Global DataOps Platform- Market

DataOps Platform- Comprehensive Study by Type (Agile Development, DevOps, Others), Application (SME, Large Enterprise) Players and Region - Global Market Outlook to 2028

DataOps Platform- Market by XX Submarkets | Forecast Years 2023-2028  

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  • Summary
  • Market Segments
  • Table of Content
  • List of Table & Figures
  • Players Profiled
DataOps Platform- Market Scope
DataOps platforms act as command centers for DataOps. These solutions orchestrate people, processes, and technology to deliver a trusted data pipeline to their users. DataOps platforms assemble several types of data management software into an individual, integrated environment.DataOps can help organizations to improve their overall performance by automating tasks, improving communication and collaboration, establishing a more reliable and faster data pipeline, and providing easier access to archived data

AttributesDetails
Study Period2018-2028
Base Year2022
UnitValue (USD Million)
Key Companies ProfiledMicrosoft (US), IBM (US), Oracle (US), AWS (US), Informatica (US), Teradata (US), Wipro (India), Accenture (Ireland), SAS Institute (US), Hitachi Vantara (US), DataKitchen (US), Atlan (Singapore), Dataiku (US), Fosfor (India), Databricks (US), StreamSets (US), Talend (US), Collibra (US), Celonis (US), BMC Software (US), Saagie (France), Composable Analytics (US), Tengu.io (Belgium), Unravel Data (US), Monte Carlo Data (US), Census (US), RightData (US), Zaloni (US), Datafold (US), DataOps.live (UK), K2view (Israel)
CAGR%


The market analysis of the dataops platform market’s competitive landscape will include market competition examination, by company, its respective overview, business description, product portfolio, key financials, etc. We also include market probability scenarios, a PEST analysis, Porter’s Five Forces analysis, a supply-chain analysis, as well as market expansion strategies. Research Analyst at AMA estimates that United States Players will contribute to the maximum growth of Global DataOps Platform- market throughout the predicted period.

Microsoft (US), IBM (US), Oracle (US), AWS (US), Informatica (US), Teradata (US), Wipro (India), Accenture (Ireland), SAS Institute (US), Hitachi Vantara (US), DataKitchen (US), Atlan (Singapore), Dataiku (US), Fosfor (India), Databricks (US), StreamSets (US), Talend (US), Collibra (US), Celonis (US), BMC Software (US), Saagie (France), Composable Analytics (US), Tengu.io (Belgium), Unravel Data (US), Monte Carlo Data (US), Census (US), RightData (US), Zaloni (US), Datafold (US), DataOps.live (UK), K2view (Israel) are some of the key players that are part of study coverage.

About Approach
The research aims to propose a patent-based approach in searching for potential technology partners as a supporting tool for enabling open innovation. The study also proposes a systematic searching process of technology partners as a preliminary step to select the emerging and key players that are involved in implementing market estimations. While patent analysis is employed to overcome the aforementioned data- and process-related limitations, as expenses occurred in that technology allows us to estimate the market size by evolving segments as target market from the total available market.

Segmentation Overview
The study have segmented the market of Global DataOps Platform- market by Type , by Application (SME and Large Enterprise) and Region with country level break-up.

On the basis of geography, the market of DataOps Platform- has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, Australia, Rest of Asia-Pacific), Europe (Germany, France, Italy, United Kingdom, Netherlands, Rest of Europe), MEA (Middle East, Africa), North America (United States, Canada, Mexico). region held largest market share in the year 2022.

In 2020, Oracle launched Oracle Cloud Observability and Management Platform. It integrates newly introduced logging, log analytics, database management, app performance monitoring, operations insights, and service connector hub services with already-existing Oracle monitoring, notifications, events, functions, streaming, and operating system management features.


Market Growth Drivers:
The need for organizations to manage increasing amounts of data more efficiently and The need for real-time processing and analysis

Restraints:
Data security and privacy and High installation cost

Opportunities:
An increase in adoption of DataOps platforms in various industries

Key Target Audience
DataOps Platform Solutions, Association Platforms, Association Management Software Options and Others

Report Objectives / Segmentation Covered

By Type
  • Agile Development
  • DevOps
  • Others
By Application
  • SME
  • Large Enterprise
By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. The need for organizations to manage increasing amounts of data more efficiently
      • 3.2.2. The need for real-time processing and analysis
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global DataOps Platform-, by Type, Application and Region (value) (2017-2022)
    • 5.1. Introduction
    • 5.2. Global DataOps Platform- (Value)
      • 5.2.1. Global DataOps Platform- by: Type (Value)
        • 5.2.1.1. Agile Development
        • 5.2.1.2. DevOps
        • 5.2.1.3. Others
      • 5.2.2. Global DataOps Platform- by: Application (Value)
        • 5.2.2.1. SME
        • 5.2.2.2. Large Enterprise
      • 5.2.3. Global DataOps Platform- Region
        • 5.2.3.1. South America
          • 5.2.3.1.1. Brazil
          • 5.2.3.1.2. Argentina
          • 5.2.3.1.3. Rest of South America
        • 5.2.3.2. Asia Pacific
          • 5.2.3.2.1. China
          • 5.2.3.2.2. Japan
          • 5.2.3.2.3. India
          • 5.2.3.2.4. South Korea
          • 5.2.3.2.5. Australia
          • 5.2.3.2.6. Rest of Asia-Pacific
        • 5.2.3.3. Europe
          • 5.2.3.3.1. Germany
          • 5.2.3.3.2. France
          • 5.2.3.3.3. Italy
          • 5.2.3.3.4. United Kingdom
          • 5.2.3.3.5. Netherlands
          • 5.2.3.3.6. Rest of Europe
        • 5.2.3.4. MEA
          • 5.2.3.4.1. Middle East
          • 5.2.3.4.2. Africa
        • 5.2.3.5. North America
          • 5.2.3.5.1. United States
          • 5.2.3.5.2. Canada
          • 5.2.3.5.3. Mexico
  • 6. DataOps Platform-: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
    • 6.2. Peer Group Analysis (2022)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Microsoft (US), IBM (US), Oracle (US), AWS (US), Informatica (US), Teradata (US), Wipro (India), Accenture (Ireland), SAS Institute (US), Hitachi Vantara (US), DataKitchen (US), Atlan (Singapore), Dataiku (US), Fosfor (India), Databricks (US), StreamSets (US), Talend (US), Collibra (US), Celonis (US), BMC Software (US), Saagie (France), Composable Analytics (US), Tengu.io (Belgium), Unravel Data (US), Monte Carlo Data (US), Census (US), RightData (US), Zaloni (US), Datafold (US), DataOps.live (UK), K2view (Israel)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
  • 7. Global DataOps Platform- Sale, by Type, Application and Region (value) (2023-2028)
    • 7.1. Introduction
    • 7.2. Global DataOps Platform- (Value)
      • 7.2.1. Global DataOps Platform- by: Type (Value)
        • 7.2.1.1. Agile Development
        • 7.2.1.2. DevOps
        • 7.2.1.3. Others
      • 7.2.2. Global DataOps Platform- by: Application (Value)
        • 7.2.2.1. SME
        • 7.2.2.2. Large Enterprise
      • 7.2.3. Global DataOps Platform- Region
        • 7.2.3.1. South America
          • 7.2.3.1.1. Brazil
          • 7.2.3.1.2. Argentina
          • 7.2.3.1.3. Rest of South America
        • 7.2.3.2. Asia Pacific
          • 7.2.3.2.1. China
          • 7.2.3.2.2. Japan
          • 7.2.3.2.3. India
          • 7.2.3.2.4. South Korea
          • 7.2.3.2.5. Australia
          • 7.2.3.2.6. Rest of Asia-Pacific
        • 7.2.3.3. Europe
          • 7.2.3.3.1. Germany
          • 7.2.3.3.2. France
          • 7.2.3.3.3. Italy
          • 7.2.3.3.4. United Kingdom
          • 7.2.3.3.5. Netherlands
          • 7.2.3.3.6. Rest of Europe
        • 7.2.3.4. MEA
          • 7.2.3.4.1. Middle East
          • 7.2.3.4.2. Africa
        • 7.2.3.5. North America
          • 7.2.3.5.1. United States
          • 7.2.3.5.2. Canada
          • 7.2.3.5.3. Mexico
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. DataOps Platform-: by Type(USD Million)
  • Table 2. DataOps Platform- Agile Development , by Region USD Million (2017-2022)
  • Table 3. DataOps Platform- DevOps , by Region USD Million (2017-2022)
  • Table 4. DataOps Platform- Others , by Region USD Million (2017-2022)
  • Table 5. DataOps Platform-: by Application(USD Million)
  • Table 6. DataOps Platform- SME , by Region USD Million (2017-2022)
  • Table 7. DataOps Platform- Large Enterprise , by Region USD Million (2017-2022)
  • Table 8. South America DataOps Platform-, by Country USD Million (2017-2022)
  • Table 9. South America DataOps Platform-, by Type USD Million (2017-2022)
  • Table 10. South America DataOps Platform-, by Application USD Million (2017-2022)
  • Table 11. Brazil DataOps Platform-, by Type USD Million (2017-2022)
  • Table 12. Brazil DataOps Platform-, by Application USD Million (2017-2022)
  • Table 13. Argentina DataOps Platform-, by Type USD Million (2017-2022)
  • Table 14. Argentina DataOps Platform-, by Application USD Million (2017-2022)
  • Table 15. Rest of South America DataOps Platform-, by Type USD Million (2017-2022)
  • Table 16. Rest of South America DataOps Platform-, by Application USD Million (2017-2022)
  • Table 17. Asia Pacific DataOps Platform-, by Country USD Million (2017-2022)
  • Table 18. Asia Pacific DataOps Platform-, by Type USD Million (2017-2022)
  • Table 19. Asia Pacific DataOps Platform-, by Application USD Million (2017-2022)
  • Table 20. China DataOps Platform-, by Type USD Million (2017-2022)
  • Table 21. China DataOps Platform-, by Application USD Million (2017-2022)
  • Table 22. Japan DataOps Platform-, by Type USD Million (2017-2022)
  • Table 23. Japan DataOps Platform-, by Application USD Million (2017-2022)
  • Table 24. India DataOps Platform-, by Type USD Million (2017-2022)
  • Table 25. India DataOps Platform-, by Application USD Million (2017-2022)
  • Table 26. South Korea DataOps Platform-, by Type USD Million (2017-2022)
  • Table 27. South Korea DataOps Platform-, by Application USD Million (2017-2022)
  • Table 28. Australia DataOps Platform-, by Type USD Million (2017-2022)
  • Table 29. Australia DataOps Platform-, by Application USD Million (2017-2022)
  • Table 30. Rest of Asia-Pacific DataOps Platform-, by Type USD Million (2017-2022)
  • Table 31. Rest of Asia-Pacific DataOps Platform-, by Application USD Million (2017-2022)
  • Table 32. Europe DataOps Platform-, by Country USD Million (2017-2022)
  • Table 33. Europe DataOps Platform-, by Type USD Million (2017-2022)
  • Table 34. Europe DataOps Platform-, by Application USD Million (2017-2022)
  • Table 35. Germany DataOps Platform-, by Type USD Million (2017-2022)
  • Table 36. Germany DataOps Platform-, by Application USD Million (2017-2022)
  • Table 37. France DataOps Platform-, by Type USD Million (2017-2022)
  • Table 38. France DataOps Platform-, by Application USD Million (2017-2022)
  • Table 39. Italy DataOps Platform-, by Type USD Million (2017-2022)
  • Table 40. Italy DataOps Platform-, by Application USD Million (2017-2022)
  • Table 41. United Kingdom DataOps Platform-, by Type USD Million (2017-2022)
  • Table 42. United Kingdom DataOps Platform-, by Application USD Million (2017-2022)
  • Table 43. Netherlands DataOps Platform-, by Type USD Million (2017-2022)
  • Table 44. Netherlands DataOps Platform-, by Application USD Million (2017-2022)
  • Table 45. Rest of Europe DataOps Platform-, by Type USD Million (2017-2022)
  • Table 46. Rest of Europe DataOps Platform-, by Application USD Million (2017-2022)
  • Table 47. MEA DataOps Platform-, by Country USD Million (2017-2022)
  • Table 48. MEA DataOps Platform-, by Type USD Million (2017-2022)
  • Table 49. MEA DataOps Platform-, by Application USD Million (2017-2022)
  • Table 50. Middle East DataOps Platform-, by Type USD Million (2017-2022)
  • Table 51. Middle East DataOps Platform-, by Application USD Million (2017-2022)
  • Table 52. Africa DataOps Platform-, by Type USD Million (2017-2022)
  • Table 53. Africa DataOps Platform-, by Application USD Million (2017-2022)
  • Table 54. North America DataOps Platform-, by Country USD Million (2017-2022)
  • Table 55. North America DataOps Platform-, by Type USD Million (2017-2022)
  • Table 56. North America DataOps Platform-, by Application USD Million (2017-2022)
  • Table 57. United States DataOps Platform-, by Type USD Million (2017-2022)
  • Table 58. United States DataOps Platform-, by Application USD Million (2017-2022)
  • Table 59. Canada DataOps Platform-, by Type USD Million (2017-2022)
  • Table 60. Canada DataOps Platform-, by Application USD Million (2017-2022)
  • Table 61. Mexico DataOps Platform-, by Type USD Million (2017-2022)
  • Table 62. Mexico DataOps Platform-, by Application USD Million (2017-2022)
  • Table 63. Company Basic Information, Sales Area and Its Competitors
  • Table 64. DataOps Platform-: by Type(USD Million)
  • Table 65. DataOps Platform- Agile Development , by Region USD Million (2023-2028)
  • Table 66. DataOps Platform- DevOps , by Region USD Million (2023-2028)
  • Table 67. DataOps Platform- Others , by Region USD Million (2023-2028)
  • Table 68. DataOps Platform-: by Application(USD Million)
  • Table 69. DataOps Platform- SME , by Region USD Million (2023-2028)
  • Table 70. DataOps Platform- Large Enterprise , by Region USD Million (2023-2028)
  • Table 71. South America DataOps Platform-, by Country USD Million (2023-2028)
  • Table 72. South America DataOps Platform-, by Type USD Million (2023-2028)
  • Table 73. South America DataOps Platform-, by Application USD Million (2023-2028)
  • Table 74. Brazil DataOps Platform-, by Type USD Million (2023-2028)
  • Table 75. Brazil DataOps Platform-, by Application USD Million (2023-2028)
  • Table 76. Argentina DataOps Platform-, by Type USD Million (2023-2028)
  • Table 77. Argentina DataOps Platform-, by Application USD Million (2023-2028)
  • Table 78. Rest of South America DataOps Platform-, by Type USD Million (2023-2028)
  • Table 79. Rest of South America DataOps Platform-, by Application USD Million (2023-2028)
  • Table 80. Asia Pacific DataOps Platform-, by Country USD Million (2023-2028)
  • Table 81. Asia Pacific DataOps Platform-, by Type USD Million (2023-2028)
  • Table 82. Asia Pacific DataOps Platform-, by Application USD Million (2023-2028)
  • Table 83. China DataOps Platform-, by Type USD Million (2023-2028)
  • Table 84. China DataOps Platform-, by Application USD Million (2023-2028)
  • Table 85. Japan DataOps Platform-, by Type USD Million (2023-2028)
  • Table 86. Japan DataOps Platform-, by Application USD Million (2023-2028)
  • Table 87. India DataOps Platform-, by Type USD Million (2023-2028)
  • Table 88. India DataOps Platform-, by Application USD Million (2023-2028)
  • Table 89. South Korea DataOps Platform-, by Type USD Million (2023-2028)
  • Table 90. South Korea DataOps Platform-, by Application USD Million (2023-2028)
  • Table 91. Australia DataOps Platform-, by Type USD Million (2023-2028)
  • Table 92. Australia DataOps Platform-, by Application USD Million (2023-2028)
  • Table 93. Rest of Asia-Pacific DataOps Platform-, by Type USD Million (2023-2028)
  • Table 94. Rest of Asia-Pacific DataOps Platform-, by Application USD Million (2023-2028)
  • Table 95. Europe DataOps Platform-, by Country USD Million (2023-2028)
  • Table 96. Europe DataOps Platform-, by Type USD Million (2023-2028)
  • Table 97. Europe DataOps Platform-, by Application USD Million (2023-2028)
  • Table 98. Germany DataOps Platform-, by Type USD Million (2023-2028)
  • Table 99. Germany DataOps Platform-, by Application USD Million (2023-2028)
  • Table 100. France DataOps Platform-, by Type USD Million (2023-2028)
  • Table 101. France DataOps Platform-, by Application USD Million (2023-2028)
  • Table 102. Italy DataOps Platform-, by Type USD Million (2023-2028)
  • Table 103. Italy DataOps Platform-, by Application USD Million (2023-2028)
  • Table 104. United Kingdom DataOps Platform-, by Type USD Million (2023-2028)
  • Table 105. United Kingdom DataOps Platform-, by Application USD Million (2023-2028)
  • Table 106. Netherlands DataOps Platform-, by Type USD Million (2023-2028)
  • Table 107. Netherlands DataOps Platform-, by Application USD Million (2023-2028)
  • Table 108. Rest of Europe DataOps Platform-, by Type USD Million (2023-2028)
  • Table 109. Rest of Europe DataOps Platform-, by Application USD Million (2023-2028)
  • Table 110. MEA DataOps Platform-, by Country USD Million (2023-2028)
  • Table 111. MEA DataOps Platform-, by Type USD Million (2023-2028)
  • Table 112. MEA DataOps Platform-, by Application USD Million (2023-2028)
  • Table 113. Middle East DataOps Platform-, by Type USD Million (2023-2028)
  • Table 114. Middle East DataOps Platform-, by Application USD Million (2023-2028)
  • Table 115. Africa DataOps Platform-, by Type USD Million (2023-2028)
  • Table 116. Africa DataOps Platform-, by Application USD Million (2023-2028)
  • Table 117. North America DataOps Platform-, by Country USD Million (2023-2028)
  • Table 118. North America DataOps Platform-, by Type USD Million (2023-2028)
  • Table 119. North America DataOps Platform-, by Application USD Million (2023-2028)
  • Table 120. United States DataOps Platform-, by Type USD Million (2023-2028)
  • Table 121. United States DataOps Platform-, by Application USD Million (2023-2028)
  • Table 122. Canada DataOps Platform-, by Type USD Million (2023-2028)
  • Table 123. Canada DataOps Platform-, by Application USD Million (2023-2028)
  • Table 124. Mexico DataOps Platform-, by Type USD Million (2023-2028)
  • Table 125. Mexico DataOps Platform-, by Application USD Million (2023-2028)
  • Table 126. Research Programs/Design for This Report
  • Table 127. Key Data Information from Secondary Sources
  • Table 128. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global DataOps Platform-: by Type USD Million (2017-2022)
  • Figure 5. Global DataOps Platform-: by Application USD Million (2017-2022)
  • Figure 6. South America DataOps Platform- Share (%), by Country
  • Figure 7. Asia Pacific DataOps Platform- Share (%), by Country
  • Figure 8. Europe DataOps Platform- Share (%), by Country
  • Figure 9. MEA DataOps Platform- Share (%), by Country
  • Figure 10. North America DataOps Platform- Share (%), by Country
  • Figure 11. Global DataOps Platform- share by Players 2022 (%)
  • Figure 12. BCG Matrix for key Companies
  • Figure 13. Microsoft (US), IBM (US), Oracle (US), AWS (US), Informatica (US), Teradata (US), Wipro (India), Accenture (Ireland), SAS Institute (US), Hitachi Vantara (US), DataKitchen (US), Atlan (Singapore), Dataiku (US), Fosfor (India), Databricks (US), StreamSets (US), Talend (US), Collibra (US), Celonis (US), BMC Software (US), Saagie (France), Composable Analytics (US), Tengu.io (Belgium), Unravel Data (US), Monte Carlo Data (US), Census (US), RightData (US), Zaloni (US), Datafold (US), DataOps.live (UK), K2view (Israel) Revenue, Net Income and Gross profit
  • Figure 14. Microsoft (US), IBM (US), Oracle (US), AWS (US), Informatica (US), Teradata (US), Wipro (India), Accenture (Ireland), SAS Institute (US), Hitachi Vantara (US), DataKitchen (US), Atlan (Singapore), Dataiku (US), Fosfor (India), Databricks (US), StreamSets (US), Talend (US), Collibra (US), Celonis (US), BMC Software (US), Saagie (France), Composable Analytics (US), Tengu.io (Belgium), Unravel Data (US), Monte Carlo Data (US), Census (US), RightData (US), Zaloni (US), Datafold (US), DataOps.live (UK), K2view (Israel) Revenue: by Geography 2022
  • Figure 15. Global DataOps Platform-: by Type USD Million (2023-2028)
  • Figure 16. Global DataOps Platform-: by Application USD Million (2023-2028)
  • Figure 17. South America DataOps Platform- Share (%), by Country
  • Figure 18. Asia Pacific DataOps Platform- Share (%), by Country
  • Figure 19. Europe DataOps Platform- Share (%), by Country
  • Figure 20. MEA DataOps Platform- Share (%), by Country
  • Figure 21. North America DataOps Platform- Share (%), by Country
List of companies from research coverage that are profiled in the study
  • Microsoft (US), IBM (US), Oracle (US), AWS (US), Informatica (US), Teradata (US), Wipro (India), Accenture (Ireland), SAS Institute (US), Hitachi Vantara (US), DataKitchen (US), Atlan (Singapore), Dataiku (US), Fosfor (India), Databricks (US), StreamSets (US), Talend (US), Collibra (US), Celonis (US), BMC Software (US), Saagie (France), Composable Analytics (US), Tengu.io (Belgium), Unravel Data (US), Monte Carlo Data (US), Census (US), RightData (US), Zaloni (US), Datafold (US), DataOps.live (UK), K2view (Israel)
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May 2023 229 Pages 75 Tables Base Year: 2022 Coverage: 15+ Companies; 18 Countries

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Frequently Asked Questions (FAQ):

The key segments that are playing vital role in DataOps Platform- Market are by type [Agile Development, DevOps and Others], by end use application [SME and Large Enterprise].
The DataOps Platform- Market is gaining popularity and expected to see strong valuation by 2028.
  • The need for organizations to manage increasing amounts of data more efficiently
  • The need for real-time processing and analysis

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