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市場調查報告書
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1530761

到 2030 年醫療保健市場預測中的巨量資料分析：按組件、部署模式、分析類型、應用程式、最終用戶和區域進行的全球分析

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
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，2024 年全球醫療保健巨量資料分析市場規模將達到 571 億美元，預計到 2030 年將達到 1,707 億美元，預測期內複合年成長率為 20%。

醫療保健中的巨量資料分析是指檢查來自各種醫療來源的大型複雜資料集以發現​​模式、趨勢和見解的過程。它涉及使用先進的分析工具和技術來處理大量結構化和非結構化的醫療資料。這種方法可以幫助醫療保健提供者改善患者照護、最佳化業務、預測疾病爆發、個人化治療並降低成本。透過利用巨量資料，醫療保健組織可以做出資料主導的決策，改善臨床結果，並最終改變醫療保健服務的提供方式。

根據美國國立衛生研究院（NIH）下屬的國家人類基因組研究所（NHGRI）網站上發表的報導，透過分析巨量資料。顯著增加。

對人口健康分析的需求不斷成長

人口健康分析使醫療保健組織能夠分析大型資料集並確定患者群體的趨勢、風險因素和干涉機會。這使得護理能夠採取更主動和預防性的方法，有助於最佳化資源分配，並支持基於價值的護理模式。隨著醫療保健轉向改善整個人群（而不僅僅是個別患者）的治療結果，利用巨量資料獲得人群層面的見解的能力變得至關重要，從而推動了市場的成長。

缺乏熟練人才

醫療保健組織很難吸引和留住既擁有巨量資料技術專業知識又擁有醫療保健領域知識的資料科學家、分析師和 IT 專業人員。這種技能差距對充分利用分析功能並從醫療保健資料中獲取可行見解的能力提出了挑戰。醫療保健資料的複雜性和嚴格的監管要求進一步推動了對獨特合格人才的需求，限制了招聘並減緩了市場擴張。

電子健康記錄(EHR) 的成長

EHR 產生大量結構化和非結構化患者資料，可進行分析以改善臨床決策、識別人口健康趨勢並提高業務效率。隨著 EHR 系統的互通性變得更強，資料變得更加標準化，從豐富的資料來源中獲取見解的潛力也隨之增加。分析工具可幫助醫療保健提供者從 EHR資料中提取價值，推動對巨量資料解決方案的需求，並開闢改善病患照護和結果的新途徑。

資料安全和隱私問題

醫療保健資料的敏感性使其成為網路攻擊的有吸引力的目標，而資料外洩可能會給患者和醫療保健提供者帶來嚴重後果。美國的 HIPAA 等嚴格法規對資料外洩行為實施嚴厲處罰。實施充滿挑戰，因為需要確保強力的安全措施並保護病患隱私，同時允許共用和分析資料。這些擔憂可能會阻止醫療保健組織全面實施巨量資料分析，從而限制市場成長。

COVID-19 的影響：

COVID-19 大流行加速了醫療保健中巨量資料分析的採用，因為各組織試圖追蹤病毒的傳播、預測疫情並最佳化資源分配。這次疫情凸顯了醫療保健領域資料主導決策的價值，並刺激了對分析能力的投資。然而，這也導致一些地區的醫療保健 IT 資源和預算緊張。

預計軟體產業在預測期內將是最大的產業

軟體部分預計將佔據醫療保健巨量資料分析的最大市場佔有率。這項優勢歸功於軟體解決方案在收集、處理和分析大量醫療資料方面的重要作用。分析軟體使醫療保健組織能夠從複雜的資料集獲得可行的見解，以支援臨床決策、人口健康管理和業務效率。分析演算法（包括人工智慧和機器學習功能）的日益複雜化正在進一步增強軟體解決方案的價值提案。隨著醫療保健變得更加資料主導，對高階分析軟體的需求持續成長。

雲端基礎的細分市場預計在預測期內複合年成長率最高

在巨量資料分析醫療保健市場中，雲端基礎的細分市場預計將呈現最高的成長率。雲端解決方案具有推動其快速採用的多項優勢，包括可擴展性、成本效益和易於部署。雲端基礎的分析平台使醫療保健公司能夠處理大量資料，而無需領先大量的前期基礎設施投資。隨著對雲端安全的擔憂消退和醫療保健專用雲端解決方案的出現，向雲端基礎的分析的轉變正在加速，推動了該領域的高成長率。

佔比最高的地區

北美憑藉著成熟的醫療IT基礎設施和電子健康記錄的高採用率，在巨量資料分析醫療保健市場佔據主導地位，為分析提供了豐富的資料基礎。對醫療保健品質和成本控制的嚴格監管要求正在推動資料分析的使用。領先技術供應商的存在和創新文化正在推動高級分析解決方案的開發和採用。此外，高額醫療保健支出和對數位健康計劃的投資進一步推動了北美市場的成長。

複合年成長率最高的地區：

亞太地區在巨量資料分析醫療保健市場中成長率最高。醫療保健系統的快速數位化，特別是在中國和印度等國家，正在產生大量可供分析的資料。政府為改善醫療保健的可近性和品質所做的努力正在推動對醫療保健IT基礎設施的投資。該地區人口眾多且不斷成長，因此人口健康管理和預測分析存在重大機會。此外，醫療保健領域擴大採用人工智慧和機器學習技術，加速了對高級分析解決方案的需求，為該地區的高成長潛力做出了貢獻。

提供免費客製化：

訂閱此報告的客戶可以存取以下免費自訂選項之一：

  • 公司簡介
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  • 區域分割
    • 根據客戶興趣對主要國家的市場估計、預測和複合年成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 資料分析
    • 資料檢驗
    • 研究途徑
  • 研究資訊來源
    • 主要研究資訊來源
    • 二次研究資訊來源
    • 先決條件

第3章市場趨勢分析

  • 促進因素
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19 的影響

第4章波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第5章醫療保健巨量資料分析市場：按組成部分

  • 軟體
    • 資料分析軟體
    • 資料管理軟體
    • 資料視覺化工具
  • 硬體
    • 貯存
    • 伺服器
    • 聯網
  • 服務
    • 諮詢服務
    • 實施服務
    • 支援和維護服務

第6章醫療保健巨量資料分析市場：依部署模式

  • 本地
  • 雲端基礎

第 7 章 醫療保健巨量資料分析市場：依分析類型

  • 說明分析
  • 預測分析
  • 指示性分析
  • 診斷分析

第8章醫療保健巨量資料分析市場：依應用分類

  • 臨床分析
    • 品質提升
    • 臨床決策支持
    • 精準醫療
  • 營運分析
    • 供應鏈分析
    • 人力資源分析
    • 財務分析
  • 人口健康分析
  • 詐欺檢測與預防
  • 個人化醫療
  • 其他用途

第 9 章 醫療保健巨量資料分析市場：依最終使用者分類

  • 醫院和診所
  • 付款人和保險公司
  • 製藥和生物技術公司
  • 研究所
  • 政府機構
  • 其他最終用戶

第 10 章 醫療保健巨量資料分析市場：按地區

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東/非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲

第11章 主要進展

  • 合約、夥伴關係、協作和合資企業
  • 收購和合併
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第12章 公司概況

  • 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.
  • Philips Healthcare
Product Code: SMRC26873

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
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • 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
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • 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

  • Table 1 Global Big Data Analytics in Healthcare Market Outlook, By Region (2022-2030) ($MN)
  • Table 2 Global Big Data Analytics in Healthcare Market Outlook, By Component (2022-2030) ($MN)
  • Table 3 Global Big Data Analytics in Healthcare Market Outlook, By Software (2022-2030) ($MN)
  • Table 4 Global Big Data Analytics in Healthcare Market Outlook, By Data Analytics Software (2022-2030) ($MN)
  • Table 5 Global Big Data Analytics in Healthcare Market Outlook, By Data Management Software (2022-2030) ($MN)
  • Table 6 Global Big Data Analytics in Healthcare Market Outlook, By Data Visualization Tools (2022-2030) ($MN)
  • Table 7 Global Big Data Analytics in Healthcare Market Outlook, By Hardware (2022-2030) ($MN)
  • Table 8 Global Big Data Analytics in Healthcare Market Outlook, By Storage (2022-2030) ($MN)
  • Table 9 Global Big Data Analytics in Healthcare Market Outlook, By Servers (2022-2030) ($MN)
  • Table 10 Global Big Data Analytics in Healthcare Market Outlook, By Networking (2022-2030) ($MN)
  • Table 11 Global Big Data Analytics in Healthcare Market Outlook, By Services (2022-2030) ($MN)
  • Table 12 Global Big Data Analytics in Healthcare Market Outlook, By Consulting Services (2022-2030) ($MN)
  • Table 13 Global Big Data Analytics in Healthcare Market Outlook, By Implementation Services (2022-2030) ($MN)
  • Table 14 Global Big Data Analytics in Healthcare Market Outlook, By Support and Maintenance Services (2022-2030) ($MN)
  • Table 15 Global Big Data Analytics in Healthcare Market Outlook, By Deployment Mode (2022-2030) ($MN)
  • Table 16 Global Big Data Analytics in Healthcare Market Outlook, By On-premises (2022-2030) ($MN)
  • Table 17 Global Big Data Analytics in Healthcare Market Outlook, By Cloud-based (2022-2030) ($MN)
  • Table 18 Global Big Data Analytics in Healthcare Market Outlook, By Analytics Type (2022-2030) ($MN)
  • Table 19 Global Big Data Analytics in Healthcare Market Outlook, By Descriptive Analytics (2022-2030) ($MN)
  • Table 20 Global Big Data Analytics in Healthcare Market Outlook, By Predictive Analytics (2022-2030) ($MN)
  • Table 21 Global Big Data Analytics in Healthcare Market Outlook, By Prescriptive Analytics (2022-2030) ($MN)
  • Table 22 Global Big Data Analytics in Healthcare Market Outlook, By Diagnostic Analytics (2022-2030) ($MN)
  • Table 23 Global Big Data Analytics in Healthcare Market Outlook, By Application (2022-2030) ($MN)
  • Table 24 Global Big Data Analytics in Healthcare Market Outlook, By Clinical Analytics (2022-2030) ($MN)
  • Table 25 Global Big Data Analytics in Healthcare Market Outlook, By Quality Improvement (2022-2030) ($MN)
  • Table 26 Global Big Data Analytics in Healthcare Market Outlook, By Clinical Decision Support (2022-2030) ($MN)
  • Table 27 Global Big Data Analytics in Healthcare Market Outlook, By Precision Medicine (2022-2030) ($MN)
  • Table 28 Global Big Data Analytics in Healthcare Market Outlook, By Operational Analytics (2022-2030) ($MN)
  • Table 29 Global Big Data Analytics in Healthcare Market Outlook, By Supply Chain Analytics (2022-2030) ($MN)
  • Table 30 Global Big Data Analytics in Healthcare Market Outlook, By Workforce Analytics (2022-2030) ($MN)
  • Table 31 Global Big Data Analytics in Healthcare Market Outlook, By Financial Analytics (2022-2030) ($MN)
  • Table 32 Global Big Data Analytics in Healthcare Market Outlook, By Population Health Analytics (2022-2030) ($MN)
  • Table 33 Global Big Data Analytics in Healthcare Market Outlook, By Fraud Detection and Prevention (2022-2030) ($MN)
  • Table 34 Global Big Data Analytics in Healthcare Market Outlook, By Personalized Medicine (2022-2030) ($MN)
  • Table 35 Global Big Data Analytics in Healthcare Market Outlook, By Other Applications (2022-2030) ($MN)
  • Table 36 Global Big Data Analytics in Healthcare Market Outlook, By End User (2022-2030) ($MN)
  • Table 37 Global Big Data Analytics in Healthcare Market Outlook, By Hospitals and Clinics (2022-2030) ($MN)
  • Table 38 Global Big Data Analytics in Healthcare Market Outlook, By Payers and Insurance Companies (2022-2030) ($MN)
  • Table 39 Global Big Data Analytics in Healthcare Market Outlook, By Pharmaceutical and Biotechnology Companies (2022-2030) ($MN)
  • Table 40 Global Big Data Analytics in Healthcare Market Outlook, By Research Organizations (2022-2030) ($MN)
  • Table 41 Global Big Data Analytics in Healthcare Market Outlook, By Government Organizations (2022-2030) ($MN)
  • Table 42 Global Big Data Analytics in Healthcare Market Outlook, By Other End Users (2022-2030) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.