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市场调查报告书
商品编码
1530761

到 2030 年医疗保健市场预测中的巨量资料分析：按组件、部署模式、分析类型、应用程式、最终用户和区域进行的全球分析

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个工作天内

价格

根据 Stratistics MRC 的数据，2024 年全球医疗保健巨量资料分析市场规模将达到 571 亿美元，预计到 2030 年将达到 1,707 亿美元，预测期内复合年增长率为 20%。

医疗保健中的巨量资料分析是指检查来自各种医疗来源的大型复杂资料集以发现​​模式、趋势和见解的过程。它涉及使用先进的分析工具和技术来处理大量结构化和非结构化的医疗资料。这种方法可以帮助医疗保健提供者改善患者照护、优化业务、预测疾病爆发、个人化治疗并降低成本。透过利用巨量资料，医疗保健组织可以做出资料主导的决策，改善临床结果，并最终改变医疗保健服务的提供方式。

根据美国国立卫生研究院（NIH）下属的国家人类基因组研究所（NHGRI）网站上发表的报导，透过分析巨量资料。显着增加。

对人口健康分析的需求不断增长

人口健康分析使医疗保健组织能够分析大型资料集并确定患者群体的趋势、风险因素和干预机会。这使得护理能够采取更主动和预防性的方法，有助于优化资源分配，并支持基于价值的护理模式。随着医疗保健转向改善整个人群（而不仅仅是个别患者）的治疗结果，利用巨量资料获得人群层面的见解的能力变得至关重要，从而推动了市场的成长。

缺乏熟练人才

医疗保健组织很难吸引和留住既拥有巨量资料技术专业知识又拥有医疗保健领域知识的资料科学家、分析师和 IT 专业人员。这种技能差距对充分利用分析功能并从医疗保健资料中获取可行见解的能力提出了挑战。医疗保健资料的复杂性和严格的监管要求进一步推动了对独特合格人才的需求，限制了招聘并减缓了市场扩张。

电子健康记录(EHR) 的成长

EHR 产生大量结构化和非结构化患者资料，可进行分析以改善临床决策、识别人口健康趋势并提高业务效率。随着 EHR 系统的互通性变得更强，资料变得更加标准化，从丰富的资料来源中获取见解的潜力也随之增加。分析工具可帮助医疗保健提供者从 EHR资料中提取价值，推动对巨量资料解决方案的需求，并开闢改善病患照护和结果的新途径。

资料安全和隐私问题

医疗保健资料的敏感性使其成为网路攻击的有吸引力的目标，而资料外洩可能会给患者和医疗保健提供者带来严重后果。美国的 HIPAA 等严格法规对资料外洩行为实施严厉处罚。实施充满挑战，因为需要确保强有力的安全措施并保护病患隐私，同时允许共用和分析资料。这些担忧可能会阻止医疗保健组织全面实施巨量资料分析，从而限制市场成长。

COVID-19 的影响：

COVID-19 大流行加速了医疗保健中巨量资料分析的采用，因为各组织试图追踪病毒的传播、预测疫情并优化资源分配。这次疫情凸显了医疗保健领域资料主导决策的价值，并刺激了对分析能力的投资。然而，这也导致一些地区的医疗保健 IT 资源和预算紧张。

预计软体产业在预测期内将是最大的产业

软体部分预计将占据医疗保健巨量资料分析的最大市场占有率。这项优势归功于软体解决方案在收集、处理和分析大量医疗资料方面的重要作用。分析软体使医疗保健组织能够从复杂的资料集获得可行的见解，以支援临床决策、人口健康管理和业务效率。分析演算法（包括人工智慧和机器学习功能）的日益复杂化正在进一步增强软体解决方案的价值提案。随着医疗保健变得更加资料主导，对高阶分析软体的需求持续增长。

云端基础的细分市场预计在预测期内复合年增长率最高

在巨量资料分析医疗保健市场中，云端基础的细分市场预计将呈现最高的成长率。云端解决方案具有推动其快速采用的多项优势，包括可扩展性、成本效益和易于部署。云端基础的分析平台使医疗保健公司能够处理大量资料，而无需领先大量的前期基础设施投资。随着对云端安全的担忧消退和医疗保健专用云端解决方案的出现，向云端基础的分析的转变正在加速，推动了该领域的高成长率。

占比最高的地区

北美凭藉着成熟的医疗IT基础设施和电子健康记录的高采用率，在巨量资料分析医疗保健市场占据主导地位，为分析提供了丰富的资料基础。对医疗保健品质和成本控制的严格监管要求正在推动资料分析的使用。领先技术供应商的存在和创新文化正在推动高级分析解决方案的开发和采用。此外，高额医疗保健支出和对数位健康计划的投资进一步推动了北美市场的成长。

复合年增长率最高的地区：

亚太地区在巨量资料分析医疗保健市场中成长率最高。医疗保健系统的快速数位化，特别是在中国和印度等国家，正在产生大量可供分析的资料。政府为改善医疗保健的可近性和品质所做的努力正在推动对医疗保健IT基础设施的投资。该地区人口众多且不断增长，因此人口健康管理和预测分析存在重大机会。此外，医疗保健领域越来越多地采用人工智慧和机器学习技术，加速了对高级分析解决方案的需求，为该地区的高成长潜力做出了贡献。

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订阅此报告的客户可以存取以下免费自订选项之一：

  • 公司简介
    • 其他市场参与者的综合分析（最多 3 家公司）
    • 主要企业SWOT分析（最多3家企业）
  • 区域分割
    • 根据客户兴趣对主要国家的市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 研究资讯来源
    • 主要研究资讯来源
    • 二次研究资讯来源
    • 先决条件

第三章市场趋势分析

  • 促进因素
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19 的影响

第4章波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第五章医疗保健巨量资料分析市场：按组成部分

  • 软体
    • 资料分析软体
    • 资料管理软体
    • 资料视觉化工具
  • 硬体
    • 贮存
    • 伺服器
    • 联网
  • 服务
    • 咨询服务
    • 实施服务
    • 支援和维护服务

第六章医疗保健巨量资料分析市场：依部署模式

  • 本地
  • 云端基础

第 7 章 医疗保健巨量资料分析市场：依分析类型

  • 说明分析
  • 预测分析
  • 指示性分析
  • 诊断分析

第八章医疗保健巨量资料分析市场：依应用分类

  • 临床分析
    • 品质提升
    • 临床决策支持
    • 精准医疗
  • 营运分析
    • 供应链分析
    • 人力资源分析
    • 财务分析
  • 人口健康分析
  • 诈欺检测与预防
  • 个人化医疗
  • 其他用途

第 9 章 医疗保健巨量资料分析市场：依最终使用者划分

  • 医院和诊所
  • 付款人和保险公司
  • 製药和生物技术公司
  • 研究所
  • 政府机构
  • 其他最终用户

第 10 章 医疗保健巨量资料分析市场：按地区

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东/非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲

第十一章 主要进展

  • 合约、伙伴关係、协作和合资企业
  • 收购和合併
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十二章 公司概况

  • 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.