Big Data in Healthcare Market

Publisher Roots Analysis

Published Feb 01, 2024

Length 331 Pages

SKU # ROAL18576015

Description

Big Data in Healthcare Market

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 ForecastsThe big data in healthcare market is expected to reach USD 67 billion by 2023 anticipated to grow at a CAGR of 19% during the forecast period 2023-2035.

Big data in healthcare sector utilizes a vast amount of unstructured data from various sources, including medical research publications, biometric data, electronic health records, the Internet of Medical Things (IoMT), social media, payer records, omics research, and data repositories. Integrating this diverse and complex data into traditional databases presents challenges in terms of organization and standardization, which are crucial for interoperability and effective analysis. However, recent advancements in big data analytics tools, artificial intelligence (AI), and machine learning (ML) have revolutionized the conversion of healthcare big data into valuable insights. These technological advancements have transformed various aspects of healthcare, enabling data-driven decision-making, improving diagnostics, enabling personalized treatment options, and empowering patients through self-service options such as online portals, mobile applications, and wearable devices. Moreover, big data analytics tools play a crucial role in accelerating drug discovery and development processes in pharmaceutical research and development (R&D). Fueled by the increasing demand for business intelligence solutions, the rise in unstructured data, and the focus on personalized medicine, the global market for big data in healthcare is poised for sustained growth in the foreseeable future.Report Coverage

The report comprehensively examines 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.

It thoroughly analyzes market influences such as drivers, restraints, opportunities, and challenges, while evaluating competitive landscapes for top players. Forecasts are provided for segment revenues across major regions.

The report offers an introduction to big data and its various types, including structured, unstructured, and semi-structured data. Additionally, it explores different types of big data analytics services and their applications in the healthcare industry. Moreover, the chapter discusses the future prospects of big data analytics in the healthcare sector, highlighting its transformative potential and business opportunities for service providers.

An in-depth analysis is provided on the current landscape of big data in healthcare service providers, considering factors such as establishment year, company size, headquarters location, business model, types of offerings, big data analytics and storage solutions provided, deployment options, application areas, and end users.

The report comprehensively examines the prevailing trends in the big data healthcare market through various representations, taking into account parameters like company size and headquarters location, business model and company size, types of offerings and headquarters location, big data storage solutions and deployment options, types of big data analytics services and application areas, as well as company size, application areas, and end users.

Detailed evaluations are conducted on the competitive strengths of big data in healthcare service providers, focusing on their supplier strength and portfolio breadth in terms of the number and types of offerings, big data analytics and storage solutions provided, deployment options, and target end users.

Elaborate profiles of leading players and concise profiles of other prominent players are presented, selected based on proprietary company competitiveness criteria, offering big data analytics solutions across different geographical regions. Each profile includes an overview of the company, financial information (if available), offerings and capabilities in big data analytics, recent developments, and a well-informed future outlook.

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

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

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