics in healthcare market segments, market trends and opportunities, and any further data you may need to thrive in the big data analytics in the healthcare industry. This big data analytics in healthcare market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The big data analytics in healthcare market size has grown rapidly in recent years. It will grow from $44.74 billion in 2024 to $52.46 billion in 2025 at a compound annual growth rate (CAGR) of 17.2%. The growth during the historic period can be attributed to factors such as the widespread adoption of electronic health records, rising healthcare costs, the expansion of wearables and remote monitoring devices, advancements in genomics and personalized medicine, and the growth of population health management initiatives.

The big data analytics in healthcare market size is expected to see rapid growth in the next few years. It will grow to $98.19 billion in 2029 at a compound annual growth rate (CAGR) of 17.0%. In the forecast period, growth is driven by factors such as the increase in insurance claims and the need for fraud detection, the expansion of telemedicine, regulatory incentives for data sharing, greater demand for cybersecurity and compliance analytics, the global aging population, and the growing burden of chronic diseases. Key trends during the forecast period include the expansion of personalized medicine, the integration of AI and machine learning, real-time data processing, improved interoperability and data integration, and the increasing adoption of cloud-based analytics.

The growing demand for personalized medicine is anticipated to fuel the expansion of the big data analytics market in healthcare. Personalized medicine involves customizing treatment plans based on an individual's genetic composition, lifestyle, and environmental factors to improve treatment efficacy and reduce side effects. This demand is increasing as genetic research progresses, allowing for more precise treatments that are tailored to each patient's unique genetic profile, which leads to improved outcomes. Big data analytics in healthcare plays a critical role in personalized medicine by analyzing large volumes of patient data to identify patterns, which helps customize treatments, boosting their effectiveness and minimizing potential risks. For example, in February 2024, the Personalized Medicine Coalition, a US-based non-profit organization, reported that the FDA approved 16 new personalized treatments for rare diseases in 2023, a notable increase from the six approvals in 2022. As a result, the surge in personalized medicine demand is driving growth in the big data analytics sector in healthcare.

Leading companies in the big data analytics healthcare sector are increasingly focusing on creating advanced solutions, such as cloud-based data and analytics ecosystems, to improve data accessibility, scalability, and real-time decision-making. These cloud-based ecosystems are integrated platforms that enable healthcare organizations to securely store, process, and analyze vast amounts of data from multiple sources in real-time, thereby supporting better decision-making and patient care. For example, in May 2024, Health Catalyst, a US-based provider of data and analytics solutions, launched Health Catalyst Ignite-a next-generation, cloud-based data and analytics ecosystem designed specifically for healthcare organizations. Ignite integrates cutting-edge technologies, healthcare-centric data models, and user-friendly self-service tools to enable seamless data sharing, centralized governance, and AI-driven insights. This platform empowers healthcare teams at all skill levels to efficiently access and analyze data, leading to smarter decisions in clinical, operational, and financial areas.

In June 2022, Oracle Corporation, a US-based tech company, acquired Cerner Corporation for an undisclosed amount. The acquisition aims to accelerate the digital transformation of healthcare by integrating Cerner's electronic health record (EHR) systems with Oracle's cloud, AI, and analytics technologies. This integration is expected to improve data sharing, enhance patient outcomes, and streamline clinical workflows, solidifying Oracle's position as a major player in the healthcare IT industry. Cerner Corporation, based in the US, specializes in healthcare information technology (HIT) solutions, using big data analytics to enhance healthcare by leveraging de-identified, real-world patient data from its Millennium platform.

Major players in the big data analytics in healthcare market are McKesson Corporation, Microsoft Corporation, Dell Technologies Inc., International Business Machines Corporation, Cisco Systems Inc., Oracle Corporation, SAP SE, KT Corporation, GE HealthCare Technologies Inc., Infosys Limited, CSL Technologies Limited, Epic Systems Corporation, SAS Institute Inc., Verisk Analytics Inc., Alteryx Inc., Inovalon Holdings LLC, Veradigm Inc., Denodo Technologies Inc., MedeAnalytics Inc., OptumHealth Care Solutions LLC, and Zephyr Health Inc.

North America was the largest region in the big data analytics in healthcare market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in big data analytics in healthcare report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

The countries covered in the big data analytics in healthcare market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The big data analytics in healthcare market includes revenues earned by entities by providing services such as predictive analytics, clinical decision support, population health management, operational analytics, and clinical research and drug development. The market value includes the value of related goods sold by the service provider or included within the service offering. The big data analytics in healthcare market also includes sales of high-performance servers, storage solutions, graphics processing units (GPUs), and cloud infrastructure. Values in this market are 'factory gate' values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Big Data Analytics In Healthcare Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on big data analytics in healthcare market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

Reasons to Purchase

Where is the largest and fastest growing market for big data analytics in healthcare ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The big data analytics in healthcare market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

The forecasts are made after considering the major factors currently impacting the market. These include the Russia-Ukraine war, rising inflation, higher interest rates, and the legacy of the COVID-19 pandemic.

Scope

Table of Contents

1. Executive Summary

2. Big Data Analytics In Healthcare Market Characteristics

3. Big Data Analytics In Healthcare Market Trends And Strategies

4. Big Data Analytics In Healthcare Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Trade Wars and Tariffs, And Covid And Recovery On The Market

5. Global Big Data Analytics In Healthcare Growth Analysis And Strategic Analysis Framework

6. Big Data Analytics In Healthcare Market Segmentation

7. Big Data Analytics In Healthcare Market Regional And Country Analysis

8. Asia-Pacific Big Data Analytics In Healthcare Market

9. China Big Data Analytics In Healthcare Market

10. India Big Data Analytics In Healthcare Market

11. Japan Big Data Analytics In Healthcare Market

12. Australia Big Data Analytics In Healthcare Market

13. Indonesia Big Data Analytics In Healthcare Market

14. South Korea Big Data Analytics In Healthcare Market

15. Western Europe Big Data Analytics In Healthcare Market

16. UK Big Data Analytics In Healthcare Market

17. Germany Big Data Analytics In Healthcare Market

18. France Big Data Analytics In Healthcare Market

19. Italy Big Data Analytics In Healthcare Market

20. Spain Big Data Analytics In Healthcare Market

21. Eastern Europe Big Data Analytics In Healthcare Market

22. Russia Big Data Analytics In Healthcare Market

23. North America Big Data Analytics In Healthcare Market

24. USA Big Data Analytics In Healthcare Market

25. Canada Big Data Analytics In Healthcare Market

26. South America Big Data Analytics In Healthcare Market

27. Brazil Big Data Analytics In Healthcare Market

28. Middle East Big Data Analytics In Healthcare Market

29. Africa Big Data Analytics In Healthcare Market

30. Big Data Analytics In Healthcare Market Competitive Landscape And Company Profiles

31. Big Data Analytics In Healthcare Market Other Major And Innovative Companies

32. Global Big Data Analytics In Healthcare Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The Big Data Analytics In Healthcare Market

34. Recent Developments In The Big Data Analytics In Healthcare Market

35. Big Data Analytics In Healthcare Market High Potential Countries, Segments and Strategies

36. Appendix

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