サンプル依頼リスト カート
  • English
  • Korean
  • Traditional Chinese
  • Simplified Chinese
表紙：ヘルスケアにおけるビッグデータ市場、産業動向と世界予測 (～2035年)：コンポーネント別、ハードウェアタイプ別、ソフトウェア・サービス別、展開オプション別、応用分野別、ヘルスケア分野別、エンドユーザー別、経済状況別
市場調査レポート
商品コード
1439183

ヘルスケアにおけるビッグデータ市場、産業動向と世界予測 (～2035年)：コンポーネント別、ハードウェアタイプ別、ソフトウェア・サービス別、展開オプション別、応用分野別、ヘルスケア分野別、エンドユーザー別、経済状況別

Big Data in Healthcare Market, Trends & Forecasts, Till 2035: Distribution by Component, Type of Hardware, Software & Service, Deployment Option, Application Area, Healthcare Vertical, End User, & Leading Players: Industry Trends & Global Forecasts
出版日: | 発行: Roots Analysis | ページ情報: 英文 331 Pages | 納期: 即日から翌営業日

● お客様のご希望に応じて、既存データの加工や未掲載情報（例：国別セグメント）の追加などの対応が可能です。　 詳細はお問い合わせください。

価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=157.14円
ヘルスケアにおけるビッグデータ市場、産業動向と世界予測 (～2035年)：コンポーネント別、ハードウェアタイプ別、ソフトウェア・サービス別、展開オプション別、応用分野別、ヘルスケア分野別、エンドユーザー別、経済状況別
出版日: 2024年01月05日
発行: Roots Analysis
ページ情報: 英文 331 Pages
納期: 即日から翌営業日
  • 全表示
  • 概要
  • 図表
  • 目次
概要

ヘルスケアにおけるビッグデータの市場規模は、2023年には670億米ドルとなり、予測期間の2023年～2035年のCAGRは19％になると予測されています。

ヘルスケア分野のビッグデータには、医学研究論文、生体データ、電子カルテ、医療モノのインターネット（IoMT）、ソーシャルメディア、支払者記録、オミックス研究、データリポジトリなど、さまざまな媒体から入手した膨大な量の非構造化データが含まれます。このような異種かつ複雑な非構造化データを従来のデータベースに統合することは、相互運用性を確保し、効果的な分析を促進するために不可欠なデータの整理と標準化という点で、大きな課題となっています。

しかし、ビッグデータ分析ツール、人工知能（AI）、機械学習（ML）の最近の進歩により、ヘルスケアのビッグデータを価値ある実用的な洞察に変換することが可能になっています。これらの技術的進歩はヘルスケアの多方面に革命をもたらし、データ主導の意思決定を促進し、診断を強化し、個別化された治療方法を可能にし、オンラインポータル、モバイルアプリケーション、ウェアラブルデバイスなどのセルフサービスオプションを通じて患者に力を与えています。さらに、ビッグデータ分析ツールは、医薬品の研究開発（R&D）における創薬・開発プロセスの迅速化においても極めて重要な役割を果たしています。ビジネスインテリジェンスソリューションに対する需要の高まり、非構造化データの急増、個別化医療の重視の高まりに後押しされ、ヘルスケアにおけるビッグデータの世界市場は、予測期間を通じて持続的な市場成長を遂げるものと位置付けられています。

当レポートでは、世界のヘルスケアにおけるビッグデータ市場について調査し、市場の概要とともに、コンポーネント別、ハードウェアタイプ別、ソフトウェア・サービス別、展開オプション別、応用分野別、ヘルスケア分野別、エンドユーザー別、経済状況別の動向、および市場に参入する企業のプロファイルなどを提供しています。

目次

第1章 序文

第2章 調査手法

第3章 経済およびその他のプロジェクト特有の考慮事項

第4章 エグゼクティブサマリー

第5章 イントロダクション

  • 章の概要
  • ビッグデータの概要
  • ビッグデータ分析
  • ヘルスケアにおけるビッグデータの応用
  • 将来の展望

第6章 全体的な市場情勢

第7章 主要な洞察

第8章 企業の競争力分析

第9章 企業プロファイル：北米のヘルスケアサービスプロバイダーにおけるビッグデータ

第10章 企業プロファイル：欧州のヘルスケアサービスプロバイダーにおけるビッグデータ

第11章 企業プロファイル：アジアおよび世界のその他の地域のヘルスケアサービスプロバイダーにおけるビッグデータ

第12章 市場への影響分析：促進要因、抑制要因、機会、課題

  • 章の概要
  • 市場促進要因
  • 市場抑制要因
  • 市場機会
  • 市場の課題
  • 結論

第13章 世界のヘルスケアにおけるビッグデータ市場

第14章 ヘルスケアにおけるビッグデータ市場、コンポーネント別

第15章 ヘルスケアにおけるビッグデータ市場、ハードウェアタイプ別

第16章 ヘルスケアにおけるビッグデータ市場、ソフトウェアタイプ別

第17章 ヘルスケアにおけるビッグデータ市場、サービスタイプ別

第18章 ヘルスケアにおけるビッグデータ市場、展開オプション別

第19章 ヘルスケアにおけるビッグデータ市場、応用分野別

第20章 ヘルスケアにおけるビッグデータ市場、ヘルスケア分野別

第21章 ヘルスケアにおけるビッグデータ市場、エンドユーザー別

第22章 ヘルスケアにおけるビッグデータ市場、経済状況別

第23章 ヘルスケアにおけるビッグデータ市場、地域別

第24章 ヘルスケアにおけるビッグデータ市場、主要企業の収益予測

  • 章の概要
  • 主な前提と調査手法
  • Microsoft
  • Optum
  • IBM
  • Oracle
  • Allscripts

第25章 結論

第26章 エグゼクティブインサイト

第27章 付録I：表形式のデータ

第28章 付録II：企業および組織のリスト

図表

List of Tables

  • Table 5.1 Comparison between Data Lake and Data Warehouse
  • Table 6.1 List of Big Data in Healthcare Service Providers
  • Table 6.2 Big Data in Healthcare Service Providers: Information on Type of Offering and Type of Big Data Analytics Offered
  • Table 6.3 Big Data in Healthcare Service Providers: Information on Type of Big Data Storage Solution Offered and Deployment Option
  • Table 6.4 Big Data in Healthcare Service Providers: Information on Application Area and End User
  • Table 8.1 Company Competitiveness Analysis: Big Data In Healthcare Service Providers based in North America
  • Table 8.2 Company Competitiveness Analysis: Big Data In Healthcare Service Providers based in Europe
  • Table 8.3 Company Competitiveness Analysis: Big Data In Healthcare Service Providers Based in Asia and Rest of the World
  • Table 9.1 Big Data in Healthcare Service Providers in North America: List Companies Profiled
  • Table 9.2 Amazon Web Services: Company Snapshot
  • Table 9.3 Amazon Web Services: Big Data Offerings and Capabilities
  • Table 9.4 Amazon Web Services: Recent Developments and Future Outlook
  • Table 9.5 Microsoft: Company Snapshot
  • Table 9.6 Microsoft: Big Data Offerings and Capabilities
  • Table 9.7 Microsoft: Recent Developments and Future Outlook
  • Table 9.8 Oracle: Company Snapshot
  • Table 9.9 Oracle: Big Data Offerings and Capabilities
  • Table 9.10 Oracle: Recent Developments and Future Outlook
  • Table 9.11 Teradata: Company Snapshot
  • Table 9.12 Teradata: Big Data Offerings and Capabilities
  • Table 9.13 Teradata: Recent Developments and Future Outlook
  • Table 9.14 Itransition: Company Snapshot
  • Table 9.15 Itransition: Big Data Offerings and Capabilities
  • Table 9.16 Nous Infosystems: Company Snapshot
  • Table 9.17 Nous Infosystems: Big Data Offerings and Capabilities
  • Table 9.18 Oxagile: Company Snapshot
  • Table 9.19 Oxagile: Big Data Offerings and Capabilities
  • Table 9.20 Softweb Solutions: Company Snapshot
  • Table 9.21 Softweb Solutions: Big Data Offerings and Capabilities
  • Table 9.22 Solix Technologies: Company Snapshot
  • Table 9.23 Solix Technologies: Big Data Offerings and Capabilities
  • Table 9.24 Trianz (formerly CBIG Consulting): Company Snapshot
  • Table 9.25 Trianz (formerly CBIG Consulting): Big Data Offerings and Capabilities
  • Table 10.1 Big Data in Healthcare Service Providers in Europe: List Companies Profiled
  • Table 10.2 Accenture: Company Snapshot
  • Table 10.3 Accenture: Big Data Offerings and Capabilities
  • Table 10.4 Accenture: Recent Developments and Future Outlook
  • Table 10.5 Keyrus: Company Snapshot
  • Table 10.6 Keyrus: Big Data Offerings and Capabilities
  • Table 10.7 Keyrus: Recent Developments and Future Outlook
  • Table 10.8 Akka Technologies: Company Snapshot
  • Table 10.9 Akka Technologies: Big Data Offerings and Capabilities
  • Table 10.10 Altamira.ai: Company Snapshot
  • Table 10.11 Altamira.ai: Big Data Offerings and Capabilities
  • Table 10.12 atom Consultancy Services (ACS): Company Snapshot
  • Table 10.13 atom Consultancy Services (ACS): Big Data Offerings and Capabilities
  • Table 10.14 Avenga: Company Snapshot
  • Table 10.15 Avenga: Big Data Offerings and Capabilities
  • Table 10.16 Lutech: Company Snapshot
  • Table 10.17 Lutech: Big Data Offerings and Capabilities
  • Table 10.18 Nagarro: Company Snapshot
  • Table 10.19 Nagarro: Big Data Offerings and Capabilities
  • Table 10.20 Scalefocus: Company Snapshot
  • Table 10.21 Scalefocus: Big Data Offerings and Capabilities
  • Table 10.22 Scalefocus: Company Snapshot
  • Table 10.23 Scalefocus: Big Data Offerings and Capabilities
  • Table 11.1 Big Data in Healthcare Service Providers in Asia and Rest of the World: List Companies Profiled
  • Table 11.2 Tata Elxsi: Company Snapshot
  • Table 11.3 Tata Elxsi: Big Data Offerings and Capabilities
  • Table 11.4 Kellton: Company Snapshot
  • Table 11.5 Kellton: Big Data Offerings and Capabilities
  • Table 11.6 Athena Global Technologies: Company Snapshot
  • Table 11.7 Athena Global Technologies: Big Data Offerings and Capabilities
  • Table 11.8 Happiest Minds: Company Snapshot
  • Table 11.9 Happiest Minds: Big Data Offerings and Capabilities
  • Table 11.10 InData Labs: Company Snapshot
  • Table 11.11 InData Labs: Big Data Offerings and Capabilities
  • Table 11.12 NTT Data: Company Snapshot
  • Table 11.13 NTT Data: Big Data Offerings and Capabilities
  • Table 11.14 OrangeMantra: Company Snapshot
  • Table 11.15 OrangeMantra: Big Data Offerings and Capabilities
  • Table 11.16 Trigyn Technologies: Company Snapshot
  • Table 11.17 Trigyn Technologies: Big Data Offerings and Capabilities
  • Table 11.18 XenonStack: Company Snapshot
  • Table 11.19 XenonStack: Big Data Offerings and Capabilities
  • Table 26.1 Emorphis Technologies: Company Snapshot
  • Table 26.2 Estenda Solutions: Company Snapshot
  • Table 26.3 DataToBiz: Company Snapshot
  • Table 26.4 Growth Acceleration Partners: Company Snapshot
  • Table 26.5 W2S Solutions: Company Snapshot
  • Table 26.6 OrangeMantra: Company Snapshot
  • Table 26.7 Soulpage IT Solutions: Company Snapshot
  • Table 26.8 TechMango: Company Snapshot
  • Table 26.9 Tata Elxsi: Company Snapshot
  • Table 26.10 OpenXcell: Company Snapshot
  • Table 26.11 ThirdEye Data: Company Snapshot
  • Table 26.12 NTT Data Services: Company Snapshot
  • Table 26.13 CodeRiders: Company Snapshot
  • Table 26.14 Xenon Stack: Company Snapshot
  • Table 27.1 Big Data in Healthcare Service Providers: Distribution by Year of Establishment
  • Table 27.2 Big Data in Healthcare Service Providers: Distribution by Company Size
  • Table 27.3 Big Data in Healthcare Service Providers: Distribution by Location of Headquarters
  • Table 27.4 Big Data in Healthcare Service Providers: Distribution by Type of Business Model
  • Table 27.5 Big Data in Healthcare Service Providers: Distribution by Type of Offering
  • Table 27.6 Big Data in Healthcare Service Providers: Type of Big Data Analytics Offered
  • Table 27.7 Big Data in Healthcare Service Providers: Type of Big Data Storage Solution Offered
  • Table 27.8 Big Data in Healthcare Service Providers: Distribution by Deployment Option
  • Table 27.9 Big Data in Healthcare Service Providers: Distribution by Application Area
  • Table 27.10 Big Data in Healthcare Service Providers: Distribution by End User
  • Table 27.11 Big Data in Healthcare Service Providers: Distribution by Year of Establishment and Company Size
  • Table 27.12 Big Data in Healthcare Service Providers: Distribution by Company Size and Location of Headquarters
  • Table 27.13 Big Data in Healthcare Service Providers: Distribution by Type of Offering and Company Size
  • Table 27.14 Big Data in Healthcare Service Providers: Distribution by Type of Big Data Analytics Offered and Application Area
  • Table 27.15 Big Data in Healthcare Service Providers: Distribution by Company Size, Application Area and End User
  • Table 27.16 Global Market for Big Data in Healthcare, Historical Trends (2018-2022) (USD Billion)
  • Table 27.17 Global Market for Big Data in Healthcare, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.18 Big Data in Healthcare Market for Hardware, Historical Trends (2018-2022) (USD Billion)
  • Table 27.19 Big Data in Healthcare Market for Hardware, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.20 Big Data in Healthcare Market for Software, Historical Trends (2018-2022) (USD Billion)
  • Table 27.21 Big Data in Healthcare Market for Software, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.22 Big Data in Healthcare Market for Services, Historical Trends (2018-2022) (USD Billion)
  • Table 27.23 Big Data in Healthcare Market for Services, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.24 Big Data in Healthcare Market for Storage Devices, Historical Trends (2018-2022) (USD Billion)
  • Table 27.25 Big Data in Healthcare Market for Storage Devices, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.26 Big Data in Healthcare Market for Servers, Historical Trends (2018-2022) (USD Billion)
  • Table 27.27 Big Data in Healthcare Market for Servers, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.28 Big Data in Healthcare Market for Networking Infrastructure, Historical Trends (2018-2022) (USD Billion)
  • Table 27.29 Big Data in Healthcare Market for Networking Infrastructure, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.30 Big Data in Healthcare Market for Electronic Health Record, Historical Trends (2018-2022) (USD Billion)
  • Table 27.31 Big Data in Healthcare Market for Electronic Health Record, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.32 Big Data in Healthcare Market for Revenue Cycle Management Software, Historical Trends (2018-2022) (USD Billion)
  • Table 27.33 Big Data in Healthcare Market for Revenue Cycle Management Software, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.34 Big Data in Healthcare Market for Practice Management Software, Historical Trends (2018-2022) (USD Billion)
  • Table 27.35 Big Data in Healthcare Market for Practice Management Software, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.36 Big Data in Healthcare Market for Workforce Management Software, Historical Trends (2018-2022) (USD Billion)
  • Table 27.37 Big Data in Healthcare Market for Workforce Management Software, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.38 Big Data in Healthcare Market for Diagnostic Analytics, Historical Trends (2018-2022) (USD Billion)
  • Table 27.39 Big Data in Healthcare Market for Diagnostic Analytics, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.40 Big Data in Healthcare Market for Descriptive Analytics, Historical Trends (2018-2022) (USD Billion)
  • Table 27.41 Big Data in Healthcare Market for Descriptive Analytics, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.42 Big Data in Healthcare Market for Predictive Analytics, Historical Trends (2018-2022) (USD Billion)
  • Table 27.43 Big Data in Healthcare Market for Predictive Analytics, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.44 Big Data in Healthcare Market for Prescriptive Analytics, Historical Trends (2018-2022) (USD Billion)
  • Table 27.45 Big Data in Healthcare Market for Prescriptive Analytics, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.46 Big Data in Healthcare Market for Cloud-based Deployment, Historical Trends (2018-2022) (USD Billion)
  • Table 27.47 Big Data in Healthcare Market for Cloud-based Deployment, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.48 Big Data in Healthcare Market for On-premises Deployment, Historical Trends (2018-2022) (USD Billion)
  • Table 27.49 Big Data in Healthcare Market for On-premises Deployment, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.50 Big Data in Healthcare Market for Operational Management, Historical Trends (2018-2022) (USD Billion)
  • Table 27.51 Big Data in Healthcare Market for Operational Management, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.52 Big Data in Healthcare Market for Clinical Data Management, Historical Trends (2018-2022) (USD Billion)
  • Table 27.53 Big Data in Healthcare Market for Clinical Data Management, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.54 Big Data in Healthcare Market for Financial Management, Historical Trends (2018-2022) (USD Billion)
  • Table 27.55 Big Data in Healthcare Market for Financial Management, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.56 Big Data in Healthcare Market for Population Health Management, Historical Trends (2018-2022) (USD Billion)
  • Table 27.57 Big Data in Healthcare Market for Population Health Management, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.58 Big Data in Healthcare Market for Healthcare Services, Historical Trends (2018-2022) (USD Billion)
  • Table 27.59 Big Data in Healthcare Market for Healthcare Services, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.60 Big Data in Healthcare Market for Pharmaceuticals, Historical Trends (2018-2022) (USD Billion)
  • Table 27.61 Big Data in Healthcare Market for Pharmaceuticals, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.62 Big Data in Healthcare Market for Medical Devices, Historical Trends (2018-2022) (USD Billion)
  • Table 27.63 Big Data in Healthcare Market for Medical Devices, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.64 Big Data in Healthcare Market for Other Verticals, Historical Trends (2018-2022) (USD Billion)
  • Table 27.65 Big Data in Healthcare Market for Other Verticals, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.66 Big Data in Healthcare Market for Hospitals, Historical Trends (2018-2022) (USD Billion)
  • Table 27.67 Big Data in Healthcare Market for Hospitals, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.68 Big Data in Healthcare Market for Health Insurance Agencies, Historical Trends (2018-2022) (USD Billion)
  • Table 27.69 Big Data in Healthcare Market for Health Insurance Agencies, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.70 Big Data in Healthcare Market for Clinics, Historical Trends (2018-2022) (USD Billion)
  • Table 27.71 Big Data in Healthcare Market for Clinics, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.72 Big Data in Healthcare Market for Other End Users, Historical Trends (2018-2022) (USD Billion)
  • Table 27.73 Big Data in Healthcare Market for Other End Users, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.74 Big Data in Healthcare Market in High Income Countries, Historical Trends (2018-2022) (USD Billion)
  • Table 27.75 Big Data in Healthcare Market in High Income Countries, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.76 Big Data in Healthcare Market in Upper-Middle Income Countries, Historical Trends (2018-2022) (USD Billion)
  • Table 27.77 Big Data in Healthcare Market in Upper-Middle Income Countries, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.78 Big Data in Healthcare Market in Lower-Middle Income Countries, Historical Trends (2018-2022) (USD Billion)
  • Table 27.79 Big Data in Healthcare Market in Lower-Middle Income Countries, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.80 Big Data in Healthcare Market in North America, Historical Trends (2018-2022) (USD Billion)
  • Table 27.81 Big Data in Healthcare Market in North America, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.82 Big Data in Healthcare Market in Europe, Historical Trends (2018-2022) (USD Billion)
  • Table 27.83 Big Data in Healthcare Market in Europe, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.84 Big Data in Healthcare Market in Asia, Historical Trends (2018-2022) (USD Billion)
  • Table 27.85 Big Data in Healthcare Market in Asia, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.86 Big Data in Healthcare Market in Latin America, Historical Trends (2018-2022) (USD Billion)
  • Table 27.87 Big Data in Healthcare Market in Latin America, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.88 Big Data in Healthcare Market in Middle East and North Africa, Historical Trends (2018-2022) (USD Billion)
  • Table 27.89 Big Data in Healthcare Market in Middle East and North Africa, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.90 Big Data in Healthcare Market in Rest of the World, Historical Trends (2018-2022) (USD Billion)
  • Table 27.91 Big Data in Healthcare Market in Rest of the World, Forecasted Estimates (2023-2035), Conservative, Base and Optimistic Scenarios (USD Billion)
  • Table 27.92 Big Data in Healthcare Market: Distribution by Leading Players, 2018-2023 (USD Billion)

List of Figures

  • Figure 2.1 Research Methodology: Project Methodology
  • Figure 2.2 Research Methodology: Forecast Methodology
  • Figure 2.3 Research Methodology: Robust Quality Control
  • Figure 2.4 Research Methodology: Key Market Segmentation
  • Figure 3.1 Lessons Learnt from Past Recessions
  • Figure 4.1 Executive Summary: Overall Market Landscape
  • Figure 4.2 Executive Summary: Global Market for Big Data in Healthcare by Component, Type of Hardware, Type of Software, Type of Service, and Deployment Option
  • Figure 4.3 Executive Summary: Global Market for Big Data in Healthcare by Application Area, Healthcare Vertical, End User, Economic Status, Geography and Leading Players
  • Figure 5.1 Types of Big Data Analytics
  • Figure 5.2 Applications of Big Data in Healthcare
  • Figure 6.1 Big Data in Healthcare Service Providers: Distribution by Year of Establishment
  • Figure 6.2 Big Data in Healthcare Service Providers: Distribution by Company Size
  • Figure 6.3 Big Data in Healthcare Service Providers: Distribution by Location of Headquarters (Region)
  • Figure 6.4 Big Data in Healthcare Service Providers: Distribution by Location of Headquarters (Country)
  • Figure 6.5 Big Data in Healthcare Service Providers: Distribution by Type of Business Model
  • Figure 6.6 Big Data in Healthcare Service Providers: Distribution by Type of Offering
  • Figure 6.7 Big Data in Healthcare Service Providers: Type of Big Data Analytics Offered
  • Figure 6.8 Big Data in Healthcare Service Providers: Type of Big Data Storage Solution Offered
  • Figure 6.9 Big Data in Healthcare Service Providers: Distribution by Deployment Option
  • Figure 6.10 Big Data in Healthcare Service Providers: Distribution by Application Area
  • Figure 6.10 Big Data in Healthcare Service Providers: Distribution by End User
  • Figure 7.1 Big Data in Healthcare Service Providers: Distribution by Year of Establishment and Company Size
  • Figure 7.2 Big Data in Healthcare Service Providers: Distribution by Company Size and Location of Headquarters
  • Figure 7.3 Big Data in Healthcare Service Providers: Distribution by Type of Offering and Company Size
  • Figure 7.4 Big Data in Healthcare Service Providers: Distribution by Type of Big Data Analytics Offered and Application Area
  • Figure 7.5 Big Data in Healthcare Service Providers: Distribution by Company Size, Application Area and End User
  • Figure 8.1 Company Competitiveness Analysis: Small Service Providers based in North America
  • Figure 8.2 Company Competitiveness Analysis: Mid-sized Service Providers based in North America (I/II)
  • Figure 8.3 Company Competitiveness Analysis: Mid-sized Service Providers based in North America (II/II)
  • Figure 8.4 Company Competitiveness Analysis: Large Service Providers based in North America (I/II)
  • Figure 8.5 Company Competitiveness Analysis: Large Service Providers based in North America (II/II)
  • Figure 8.6 Company Competitiveness Analysis: Very Large Service Providers based in North America
  • Figure 8.7 Company Competitiveness Analysis: Small Service Providers based in Europe
  • Figure 8.8 Company Competitiveness Analysis: Mid-sized Service Providers based in Europe
  • Figure 8.9 Company Competitiveness Analysis: Large and Very Large Big Service Providers based in Europe
  • Figure 8.10 Company Competitiveness Analysis: Small Service Providers based in Asia and Rest of the World
  • Figure 8.11 Company Competitiveness Analysis: Mid-sized Service Providers based in Asia and Rest of the World (I/II)
  • Figure 8.12 Company Competitiveness Analysis: Mid-sized Service Providers based in Asia and Rest of the World (II/II)
  • Figure 8.13 Company Competitiveness Analysis: Large Big Service Providers based in Asia and Rest of the World
  • Figure 8.14 Company Competitiveness Analysis: Very Large Service Providers based in Asia and Rest of the World
  • Figure 9.1 Amazon Web Services: Annual Revenues, FY 2018 - 9M FY 2023 (USD Billion)
  • Figure 9.2 Microsoft: Annual Revenues, FY 2018 - Q1 FY 2024 (USD Billion)
  • Figure 9.3 Oracle: Annual Revenues, FY 2018 - Q1 FY 2024 (USD Billion)
  • Figure 9.4 Teradata: Annual Revenues, FY 2018 - 9M FY 2023 (USD Billion)
  • Figure 10.1 Accenture: Annual Revenues, FY 2018 - FY 2023 (USD Billion)
  • Figure 10.2 Keyrus: Annual Revenues, FY 2018 - H1 FY 2023 (USD Million)
  • Figure 11.1 Tata Elxsi: Annual Revenues, FY 2018 - H1 FY 2023 (INR Billion)
  • Figure 11.2 Kellton: Annual Revenues, FY 2018 - FY 2023 (INR Billion)
  • Figure 12.1 Big Data in Healthcare Market Drivers
  • Figure 12.2 Big Data in Healthcare Market Restraints
  • Figure 12.3 Big Data in Healthcare Market Opportunities
  • Figure 12.4 Big Data in Healthcare Market Challenges
  • Figure 13.1 Global Market for Big Data in Healthcare, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 13.2 Global Market for Big Data in Healthcare, Forecasted Estimates (2023-2035): Conservative Scenario (USD Billion)
  • Figure 13.3 Global Market for Big Data in Healthcare, Forecasted Estimates (2023-2035): Optimistic Scenario (USD Billion)
  • Figure 14.1 Big Data in Healthcare Market: Distribution by Component, 2018, 2023 and 2035 (USD Billion)
  • Figure 14.2 Big Data in Healthcare Market for Hardware, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 14.3 Big Data in Healthcare Market for Software, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 14.4 Big Data in Healthcare Market for Services, Historical Trends (2018-2022) and Forecasted Estimates
  • Figure 15.1 Big Data in Healthcare Market: Distribution by Type of Hardware, 2018, 2023 and 2035 (USD Billion)
  • Figure 15.2 Big Data in Healthcare Market for Storage Devices, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 15.3 Big Data in Healthcare Market for Servers, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 15.4 Big Data in Healthcare Market for Networking Infrastructure, Historical Trends (2018-2022) and Forecasted Estimates
  • Figure 16.1 Big Data in Healthcare Market: Distribution by Type of Software, 2018, 2023 and 2035 (USD Billion)
  • Figure 16.2 Big Data in Healthcare Market for Electronic Health Records, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 16.3 Big Data in Healthcare Market for Revenue Cycle Management Software, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 16.4 Big Data in Healthcare Market for Practice Management Software, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 16.5 Big Data in Healthcare Market for Workforce Management Software, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 17.1 Big Data in Healthcare Market: Distribution by Type of Service, 2018, 2023 and 2035 (USD Billion)
  • Figure 17.2 Big Data in Healthcare Market for Diagnostic Analytics, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 17.3 Big Data in Healthcare Market for Descriptive Analytics, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 17.4 Big Data in Healthcare Market for Predictive Analytics, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 17.5 Big Data in Healthcare Market for Prescriptive Analytics, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 18.1 Big Data in Healthcare Market: Distribution by Deployment Option, 2018, 2023 and 2035 (USD Billion)
  • Figure 18.2 Big Data in Healthcare Market for Cloud-based Deployment, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 18.3 Big Data in Healthcare Market for On-premises Deployment, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 19.1 Big Data in Healthcare Market: Distribution by Application Area, 2018, 2023 and 2035
  • Figure 19.2 Big Data in Healthcare Market for Operational Management, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 19.3 Big Data in Healthcare Market for Clinical Data Management, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 19.4 Big Data in Healthcare Market for Financial Management, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 19.5 Big Data in Healthcare Market for Population Health Management, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 20.1 Big Data in Healthcare Market: Distribution by Healthcare Vertical, 2018, 2023 and 2035
  • Figure 20.2 Big Data in Healthcare Market for Healthcare Services, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 20.3 Big Data in Healthcare Market for Pharmaceuticals, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 20.4 Big Data in Healthcare Market for Medical Devices, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 20.5 Big Data in Healthcare Market for Other Verticals, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 21.1 Big Data in Healthcare Market: Distribution by End User, 2018, 2023 and 2035 (USD Billion)
  • Figure 21.2 Big Data in Healthcare Market for Hospitals, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 21.3 Big Data in Healthcare Market for Health Insurance Agencies, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 21.4 Big Data in Healthcare Market for Clinics, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 21.5 Big Data in Healthcare Market for Other End Users, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.1 Big Data in Healthcare Market: Distribution by Economic Status, 2018, 2023 and 2035
  • Figure 22.2 Big Data in Healthcare Market in High Income Countries, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.3 Big Data in Healthcare Market in the US, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.4 Big Data in Healthcare Market in Canada, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.5 Big Data in Healthcare Market in Germany, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.6 Big Data in Healthcare Market in the UK, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.7 Big Data in Healthcare Market in the UAE, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.8 Big Data in Healthcare Market in South Korea, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.9 Big Data in Healthcare Market in France, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.10 Big Data in Healthcare Market in Australia, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.11 Big Data in Healthcare Market in New Zealand, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.12 Big Data in Healthcare Market in Italy, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.13 Big Data in Healthcare Market in Saudi Arabia, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.14 Big Data in Healthcare Market in Nordic Countries, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.15 Big Data in Healthcare Market in Upper-Middle Income Countries, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.16 Big Data in Healthcare Market in China, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.17 Big Data in Healthcare Market in Russia, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.18 Big Data in Healthcare Market in Brazil, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.19 Big Data in Healthcare Market in Japan, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.20 Big Data in Healthcare Market in South Africa, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 22.21 Big Data in Healthcare Market in India, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 23.1 Big Data in Healthcare Market: Distribution by Geography, 2018, 2023 and 2035 (USD Billion)
  • Figure 23.2 Big Data in Healthcare Market in North America, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 23.3 Big Data in Healthcare Market in Europe, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 23.4 Big Data in Healthcare Market in Asia, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 23.5 Big Data in Healthcare Market in Middle East and North Africa, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 23.6 Big Data in Healthcare Market in Latin America, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 23.7 Big Data in Healthcare Market in Rest of the World, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035) (USD Billion)
  • Figure 24.1 Microsoft: Revenue Generated from Big Data in Healthcare Offerings, FY 2018 - FY 2023 (USD Billion)
  • Figure 24.2 Optum: Revenue Generated from Big Data in Healthcare Offerings, FY 2018 - FY 2023 (USD Billion)
  • Figure 24.3 IBM: Revenue Generated from Big Data in Healthcare Offerings, FY 2018 - FY 2023 (USD Billion)
  • Figure 24.4 Oracle: Revenue Generated from Big Data in Healthcare Offerings, FY 2018 - FY 2023 (USD Billion)
  • Figure 24.5 Allscripts: Revenue Generated from Big Data in Healthcare Offerings, FY 2018 - FY 2023 (USD Billion)
目次
Product Code: RA100475

Big Data in Healthcare Market, Trends and Forecasts (Global and Regional), Till 2035: Distribution by Component (Hardware, Services and Software), Type of Hardware (Storage Devices, Networking Infrastructure and Servers), Type of Software (Electronic Health Record, Practice Management Software, Revenue Cycle Management Software, and Workforce Management Software), and Type of Service (Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics), Deployment Option (Cloud-based and On-premises), Application Area (Clinical Data Management, Financial Management, Operational Management, and Population Health Management), Healthcare Vertical (Healthcare Services, Medical Devices, Pharmaceuticals, and Other Verticals), End User (Clinics, Health Insurance Agencies, Hospitals, and Other End Users), Economic Status (High Income Countries, Upper-Middle Income Countries, and Lower-Middle Income Countries), Geography (North America, Europe, Asia, Middle East and North Africa, Latin America and Rest of the World), and Leading Players: Industry Trends and Global Forecasts

The big data in healthcare market is valued at USD 67 billion in 2023 growing at a CAGR of 19% during the forecast period 2023-2035.

Big data in the healthcare sector encompasses a vast volume of unstructured data sourced from various outlets, including medical research publications, biometric data, electronic health records, the Internet of Medical Things (IoMT), social media, payer records, omics research, and data repositories. The integration of this heterogeneous and intricate unstructured data into conventional databases presents a significant challenge in terms of data organization and standardization, critical for ensuring interoperability and facilitating effective analysis. However, recent advancements in big data analytics tools, artificial intelligence (AI), and machine learning (ML) have transformed the conversion of healthcare big data into valuable and actionable insights. These technological advancements have revolutionized multiple facets of healthcare, facilitating data-driven decision-making, enhancing diagnostics, enabling personalized treatment modalities, and empowering patients through self-service options such as online portals, mobile applications, and wearable devices. Additionally, big data analytics tools play a pivotal role in expediting drug discovery and development processes within pharmaceutical research and development (R&D). Driven by the escalating demand for business intelligence solutions, the proliferation of unstructured data, and the growing emphasis on personalized medicine, the global market for big data in healthcare is positioned for sustained market growth throughout the forecast period.

Key Market Segments

Component

Hardware (Storage Devices, Servers, and Networking Infrastructure)

Software (Electronic Health Record, Practice Management Software, Revenue Cycle Management Software, and Workforce Management Software)

Services (Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics)

Deployment Option

Cloud-based

On-premises

Application Area

Clinical Data Management

Financial Management

Operational Management

Population Health Management

Healthcare Vertical

Healthcare Services

Medical Devices

Pharmaceuticals

Other Verticals

Economic Status

High Income Countries

Upper-Middle Income Countries

Lower-Middle Income Countries

End User

Clinics

Health Insurance Agencies

Hospitals

Other End Users

Geography

North America

Europe

Asia

Latin America

Middle East and North Africa

Rest of the World

Research Coverage:

The report studies the big data in health care market based on components, types of hardware, types of software, types of services, deployment options, application areas, healthcare verticals, end users, types of economy, key geographical regions and leading players.

The report assesses the potential advantages and obstacles within the market for those involved and offers information on the competitive environment for top players in the market.

The report forecasts the revenue of market segments with respect to five major regions

The report provides an overview of big data and its type, including structured data, unstructured data, and semi-structured data. In addition, the chapter discusses the various types of Big Data analytics services and how they can be used in the healthcare industry. Furthermore, the chapter looks ahead to the future of Big Data Analytics in the healthcare market, showing how big data analytics can transform the healthcare industry and provide business opportunities for service providers.

Comprehensive analysis of the current landscape of big data in healthcare service providers considering parameters such as establishment year, company size, location of headquarters, business model, type of offering, type of big data analytics offered, type of big data storage solution offered, deployment option, application area and end user.

A comprehensive examination, emphasizing current trends in the big data healthcare market using various representations, considering pertinent parameters like company size and headquarters location, company size and business model, type of offerings and headquarters location, type of big data storage solution provided and deployment options, type of big data analytics offered and application areas, as well as company size, application area, and end user.

Detailed company competitiveness evaluation of big data in healthcare service providers, considering supplier strength and portfolio strength in terms of number of offerings, type of big data analytics services offered, type of big data storage solution offered, deployment option, and end user.

Elaborate profiles of leading players and tabulated profiles of other prominent players, selected based on our proprietary company competitiveness, offering big data analytics solutions across various geographies. Each detailed profile includes an overview of the company (including establishment year, employee count, headquarters location, and leadership team), financial information (if available), big data analytics offerings and capabilities, recent developments, and a well-informed future outlook.

The report analyzes factors (such as drivers, restraints, opportunities, and challenges) affecting the market growth

Key Benefits of Buying this Report

The report offers market leaders and newcomers valuable insights into revenue estimations for both the overall market and its sub-segments.

Stakeholders can utilize the report to enhance their understanding of the competitive landscape, allowing for improved business positioning and more effective go-to-market strategies.

The report provides stakeholders with a pulse on the big data in healthcare market, furnishing them with essential information on significant market drivers, barriers, opportunities, and challenges.

Key Market Companies

Accenture

Akka Technologies

Altamira.ai

Amazon Web Services

Athena Global Technologies

atom Consultancy Services (ACS)

Avenga

Happiest Minds

InData Labs

Itransition

Kellton

Keyrus

Lutech

Microsoft

Nagarro

Nous Infosystems

NTT data

Oracle

Orange Mantra

Oxagile

Scalefocus

Softweb Solutions

Solix Technologies

Spindox

Tata Elxsi

Teradata

Trianz (formerly CBIG Consulting)

Trigyn Technologies

XenonStack

TABLE OF CONTENTS

1. PREFACE

  • 1.1. Introduction
  • 1.2. Market Share Insights
  • 1.3. Key Market Insights
  • 1.4. Report Coverage
  • 1.5. Key Questions Answered
  • 1.6. Chapter Outlines

2. RESEARCH METHODOLOGY

  • 2.1. Chapter Overview
  • 2.2. Research Assumptions
  • 2.3. Project Methodology
  • 2.4. Forecast Methodology
  • 2.5. Robust Quality Control
  • 2.6. Key Considerations
    • 2.6.1. Demographics
    • 2.6.2. Economic Factors
    • 2.6.3. Government Regulations
    • 2.6.4. Supply Chain
    • 2.6.5. COVID Impact / Related Factors
    • 2.6.6. Market Access
    • 2.6.7. Healthcare Policies
    • 2.6.8. Industry Consolidation
  • 2.7. Key Market Segmentations

3. ECONOMIC AND OTHER PROJECT SPECIFIC CONSIDERATIONS

  • 3.1. Chapter Overview
  • 3.2. Market Dynamics
    • 3.2.1. Time Period
      • 3.2.1.1. Historical Trends
      • 3.2.1.2. Current and Forecasted Estimates
    • 3.2.2. Currency Coverage
      • 3.2.2.1. Major Currencies Affecting the Market
      • 3.2.2.2. Impact of Currency Fluctuations on the Industry
    • 3.2.3. Foreign Exchange Impact
      • 3.2.3.1. Evaluation of Foreign Exchange Rates and Their Impact on Market
      • 3.2.3.2. Strategies for Mitigating Foreign Exchange Risk
    • 3.2.4. Recession
      • 3.2.4.1. Historical Analysis of Past Recessions and Lessons Learnt
      • 3.2.4.2. Assessment of Current Economic Conditions and Potential Impact on the Market
    • 3.2.5. Inflation
      • 3.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
      • 3.2.5.2. Potential Impact of Inflation on the Market Evolution

4. EXECUTIVE SUMMARY

  • 4.1. Chapter Overview

5. INTRODUCTION

  • 5.1. Chapter Overview
  • 5.2. Overview of Big Data
    • 5.2.1. Types of Big Data
      • 5.2.1.1. Structured Data
      • 5.2.1.2. Unstructured Data
      • 5.2.1.3. Semi-Structured Data
    • 5.2.2. Management and Storage of Big Data
  • 5.3. Big Data Analytics
    • 5.3.1. Types of Big Data Analytics
      • 5.3.1.1. Descriptive Analytics
      • 5.3.1.2. Diagnostic Analytics
      • 5.3.1.3. Predictive Analytics
      • 5.3.1.4. Prescriptive Analytics
  • 5.4. Applications of Big Data in Healthcare
  • 5.5. Future Perspective

6. OVERALL MARKET LANDSCAPE

  • 6.1. Chapter Overview
  • 6.2. Big Data in Healthcare Service Providers: Overall Market Landscape
  • 6.3. Analysis by Year of Establishment
  • 6.4. Analysis by Company Size
  • 6.5. Analysis by Location of Headquarters
  • 6.6. Analysis by Type of Business Model
  • 6.7. Analysis by Type of Offering
  • 6.8. Analysis by Type of Big Data Analytics Offered
  • 6.9. Analysis by Type of Big Data Storage Solution Offered
  • 6.10. Analysis by Deployment Option
  • 6.11. Analysis by Application Area
  • 6.12. Analysis by End User

7. KEY INSIGHTS

  • 7.1. Chapter Overview
  • 7.2. Big Data in Healthcare Service Providers: Key Insights
    • 7.2.1 Analysis by Year of Establishment and Company Size
    • 7.2.2. Analysis by Company Size and Location of Headquarters
    • 7.2.3. Analysis by Type of Offering and Company Size
    • 7.2.4. Analysis by Type of Big Data Analytics Offered and Application Area
    • 7.2.5. Analysis by Company Size, Application Area and End User

8. COMPANY COMPETITIVENSS ANALYSIS

  • 8.1. Chapter Overview
  • 8.2. Assumptions and Key Parameters
  • 8.3. Methodology
  • 8.4. Big Data in Healthcare Service Providers: Company Competitiveness Analysis
    • 8.4.1. Big Data in Healthcare Service Providers based in North America
      • 8.4.1.1. Small Service Providers based in North America
      • 8.4.1.2. Mid-sized Service Providers based in North America
      • 8.4.1.3. Large Service Providers based in North America
      • 8.4.1.4. Very LargeService Providers based in North America
    • 8.4.2. Big Data in Healthcare Service Providers based in Europe
      • 8.4.2.1. Small Service Providers based in Europe
      • 8.4.2.2. Mid-sized Service Providers based in Europe
      • 8.4.2.3. Large and Very Large Service Providers based in Europe
    • 8.4.3. Big Data in Healthcare Service Providers based in Asia and Rest of the World
      • 8.4.3.1. Small Service Providers based in Asia and Rest of the World
      • 8.4.3.2. Mid-sized Service Providers based in Asia and Rest of the World
      • 8.4.3.3. Large Service Providers based in Asia and Rest of the World
      • 8.4.3.4. Very Large Service Providers based in Asia and Rest of the World

9. COMPANY PROFILES: BIG DATA IN HEALTHCARE SERVICE PROVIDERS IN NORTH AMERICA

  • 9.1. Chapter Overview
  • 9.2. Detailed Company Profiles of Leading Players in North America
    • 9.2.1. Amazon Web Services
      • 9.2.1.1. Company Overview
      • 9.2.1.2. Financial Information
      • 9.2.1.3. Big Data Offerings and Capabilities
      • 9.2.1.4. Recent Developments and Future Outlook
    • 9.2.2. Microsoft
      • 9.2.2.1. Company Overview
      • 9.2.2.2. Financial Information
      • 9.2.2.3. Big Data Offerings and Capabilities
      • 9.2.2.4. Recent Developments and Future Outlook
    • 9.2.3. Oracle
      • 9.2.3.1. Company Overview
      • 9.2.3.2. Financial Information
      • 9.2.3.3. Big Data Offerings and Capabilities
      • 9.2.3.4. Recent Developments and Future Outlook
    • 9.2.4. Teradata
      • 9.2.4.1. Company Overview
      • 9.2.4.2. Financial Information
      • 9.2.4.3. Big Data Offerings and Capabilities
      • 9.2.4.4. Recent Developments and Future Outlook
  • 9.3. Short Company Profiles of Other Prominent Players in North America
    • 9.3.1 Itransition
      • 9.3.1.1. Company Overview
      • 9.3.1.2. Big Data Offerings and Capabilities
    • 9.3.2 Nous Infosystems
      • 9.3.2.1. Company Overview
      • 9.3.2.2. Big Data Offerings and Capabilities
    • 9.3.3 Oxagile
      • 9.3.3.1. Company Overview
      • 9.3.3.2. Big Data Offerings and Capabilities
    • 9.3.4 Softweb Solutions
      • 9.3.4.1. Company Overview
      • 9.3.4.2. Big Data Offerings and Capabilities
    • 9.3.5 Solix Technologies
      • 9.3.5.1. Company Overview
      • 9.3.5.2. Big Data Offerings and Capabilities
    • 9.3.6 Trianz (formerly CBIG Consulting)
      • 9.3.6.1. Company Overview
      • 9.3.6.2. Big Data Offerings and Capabilities

10. COMPANY PROFILES: BIG DATA IN HEALTHCARE SERVICE PROVIDERS IN EUROPE

  • 10.1. Chapter Overview
  • 10.2. Detailed Company Profiles of Leading Players in Europe
    • 10.2.1. Accenture
      • 10.2.1.1. Company Overview
      • 10.2.1.2. Financial Information
      • 10.2.1.3. Big Data Offerings and Capabilities
      • 10.2.1.4. Recent Developments and Future Outlook
    • 10.2.2. Keyrus
      • 10.2.2.1. Company Overview
      • 10.2.2.2. Financial Information
      • 10.2.2.3. Big Data Offerings and Capabilities
      • 10.2.2.4. Recent Developments and Future Outlook
  • 10.3. Short Company Profiles of Other Prominent Players in Europe
    • 10.3.1 Akka Technologies
      • 10.3.1.1. Company Overview
      • 10.3.1.2. Big Data Offerings and Capabilities
    • 10.3.2 Altamira.ai
      • 10.3.2.1. Company Overview
      • 10.3.2.2. Big Data Offerings and Capabilities
    • 10.3.3 atom Consultancy Services (ACS)
      • 10.3.3.1. Company Overview
      • 10.3.3.2. Big Data Offerings and Capabilities
    • 10.3.4 Avenga
      • 10.3.4.1. Company Overview
      • 10.3.4.2. Big Data Offerings and Capabilities
    • 10.3.5 Lutech
      • 10.3.5.1. Company Overview
      • 10.3.5.2. Big Data Offerings and Capabilities
    • 10.3.6 Nagarro
      • 10.3.6.1. Company Overview
      • 10.3.6.2. Big Data Offerings and Capabilities
    • 10.3.7 Scalefocus
      • 10.3.7.1. Company Overview
      • 10.3.7.2. Big Data Offerings and Capabilities
    • 10.3.8 Spindox
      • 10.3.8.1. Company Overview
      • 10.3.8.2. Big Data Offerings and Capabilities

11. COMPANY PROFILES: BIG DATA IN HEALTHCARE SERVICE PROVIDERS IN ASIA AND REST OF THE WORLD

  • 11.1. Chapter Overview
  • 11.2. Detailed Company Profiles of Leading Players in Asia and Rest of the World
    • 11.2.1. Tata Elxsi
      • 11.2.1.1. Company Overview
      • 11.2.1.2. Big Data Offerings and Capabilities
      • 11.2.1.3. Recent Developments and Future Outlook
    • 11.2.2. Kellton
      • 11.2.2.1. Company Overview
      • 11.2.2.2. Financial Information
      • 11.2.2.3. Big Data Offerings and Capabilities
      • 11.2.2.4. Recent Developments and Future Outlook
  • 11.3. Short Company Profiles of Other Prominent Players in Asia and Rest of the World
    • 11.3.1 Athena Global Technologies
      • 11.3.1.1. Company Overview
      • 11.3.1.2. Big Data Offerings and Capabilities
    • 11.3.2 Happiest Minds
      • 11.3.2.1. Company Overview
      • 11.3.2.2. Big Data Offerings and Capabilities
    • 11.3.3 InData Labs
      • 11.3.3.1. Company Overview
      • 11.3.3.2. Big Data Offerings and Capabilities
    • 11.3.4 NTT data
      • 11.3.4.1. Company Overview
      • 11.3.4.2. Big Data Offerings and Capabilities
    • 11.3.5 OrangeMantra
      • 11.3.5.1. Company Overview
      • 11.3.5.2. Big Data Offerings and Capabilities
    • 11.3.6 Trigyn Technologies
      • 11.3.6.1. Company Overview
      • 11.3.6.2. Big Data Offerings and Capabilities
    • 11.3.7 XenonStack
      • 11.3.7.1. Company Overview
      • 11.3.7.2. Big Data Offerings and Capabilities

12. MARKET IMPACT ANALYSIS: DRIVERS, RESTRAINTS, OPPORTUNITIES AND CHALLENGES

  • 12.1. Chapter Overview
  • 12.2. Market Drivers
  • 12.3. Market Restraints
  • 12.4. Market Opportunities
  • 12.5. Market Challenges
  • 12.6. Conclusion

13. GLOBAL BIG DATA IN HEALTHCARE MARKET

  • 13.1. Chapter Overview
  • 13.2. Key Assumptions and Methodology
  • 13.3. Global Big Data in Healthcare Market, Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 13.3.1. Scenario Analysis
      • 13.3.1.1. Conservative Scenario
      • 13.3.1.2. Optimistic Scenario
  • 13.4. Key Market Segmentations

14. BIG DATA IN HEALTHCARE MARKET, BY COMPONENT

  • 14.1. Chapter Overview
  • 14.2. Key Assumptions and Methodology
  • 14.3. Big Data in Healthcare Market: Distribution by Component, 2018, 2023 and 2035
    • 14.3.1. Big Data Hardware: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 14.3.2. Big Data Software: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 14.3.3. Big Data Services: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
  • 14.4. Data Triangulation and Validation

15. BIG DATA IN HEALTHCARE MARKET, BY TYPE OF HARDWARE

  • 15.1. Chapter Overview
  • 15.2. Key Assumptions and Methodology
  • 15.3. Big Data in Healthcare Market: Distribution by Type of Hardware, 2018, 2023 and 2035
    • 15.3.1. Storage Devices: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 15.3.2. Servers: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 15.3.3. Networking Infrastructure: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
  • 15.4. Data Triangulation and Validation

16. BIG DATA IN HEALTHCARE MARKET, BY TYPE OF SOFTWARE

  • 16.1. Chapter Overview
  • 16.2. Key Assumptions and Methodology
  • 16.3. Big Data in Healthcare Market: Distribution by Type of Software, 2018, 2023 and 2035
    • 16.3.1. Electronic Health Record: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 16.3.2. Revenue Cycle Management Software: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 16.3.3. Practice Management Software: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 16.3.4. Workforce Management Software: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
  • 16.4. Data Triangulation and Validation

17. BIG DATA IN HEALTHCARE MARKET, BY TYPE OF SERVICE

  • 17.1. Chapter Overview
  • 17.2. Key Assumptions and Methodology
  • 17.3. Big Data in Healthcare Market: Distribution by Type of Services, 2018, 2023 and 2035
    • 17.3.1. Diagnostic Analytics: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 17.3.2. Descriptive Analytics: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 17.3.3. Predictive Analytics: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 17.3.4. Prescriptive Analytics: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
  • 17.4. Data Triangulation and Validation

18. BIG DATA IN HEALTHCARE MARKET, BY DEPLOYMENT OPTION

  • 18.1. Chapter Overview
  • 18.2. Key Assumptions and Methodology
  • 18.3. Big Data in Healthcare Market: Distribution by Deployment Option, 2018, 2023 and 2035
    • 18.3.1. Cloud-based Deployment: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 18.3.2. On-premises Deployment: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
  • 18.4. Data Triangulation and Validation

19. BIG DATA IN HEALTHCARE MARKET, BY APPLICATION AREA

  • 19.1. Chapter Overview
  • 19.2. Key Assumptions and Methodology
  • 19.3. Big Data in Healthcare Market: Distribution by Application Area, 2018, 2023 and 2035
    • 19.3.1. Operational Management: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 19.3.2. Clinical Data Management: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 19.3.3. Financial Management: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 19.3.4. Population Health Management: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
  • 19.4. Data Triangulation and Validation

20. BIG DATA IN HEALTHCARE MARKET, BY HEALTHCARE VERTICAL

  • 20.1. Chapter Overview
  • 20.2. Key Assumptions and Methodology
  • 20.3. Big Data in Healthcare Market: Distribution by Healthcare Vertical, 2018, 2023 and 2035
    • 20.3.1. Healthcare Services: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 20.3.2. Pharmaceuticals: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 20.3.3. Medical Devices: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 20.3.4. Other Verticals: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
  • 20.4. Data Triangulation and Validation

21. BIG DATA IN HEALTHCARE MARKET, BY END USER

  • 21.1. Chapter Overview
  • 21.2. Key Assumptions and Methodology
  • 21.3. Big Data in Healthcare Market: Distribution by End User, 2018, 2023 and 2035
    • 21.3.1. Hospitals: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 21.3.2. Health Insurance Agencies: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 21.3.3. Clinics: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 21.3.4. Other End Users: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
  • 21.4. Data Triangulation and Validation

22. BIG DATA IN HEALTHCARE MARKET, BY ECONOMIC STATUS

  • 22.1. Chapter Overview
  • 22.2. Key Assumptions and Methodology
  • 22.3. Big Data in Healthcare Market: Distribution by Economic Status, 2018, 2023 and 2035
    • 22.3.1. High Income Countries: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.1. US: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.2. Canada: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.3. Germany: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.4. UK: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.5. UAE: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.6. South Korea: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.7. France: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.8. Australia: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.9. New Zealand: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.10. Italy: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.11. Saudi Arabia: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.1.11. Nordic Countries: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 22.3.2. Upper-Middle Income Countries: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.2.1. China: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.2.1. Russia: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.2.1. Brazil: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.2.1. Japan: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.2.1. South Africa: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 22.3.3. Lower-Middle Income Countries: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
      • 22.3.3.1. India: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
  • 22.4. Data Triangulation and Validation

23. BIG DATA IN HEALTHCARE MARKET, BY GEOGRAPHY

  • 23.1. Chapter Overview
  • 23.2. Key Assumptions and Methodology
  • 23.3. Big Data in Healthcare Market: Distribution by Geography, 2018, 2023 and 2035
    • 23.3.1. North America: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 23.3.2. Europe: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 23.3.3. Asia: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 23.3.4. Middle East and North Africa: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 23.3.5. Latin America: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
    • 23.3.6. Rest of the World: Historical Trends (2018-2022) and Forecasted Estimates (2023-2035)
  • 23.4. Data Triangulation and Validation

24. BIG DATA IN HEALTHCARE MARKET, REVENUE FORECAST OF LEADING PLAYERS

  • 24.1. Chapter Overview
  • 24.2. Key Assumptions and Methodology
  • 24.3. Microsoft: Revenue Generated from Big Data in Healthcare Offerings FY 2018 - FY 2023
  • 24.4. Optum: Revenue Generated from Big Data in Healthcare Offerings FY 2018 - FY 2023
  • 24.5. IBM: Revenue Generated from Big Data in Healthcare Offerings FY 2018 - FY 2023
  • 24.6. Oracle: Revenue Generated from Big Data in Healthcare Offerings FY 2018 - FY 2023
  • 24.7. Allscripts: Revenue Generated from Big Data in Healthcare Offerings FY 2018 - FY 2023

25. CONCLUSION

  • 25.1. Chapter Overview

26. EXECUTIVE INSIGHTS

  • 26.1. Chapter Overview
  • 26.2. Emorphis Technologies
    • 26.2.1. Company Snapshot
    • 26.2.2. Interview Transcript
  • 26.3. Estenda Solutions
    • 26.3.1. Company Snapshot
    • 26.3.2. Interview Transcript
  • 26.4. DataToBiz
    • 26.4.1. Company Snapshot
    • 26.4.2. Interview Transcript
  • 26.5. Growth Acceleration Partners
    • 26.5.1. Company Snapshot
    • 26.5.2. Interview Transcrip
  • 26.6. W2S Solutions
    • 26.6.1. Company Snapshot
    • 26.6.2. Interview Transcript
  • 26.7. OrangeMantra
    • 26.7.1. Company Snapshot
    • 26.7.2. Interview Transcript
  • 26.8. Soulpage IT Solutions
    • 26.8.1. Company Snapshot
    • 26.8.2. Interview Transcript
  • 26.9. TechMango
    • 26.9.1. Company Snapshot
    • 26.9.2. Interview Transcript
  • 26.10. Tata Elxsi
    • 26.10.1. Company Snapshot
    • 26.10.2. Interview Transcript
  • 26.11. OpenXcell
    • 26.11.1. Company Snapshot
    • 26.11.2. Interview Transcript
  • 26.12. ThirdEye Data
    • 26.12.1. Company Snapshot
    • 26.12.2. Interview Transcript
  • 26.13. NTT Data
    • 26.13.1. Company Snapshot
    • 26.13.2. Interview Transcript
  • 26.14. CodeRiders
    • 26.14.1. Company Snapshot
    • 26.14.2. Interview Transcript
  • 26.15. Xenon Stack
    • 26.15.1. Company Snapshot
    • 26.15.2. Interview Transcript

27. APPENDIX I: TABULATED DATA

28. APPENDIX II: LIST OF COMPANIES AND ORGANIZATIONS