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Big Data Analytics in Healthcare Market Size, Share & Industry Trends Analysis Report By Component (Software and Services), By End User, By Analytics Type, By Application, By Deployment, By Regional Outlook and Forecast, 2023-2029

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    Report

  • 324 Pages
  • April 2023
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5806535
The Global Big Data Analytics in Healthcare Market size is expected to reach $130.2 billion by 2029, rising at a market growth of 19.7% CAGR during the forecast period.

Big data analytics in healthcare refers to the intricate process of poring over large amounts of data to unearth information like occult patterns, undiscovered connections, market trends, and customer preferences that may assist healthcare providers in making wise clinical and commercial decisions. Healthcare analytics is a vast field with many distinct topics, including clinical delivery, operational effectiveness, and personalized treatment.



Big data analytics also enhances population health, integrates performance modeling with financial & predictive care monitoring, and other processes to improve process-oriented expenditures in the healthcare sector. The growth of big data analytics in healthcare market is result of the rise in regulatory compliance in the healthcare sector, growing need for big data analytics solutions for managing population health, rising expenditures by healthcare providers on technically sophisticated solutions, and continuous growth in the production of an enormous amount of medical data in the form of biometric data, electronic health records (EHR), and sensor data.

The use of large and complex heterogeneous datasets, like biological data, electronic health record records, and various omics datasets, is required to apply big data analytics in healthcare. Data analytics utilized in the healthcare industry are in great demand owing to the need to manage a patient's medical records and analyze the regularity with which that patient may experience similar health issues. The aforementioned scenario benefits both the big data technology and service sectors since, once a technology is embraced in a specific industry, it absorbs all available choices for revenue generation. These reasons will increase the demand for big data analytics in healthcare during the projected period.

COVID-19 Impact Analysis

Big data analytics firms extended their services to the healthcare sector to accommodate the various needs of their clients. Additionally, covid-19 has resulted in a significant number of fatalities, making it necessary to comprehend the traits and behavior of this pandemic to control it. The market demand has been significantly impacted by using big data analytics to quickly analyze and identify a vast volume of healthcare data. The pandemic led to an increase in the use of EHR in both developed and developing nations, which will affect the market's growth.

Market Growth Factors

Increasing investments and government regulations

Hospitals are not the only businesses that use analytical platforms to acquire medical data from various studies, organize it, interpret it, look up past data, analyze it to spot trends and develop methods, tools, and technologies to get the best results. These data analytics platforms are also being used by policymakers to conduct data and model research to enhance judgments and policies connected to healthcare facilities and the delivery of care to patients. The American government has acted in this area, as evidenced by the HealthData.gov website, which compiles information from numerous government databases on topics including community health outcomes. These elements have caused the demand to increase during the anticipated period.

These services help in preventing fraudulent activities by increasing security

Healthcare enterprises are a prime focus for cyber attackers due to the abundance of confidential information they possess regarding their clientele. Studies indicate that many healthcare companies have experienced data breaches. In commerce, it is widely known that personal information holds significant value and profitability within the illicit market. Therefore, numerous enterprises utilize analytics to assist in mitigating security threats. The team detects any alterations in network activity or anomalous behaviors indicative of a potential cyber threat. Big data analytics in healthcare market is estimated to witness growth in the forecast period due to this.

Market Restraining Factors

Privacy and security concerns

The utilization of big data in the healthcare sector has a number of major drawbacks, one of which is loss of privacy. Monitoring patient data, organizing collected data, tracking medical assets & inventory, and presenting data on dashboards and reports are some of the applications of these big data technologies. The display of sensitive medical data, especially that of patients, infringes on privacy standards and casts a negative light on big data. The patient is denied absolute freedom because it gives doctors complete access to patient information from anywhere. As a result, during the projection period, demand for this service may decline due to such circumstances.

Analytics Type Outlook

Based on analytics type, the big data analytics in healthcare market is segmented into descriptive analytics, predictive analytics, prescriptive analytics and diagnostic analytics. In 2021, the descriptive analytics segment held the highest revenue share in big data analytics in healthcare market. Descriptive analytics was extensively used to examine historical data & patient histories to study the spread of the virus, which has been a significant factor in the segment's growth. Getting historical data and transforming it into actionable insights, descriptive analytics has proven to be a valuable method for comprehending what occurred.



The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.

Application Outlook

By application, the big data analytics in healthcare market is bifurcated into clinical analytics, financial analytics and operational analytics. In 2022, the financial analytics segment recorded a remarkable revenue share in big data analytics in healthcare market. The expansion of this market has been attributed to the healthcare institutions' and organizations' ongoing efforts to reduce treatment costs while providing better care to patients. Healthcare organizations use analytical tools for both descriptive & predictive analysis to deliver enhanced patient care, reduce overall operational costs, and minimize fraud in insurance claims.

End user Outlook

Based on end user, the big data analytics in healthcare market is categorized into hospitals & clinics, finance & insurance agencies, and research organizations. The finance & insurance agencies segment garnered a significant revenue share in the big data analytics in healthcare market in 2022. For many years, insurance businesses have been undergoing a digital transition. It has improved responsiveness, effectiveness, and accuracy in every division of insurance firms. The insurance industry benefits from advanced data and predictive analytics tools that enable data-driven business decisions



Deployment Outlook

Based on deployment, the big data analytics in healthcare market is segmented into cloud and on-premise. In 2022, the on-premise segment dominated the big data analytics in healthcare market with maximum revenue share. The significant market share of this segment is primarily because on-premises deployment enables end users to use solutions from several providers, allowing for customization to meet end-user needs. In addition, due to convenience and security, most institutions install software and instruments to store data on-site, leading to a significant market share for this kind of delivery.

Component Outlook

By component the big data analytics in healthcare market is divided into software and services. In 2022, the software segment held the highest revenue share in big data analytics in healthcare market. Massive amounts of clinical data have been generated due to the growing patient load on the healthcare system, the rise in disease prevalence, etc. Additionally, the market is growing due to the industry's unrelenting pressure to provide patients with better care, better outcomes, and more affordable treatments.

Regional Outlook

Region wise, the big data analytics in healthcare market is analyzed across North America, Europe, Asia Pacific and LAMEA. The North America region led the big data analytics in healthcare market by generating the highest revenue share in 2022. With the adoption of these platforms and the improvement of technical availability, the region now features cutting-edge medical facilities that have contributed to North America's market expansion. Hospitals and other businesses must now utilize analytics technologies owing to the rising prevalence of chronic diseases and the aging population. The presence of significant corporations on the market has also contributed to the astronomical income percentage.

The Cardinal Matrix - Big Data Analytics in Healthcare Market Competition Analysis



The major strategies followed by the market participants are Partnerships. Based on the Analysis presented in the Cardinal matrix; UnitedHealth Group, Inc. (Optum, Inc.) is the forerunner in the Big Data Analytics in Healthcare Market. Companies such as Hewlett Packard Enterprise Company, Cognizant Technology Solutions Corporation, and GE HealthCare Technologies, Inc. are some of the key innovators in Big Data Analytics in Healthcare Market.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Oracle Corporation (Cerner Corporation), Veradigm, Inc., GE HealthCare Technologies, Inc., IBM Corporation, Epic Systems Corporation, UnitedHealth Group, Inc. (Optum, Inc.), Cognizant Technology Solutions Corporation, KT Corporation, Hewlett Packard Enterprise Company, and Health Fidelity, Inc. (Edifecs, Inc.)

Strategies Deployed in Big Data Analytics in Healthcare Market

Partnerships, Collaborations and Agreements:

  • Nov-2022: GE Healthcare teamed up with MediView XR, a US-based med-tech company. The collaboration focuses on combining medical imaging and mixed reality solutions. The collaboration integrates MediView's competence in 3D augmented reality medical visualization, telecollaboration, surgical navigation and GE's data analytics, and digital infrastructure. Moreover, the collaboration with MediView reflects GE Healthcare's devotion to accelerating precision care.
  • Oct-2022: Cognizant extended its collaboration with Qualcomm Technologies, a UK-based provider of single-chip radio devices. The extended collaboration focuses on advancing enterprise digital transformation. The collaboration integrates Cognizant's competence in IoT, cloud, and data analytics and Qualcomm's expertise in 5G connectivity solutions, and AI to support clients across multiple industries' advanced digital transformation.
  • May-2022: GE Healthcare collaborated with Alliance Medical, a UK-based provider of medical scanning services. The collaboration focuses on enhancing productivity in the hospital's radiology departments through AI and data analytics. Through this collaboration, the company also aims at enhancing patient outcomes.
  • Mar-2022: Cognizant announced a collaboration with Microsoft, a US-based technology company. The collaboration focuses on offering digital health solutions to improve remote patient monitoring. The new solutions come with built-in analytics that enables healthcare providers to recognize warning signs, and gain patient insights. Moreover, through this collaboration, the company also provides solutions that intend to connect patients and healthcare providers and improve the quality of healthcare.
  • Oct-2021: IBM joined hands with Deloitte, a multinational professional services network. This collaboration aimed to introduce a new offering, DAPPER, which is an AI-enabled managed analytics solution. DAPPER's end-to-end capabilities would enable companies to gain confidence in the insights that their data offers through a secured, simple-to-consume managed service offering to resolve the challenges of adopting AI.
  • Aug-2021: IBM partnered with Cloudera, an American software company. Under this partnership, the companies would strengthen their joint development as well as go-to-market programs in order to bring the cutting-edge analytical potentials of IBM Cloud Pak for Data, a unified platform for AI and data, to the Cloudera Data Platform.
  • Aug-2021: GE Healthcare came into collaboration with AWS, a US-based provider of the cloud-based web platform. The collaboration involves providing healthcare providers and hospitals with cloud-based imaging solutions, clinical, and operational insights, and integrated data.

Product Launches and Product Expansions:

  • Dec-2022: Hewlett Packard Enterprise introduced new improvements to its HPE GreenLake platform. The new improvements are made in developer, analytics, and application services. New updates include improvement to consumption analytics, six workload-optimized instances, etc.
  • Nov-2022: IBM launched IBM Business Analytics Enterprise. The new product is a comprehensive suite that includes, budgeting, reporting, forecasting, planning, and dashboard capabilities, providing the user with a holistic view of data sources across the entire business.
  • Oct-2022: Oracle introduced Oracle Network Analytics Suite, a cloud-based analytics solutions offerings that integrate network function data and AI and ML. The new product supports the operators in making better and more informed, automated decisions. Further, the new product offering enables the operators to identify abnormalities that have the power to cause disastrous network function failures.
  • Sep-2022: Oracle added new features and improvements to its NetSuite Analytics Warehouse. The improvements are intended to enhance decision-making skills and enable the user to explore new revenue sources. The new features and updates benefit the user in multiple ways, advance time to insights, simplify data management, and many more.
  • Oct-2021: Allscripts (Veradigm) introduced guided scheduling, within Allscripts Practice Management. The new application is an AI-based scheduling application that leverages real-time data to advance providers' days. The new application can enhance the proper utilization of resources, and reduce the effect of schedule churn.
  • Sep-2021: HP launched HP Amplify Data Insights. The new offering is designed to provide data analytics tools to partners. The new product offering provides partners with an analytics dashboard, descriptive, prescriptive, and predictive insights, and in return, the partners have to opt-in on sharing certain data.

Mergers and Acquisitions:

  • Jan-2023: Hewlett Packard Enterprise acquired Pachyderm, a US-based operator of data engineering platforms. The addition of Pachyderm enables HPE to provide an integrated ML pipeline to advance customers' journeys. The addition of Pachyderm’s reproducible AI software adds value to HPE's already existing AI-at-scale offering, further advances AI, and enables exploring greater opportunities in multiple areas including, image, text, video analysis, generative AI, etc.
  • Oct-2022: UnitedHealth Group took over Change Healthcare, a US-based healthcare technology company. The combined company would simplify and unify administrative, payment processes, and core clinical. Further, this acquisition benefits the whole healthcare system through enhanced efficiency, and reduction in costs.
  • Jul-2021: IBM entered into an agreement to acquire Bluetab Solutions Group, an enterprise software, and technical services company. Through this acquisition, Bluetab would become a strategic part of IBM's data services consulting practice to improve its hybrid cloud and AI strategy.
  • Jul-2021: HPE took over Ampool, a US-based provider of data engineering platforms. The addition of Ampool advances HPE's Ezmeral analytics runtime, improves quality, etc. Additionally, the acquisition reflects HPE's focus and dedication towards developing an open-source-based IP-rich capability intended for the HPE Ezmeral software portfolio, to provide supreme quality analytics.
  • Apr-2021: Cognizant completed the acquisition of Servian, an Australia-based provider of data, analytics, AI, and cloud technology services. The addition of Servian broadens the acquiring company's digital transformation capabilities in New Zealand and Australia. Additionally, the combination of Cognizant's digital expertise and Servian's strengths would unlock the full power of their clients in Australia.

Scope of the Study

By Component

  • Software
  • Services

By End-user

  • Hospitals & Clinics
  • Finance & Insurance Agencies
  • Research Organizations

By Analytics Type

  • Descriptive Analytics
  • Predictive Analytics
  • Prescriptive Analytics
  • Diagnostic Analytics

By Application

  • Clinical Analytics
  • Financial Analytics
  • Operational Analytics

By Deployment

  • On-premise
  • Cloud

By Geography

  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players

List of Companies Profiled in the Report:

  • Oracle Corporation (Cerner Corporation)
  • Veradigm, Inc.
  • GE HealthCare Technologies, Inc.
  • IBM Corporation
  • Epic Systems Corporation
  • UnitedHealth Group, Inc. (Optum, Inc.)
  • Cognizant Technology Solutions Corporation
  • KT Corporation
  • Hewlett Packard Enterprise Company
  • Health Fidelity, Inc. (Edifecs, Inc.)

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Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Big Data Analytics in Healthcare Market, by Component
1.4.2 Global Big Data Analytics in Healthcare Market, by End User
1.4.3 Global Big Data Analytics in Healthcare Market, by Analytics Type
1.4.4 Global Big Data Analytics in Healthcare Market, by Application
1.4.5 Global Big Data Analytics in Healthcare Market, by Deployment
1.4.6 Global Big Data Analytics in Healthcare Market, by Geography
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition & Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Analyst's Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Market Share Analysis, 2021
3.4 Top Winning Strategies
3.4.1 Key Leading Strategies: Percentage Distribution (2019-2023)
3.4.2 Key Strategic Move: (Partnerships, Collaborations & Agreements: 2019, Jan-2022, Nov) Leading Players
Chapter 4. Global Big Data Analytics in Healthcare Market by Component
4.1 Global Software Market by Region
4.2 Global Services Market by Region
Chapter 5. Global Big Data Analytics in Healthcare Market by End User
5.1 Global Hospitals & Clinics Market by Region
5.2 Global Finance & Insurance Agencies Market by Region
5.3 Global Research Organizations Market by Region
Chapter 6. Global Big Data Analytics in Healthcare Market by Analytics Type
6.1 Global Descriptive Analytics Market by Region
6.2 Global Predictive Analytics Market by Region
6.3 Global Prescriptive Analytics Market by Region
6.4 Global Diagnostic Analytics Market by Region
Chapter 7. Global Big Data Analytics in Healthcare Market by Application
7.1 Global Clinical Analytics Market by Region
7.2 Global Financial Analytics Market by Region
7.3 Global Operational Analytics Market by Region
Chapter 8. Global Big Data Analytics in Healthcare Market by Deployment
8.1 Global On-premise Market by Region
8.2 Global Cloud Market by Region
Chapter 9. Global Big Data Analytics in Healthcare Market by Region
9.1 North America Big Data Analytics in Healthcare Market
9.1.1 North America Big Data Analytics in Healthcare Market by Component
9.1.1.1 North America Software Market by Country
9.1.1.2 North America Services Market by Country
9.1.2 North America Big Data Analytics in Healthcare Market by End User
9.1.2.1 North America Hospitals & Clinics Market by Country
9.1.2.2 North America Finance & Insurance Agencies Market by Country
9.1.2.3 North America Research Organizations Market by Country
9.1.3 North America Big Data Analytics in Healthcare Market by Analytics Type
9.1.3.1 North America Descriptive Analytics Market by Country
9.1.3.2 North America Predictive Analytics Market by Country
9.1.3.3 North America Prescriptive Analytics Market by Country
9.1.3.4 North America Diagnostic Analytics Market by Country
9.1.4 North America Big Data Analytics in Healthcare Market by Application
9.1.4.1 North America Clinical Analytics Market by Country
9.1.4.2 North America Financial Analytics Market by Country
9.1.4.3 North America Operational Analytics Market by Country
9.1.5 North America Big Data Analytics in Healthcare Market by Deployment
9.1.5.1 North America On-premise Market by Country
9.1.5.2 North America Cloud Market by Country
9.1.6 North America Big Data Analytics in Healthcare Market by Country
9.1.6.1 US Big Data Analytics in Healthcare Market
9.1.6.1.1 US Big Data Analytics in Healthcare Market by Component
9.1.6.1.2 US Big Data Analytics in Healthcare Market by End User
9.1.6.1.3 US Big Data Analytics in Healthcare Market by Analytics Type
9.1.6.1.4 US Big Data Analytics in Healthcare Market by Application
9.1.6.1.5 US Big Data Analytics in Healthcare Market by Deployment
9.1.6.2 Canada Big Data Analytics in Healthcare Market
9.1.6.2.1 Canada Big Data Analytics in Healthcare Market by Component
9.1.6.2.2 Canada Big Data Analytics in Healthcare Market by End User
9.1.6.2.3 Canada Big Data Analytics in Healthcare Market by Analytics Type
9.1.6.2.4 Canada Big Data Analytics in Healthcare Market by Application
9.1.6.2.5 Canada Big Data Analytics in Healthcare Market by Deployment
9.1.6.3 Mexico Big Data Analytics in Healthcare Market
9.1.6.3.1 Mexico Big Data Analytics in Healthcare Market by Component
9.1.6.3.2 Mexico Big Data Analytics in Healthcare Market by End User
9.1.6.3.3 Mexico Big Data Analytics in Healthcare Market by Analytics Type
9.1.6.3.4 Mexico Big Data Analytics in Healthcare Market by Application
9.1.6.3.5 Mexico Big Data Analytics in Healthcare Market by Deployment
9.1.6.4 Rest of North America Big Data Analytics in Healthcare Market
9.1.6.4.1 Rest of North America Big Data Analytics in Healthcare Market by Component
9.1.6.4.2 Rest of North America Big Data Analytics in Healthcare Market by End User
9.1.6.4.3 Rest of North America Big Data Analytics in Healthcare Market by Analytics Type
9.1.6.4.4 Rest of North America Big Data Analytics in Healthcare Market by Application
9.1.6.4.5 Rest of North America Big Data Analytics in Healthcare Market by Deployment
9.2 Europe Big Data Analytics in Healthcare Market
9.2.1 Europe Big Data Analytics in Healthcare Market by Component
9.2.1.1 Europe Software Market by Country
9.2.1.2 Europe Services Market by Country
9.2.2 Europe Big Data Analytics in Healthcare Market by End User
9.2.2.1 Europe Hospitals & Clinics Market by Country
9.2.2.2 Europe Finance & Insurance Agencies Market by Country
9.2.2.3 Europe Research Organizations Market by Country
9.2.3 Europe Big Data Analytics in Healthcare Market by Analytics Type
9.2.3.1 Europe Descriptive Analytics Market by Country
9.2.3.2 Europe Predictive Analytics Market by Country
9.2.3.3 Europe Prescriptive Analytics Market by Country
9.2.3.4 Europe Diagnostic Analytics Market by Country
9.2.4 Europe Big Data Analytics in Healthcare Market by Application
9.2.4.1 Europe Clinical Analytics Market by Country
9.2.4.2 Europe Financial Analytics Market by Country
9.2.4.3 Europe Operational Analytics Market by Country
9.2.5 Europe Big Data Analytics in Healthcare Market by Deployment
9.2.5.1 Europe On-premise Market by Country
9.2.5.2 Europe Cloud Market by Country
9.2.6 Europe Big Data Analytics in Healthcare Market by Country
9.2.6.1 Germany Big Data Analytics in Healthcare Market
9.2.6.1.1 Germany Big Data Analytics in Healthcare Market by Component
9.2.6.1.2 Germany Big Data Analytics in Healthcare Market by End User
9.2.6.1.3 Germany Big Data Analytics in Healthcare Market by Analytics Type
9.2.6.1.4 Germany Big Data Analytics in Healthcare Market by Application
9.2.6.1.5 Germany Big Data Analytics in Healthcare Market by Deployment
9.2.6.2 UK Big Data Analytics in Healthcare Market
9.2.6.2.1 UK Big Data Analytics in Healthcare Market by Component
9.2.6.2.2 UK Big Data Analytics in Healthcare Market by End User
9.2.6.2.3 UK Big Data Analytics in Healthcare Market by Analytics Type
9.2.6.2.4 UK Big Data Analytics in Healthcare Market by Application
9.2.6.2.5 UK Big Data Analytics in Healthcare Market by Deployment
9.2.6.3 France Big Data Analytics in Healthcare Market
9.2.6.3.1 France Big Data Analytics in Healthcare Market by Component
9.2.6.3.2 France Big Data Analytics in Healthcare Market by End User
9.2.6.3.3 France Big Data Analytics in Healthcare Market by Analytics Type
9.2.6.3.4 France Big Data Analytics in Healthcare Market by Application
9.2.6.3.5 France Big Data Analytics in Healthcare Market by Deployment
9.2.6.4 Russia Big Data Analytics in Healthcare Market
9.2.6.4.1 Russia Big Data Analytics in Healthcare Market by Component
9.2.6.4.2 Russia Big Data Analytics in Healthcare Market by End User
9.2.6.4.3 Russia Big Data Analytics in Healthcare Market by Analytics Type
9.2.6.4.4 Russia Big Data Analytics in Healthcare Market by Application
9.2.6.4.5 Russia Big Data Analytics in Healthcare Market by Deployment
9.2.6.5 Spain Big Data Analytics in Healthcare Market
9.2.6.5.1 Spain Big Data Analytics in Healthcare Market by Component
9.2.6.5.2 Spain Big Data Analytics in Healthcare Market by End User
9.2.6.5.3 Spain Big Data Analytics in Healthcare Market by Analytics Type
9.2.6.5.4 Spain Big Data Analytics in Healthcare Market by Application
9.2.6.5.5 Spain Big Data Analytics in Healthcare Market by Deployment
9.2.6.6 Italy Big Data Analytics in Healthcare Market
9.2.6.6.1 Italy Big Data Analytics in Healthcare Market by Component
9.2.6.6.2 Italy Big Data Analytics in Healthcare Market by End User
9.2.6.6.3 Italy Big Data Analytics in Healthcare Market by Analytics Type
9.2.6.6.4 Italy Big Data Analytics in Healthcare Market by Application
9.2.6.6.5 Italy Big Data Analytics in Healthcare Market by Deployment
9.2.6.7 Rest of Europe Big Data Analytics in Healthcare Market
9.2.6.7.1 Rest of Europe Big Data Analytics in Healthcare Market by Component
9.2.6.7.2 Rest of Europe Big Data Analytics in Healthcare Market by End User
9.2.6.7.3 Rest of Europe Big Data Analytics in Healthcare Market by Analytics Type
9.2.6.7.4 Rest of Europe Big Data Analytics in Healthcare Market by Application
9.2.6.7.5 Rest of Europe Big Data Analytics in Healthcare Market by Deployment
9.3 Asia Pacific Big Data Analytics in Healthcare Market
9.3.1 Asia Pacific Big Data Analytics in Healthcare Market by Component
9.3.1.1 Asia Pacific Software Market by Country
9.3.1.2 Asia Pacific Services Market by Country
9.3.2 Asia Pacific Big Data Analytics in Healthcare Market by End User
9.3.2.1 Asia Pacific Hospitals & Clinics Market by Country
9.3.2.2 Asia Pacific Finance & Insurance Agencies Market by Country
9.3.2.3 Asia Pacific Research Organizations Market by Country
9.3.3 Asia Pacific Big Data Analytics in Healthcare Market by Analytics Type
9.3.3.1 Asia Pacific Descriptive Analytics Market by Country
9.3.3.2 Asia Pacific Predictive Analytics Market by Country
9.3.3.3 Asia Pacific Prescriptive Analytics Market by Country
9.3.3.4 Asia Pacific Diagnostic Analytics Market by Country
9.3.4 Asia Pacific Big Data Analytics in Healthcare Market by Application
9.3.4.1 Asia Pacific Clinical Analytics Market by Country
9.3.4.2 Asia Pacific Financial Analytics Market by Country
9.3.4.3 Asia Pacific Operational Analytics Market by Country
9.3.5 Asia Pacific Big Data Analytics in Healthcare Market by Deployment
9.3.5.1 Asia Pacific On-premise Market by Country
9.3.5.2 Asia Pacific Cloud Market by Country
9.3.6 Asia Pacific Big Data Analytics in Healthcare Market by Country
9.3.6.1 China Big Data Analytics in Healthcare Market
9.3.6.1.1 China Big Data Analytics in Healthcare Market by Component
9.3.6.1.2 China Big Data Analytics in Healthcare Market by End User
9.3.6.1.3 China Big Data Analytics in Healthcare Market by Analytics Type
9.3.6.1.4 China Big Data Analytics in Healthcare Market by Application
9.3.6.1.5 China Big Data Analytics in Healthcare Market by Deployment
9.3.6.2 Japan Big Data Analytics in Healthcare Market
9.3.6.2.1 Japan Big Data Analytics in Healthcare Market by Component
9.3.6.2.2 Japan Big Data Analytics in Healthcare Market by End User
9.3.6.2.3 Japan Big Data Analytics in Healthcare Market by Analytics Type
9.3.6.2.4 Japan Big Data Analytics in Healthcare Market by Application
9.3.6.2.5 Japan Big Data Analytics in Healthcare Market by Deployment
9.3.6.3 India Big Data Analytics in Healthcare Market
9.3.6.3.1 India Big Data Analytics in Healthcare Market by Component
9.3.6.3.2 India Big Data Analytics in Healthcare Market by End User
9.3.6.3.3 India Big Data Analytics in Healthcare Market by Analytics Type
9.3.6.3.4 India Big Data Analytics in Healthcare Market by Application
9.3.6.3.5 India Big Data Analytics in Healthcare Market by Deployment
9.3.6.4 South Korea Big Data Analytics in Healthcare Market
9.3.6.4.1 South Korea Big Data Analytics in Healthcare Market by Component
9.3.6.4.2 South Korea Big Data Analytics in Healthcare Market by End User
9.3.6.4.3 South Korea Big Data Analytics in Healthcare Market by Analytics Type
9.3.6.4.4 South Korea Big Data Analytics in Healthcare Market by Application
9.3.6.4.5 South Korea Big Data Analytics in Healthcare Market by Deployment
9.3.6.5 Singapore Big Data Analytics in Healthcare Market
9.3.6.5.1 Singapore Big Data Analytics in Healthcare Market by Component
9.3.6.5.2 Singapore Big Data Analytics in Healthcare Market by End User
9.3.6.5.3 Singapore Big Data Analytics in Healthcare Market by Analytics Type
9.3.6.5.4 Singapore Big Data Analytics in Healthcare Market by Application
9.3.6.5.5 Singapore Big Data Analytics in Healthcare Market by Deployment
9.3.6.6 Malaysia Big Data Analytics in Healthcare Market
9.3.6.6.1 Malaysia Big Data Analytics in Healthcare Market by Component
9.3.6.6.2 Malaysia Big Data Analytics in Healthcare Market by End User
9.3.6.6.3 Malaysia Big Data Analytics in Healthcare Market by Analytics Type
9.3.6.6.4 Malaysia Big Data Analytics in Healthcare Market by Application
9.3.6.6.5 Malaysia Big Data Analytics in Healthcare Market by Deployment
9.3.6.7 Rest of Asia Pacific Big Data Analytics in Healthcare Market
9.3.6.7.1 Rest of Asia Pacific Big Data Analytics in Healthcare Market by Component
9.3.6.7.2 Rest of Asia Pacific Big Data Analytics in Healthcare Market by End User
9.3.6.7.3 Rest of Asia Pacific Big Data Analytics in Healthcare Market by Analytics Type
9.3.6.7.4 Rest of Asia Pacific Big Data Analytics in Healthcare Market by Application
9.3.6.7.5 Rest of Asia Pacific Big Data Analytics in Healthcare Market by Deployment
9.4 LAMEA Big Data Analytics in Healthcare Market
9.4.1 LAMEA Big Data Analytics in Healthcare Market by Component
9.4.1.1 LAMEA Software Market by Country
9.4.1.2 LAMEA Services Market by Country
9.4.2 LAMEA Big Data Analytics in Healthcare Market by End User
9.4.2.1 LAMEA Hospitals & Clinics Market by Country
9.4.2.2 LAMEA Finance & Insurance Agencies Market by Country
9.4.2.3 LAMEA Research Organizations Market by Country
9.4.3 LAMEA Big Data Analytics in Healthcare Market by Analytics Type
9.4.3.1 LAMEA Descriptive Analytics Market by Country
9.4.3.2 LAMEA Predictive Analytics Market by Country
9.4.3.3 LAMEA Prescriptive Analytics Market by Country
9.4.3.4 LAMEA Diagnostic Analytics Market by Country
9.4.4 LAMEA Big Data Analytics in Healthcare Market by Application
9.4.4.1 LAMEA Clinical Analytics Market by Country
9.4.4.2 LAMEA Financial Analytics Market by Country
9.4.4.3 LAMEA Operational Analytics Market by Country
9.4.5 LAMEA Big Data Analytics in Healthcare Market by Deployment
9.4.5.1 LAMEA On-premise Market by Country
9.4.5.2 LAMEA Cloud Market by Country
9.4.6 LAMEA Big Data Analytics in Healthcare Market by Country
9.4.6.1 Brazil Big Data Analytics in Healthcare Market
9.4.6.1.1 Brazil Big Data Analytics in Healthcare Market by Component
9.4.6.1.2 Brazil Big Data Analytics in Healthcare Market by End User
9.4.6.1.3 Brazil Big Data Analytics in Healthcare Market by Analytics Type
9.4.6.1.4 Brazil Big Data Analytics in Healthcare Market by Application
9.4.6.1.5 Brazil Big Data Analytics in Healthcare Market by Deployment
9.4.6.2 Argentina Big Data Analytics in Healthcare Market
9.4.6.2.1 Argentina Big Data Analytics in Healthcare Market by Component
9.4.6.2.2 Argentina Big Data Analytics in Healthcare Market by End User
9.4.6.2.3 Argentina Big Data Analytics in Healthcare Market by Analytics Type
9.4.6.2.4 Argentina Big Data Analytics in Healthcare Market by Application
9.4.6.2.5 Argentina Big Data Analytics in Healthcare Market by Deployment
9.4.6.3 UAE Big Data Analytics in Healthcare Market
9.4.6.3.1 UAE Big Data Analytics in Healthcare Market by Component
9.4.6.3.2 UAE Big Data Analytics in Healthcare Market by End User
9.4.6.3.3 UAE Big Data Analytics in Healthcare Market by Analytics Type
9.4.6.3.4 UAE Big Data Analytics in Healthcare Market by Application
9.4.6.3.5 UAE Big Data Analytics in Healthcare Market by Deployment
9.4.6.4 Saudi Arabia Big Data Analytics in Healthcare Market
9.4.6.4.1 Saudi Arabia Big Data Analytics in Healthcare Market by Component
9.4.6.4.2 Saudi Arabia Big Data Analytics in Healthcare Market by End User
9.4.6.4.3 Saudi Arabia Big Data Analytics in Healthcare Market by Analytics Type
9.4.6.4.4 Saudi Arabia Big Data Analytics in Healthcare Market by Application
9.4.6.4.5 Saudi Arabia Big Data Analytics in Healthcare Market by Deployment
9.4.6.5 South Africa Big Data Analytics in Healthcare Market
9.4.6.5.1 South Africa Big Data Analytics in Healthcare Market by Component
9.4.6.5.2 South Africa Big Data Analytics in Healthcare Market by End User
9.4.6.5.3 South Africa Big Data Analytics in Healthcare Market by Analytics Type
9.4.6.5.4 South Africa Big Data Analytics in Healthcare Market by Application
9.4.6.5.5 South Africa Big Data Analytics in Healthcare Market by Deployment
9.4.6.6 Nigeria Big Data Analytics in Healthcare Market
9.4.6.6.1 Nigeria Big Data Analytics in Healthcare Market by Component
9.4.6.6.2 Nigeria Big Data Analytics in Healthcare Market by End User
9.4.6.6.3 Nigeria Big Data Analytics in Healthcare Market by Analytics Type
9.4.6.6.4 Nigeria Big Data Analytics in Healthcare Market by Application
9.4.6.6.5 Nigeria Big Data Analytics in Healthcare Market by Deployment
9.4.6.7 Rest of LAMEA Big Data Analytics in Healthcare Market
9.4.6.7.1 Rest of LAMEA Big Data Analytics in Healthcare Market by Component
9.4.6.7.2 Rest of LAMEA Big Data Analytics in Healthcare Market by End User
9.4.6.7.3 Rest of LAMEA Big Data Analytics in Healthcare Market by Analytics Type
9.4.6.7.4 Rest of LAMEA Big Data Analytics in Healthcare Market by Application
9.4.6.7.5 Rest of LAMEA Big Data Analytics in Healthcare Market by Deployment
Chapter 10. Company Profiles
10.1 Hewlett Packard Enterprise Company
10.1.1 Company Overview
10.1.2 Financial Analysis
10.1.3 Segmental and Regional Analysis
10.1.4 Research & Development Expense
10.1.5 Recent strategies and developments:
10.1.5.1 Product Launches and Product Expansions:
10.1.5.2 Acquisition and Mergers:
10.1.6 SWOT Analysis
10.2 IBM Corporation
10.2.1 Company Overview
10.2.2 Financial Analysis
10.2.3 Regional & Segmental Analysis
10.2.4 Research & Development Expenses
10.2.5 Recent strategies and developments:
10.2.5.2 Product Launches and Product Expansions:
10.2.5.3 Acquisition and Mergers:
10.2.6 SWOT Analysis
10.3 Cognizant Technology Solutions Corporation
10.3.1 Company overview
10.3.2 Financial Analysis
10.3.3 Segmental and Regional Analysis
10.3.4 Recent strategies and developments:
10.3.4.1 Partnerships, Collaborations, and Agreements:
10.3.4.2 Acquisition and Mergers:
10.3.5 SWOT Analysis
10.4 Oracle Corporation (Cerner Corporation)
10.4.1 Company Overview
10.4.2 Financial Analysis
10.4.3 Segmental and Regional Analysis
10.4.4 Research & Development Expense
10.4.5 Recent strategies and developments:
10.4.5.1 Product Launches and Product Expansions:
10.4.6 SWOT Analysis
10.5 Veradigm, Inc.
10.5.1 Company Overview
10.5.2 Financial Analysis
10.5.3 Regional & Segmental Analysis
10.5.4 Research & Development Expenses
10.5.5 Recent strategies and developments:
10.5.5.1 Product Launches and Product Expansions:
10.6 GE HealthCare Technologies, Inc.
10.6.1 Company Overview
10.6.2 Financial Analysis
10.6.3 Segmental and Regional Analysis
10.6.4 Research & Development Expenses
10.6.5 Recent strategies and developments:
10.6.5.1 Partnerships, Collaborations, and Agreements:
10.7 UnitedHealth Group, Inc. (Optum, Inc.)
10.7.1 Company Overview
10.7.2 Financial Analysis
10.7.3 Segmental Analysis
10.7.4 Recent strategies and developments:
10.7.4.1 Acquisition and Mergers:
10.8 KT Corporation
10.8.1 Company Overview
10.8.2 Financial Analysis
10.8.3 Segmental Analysis
10.8.4 Research & Development Expenses
10.9 Health Fidelity, Inc. (Edifecs, Inc.)
10.9.1 Company Overview
10.9.2 Recent strategies and developments:
10.9.2.1 Partnerships, Collaborations, and Agreements:
10.10. Epic Systems Corporation
10.10.1 Company Overview

Companies Mentioned

  • Oracle Corporation (Cerner Corporation)
  • Veradigm, Inc.
  • GE HealthCare Technologies, Inc.
  • IBM Corporation
  • Epic Systems Corporation
  • UnitedHealth Group, Inc. (Optum, Inc.)
  • Cognizant Technology Solutions Corporation
  • KT Corporation
  • Hewlett Packard Enterprise Company
  • Health Fidelity, Inc. (Edifecs, Inc.)

Methodology

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