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Published on: Sep 2022 | From USD $2900 | Published By: QY RESEARCH | Number Of Pages: 121
Report Scope
This latest report researches the industry structure, revenue and gross margin. Major playersÕ headquarters, market shares, industry ranking and profiles are presented. The primary and secondary research is done in order to access up-to-date government regulations, market information and industry data. Data were collected from the Data Science and Machine-Learning Platforms companies, distributors, end users, industry associations, governments' industry bureaus, industry publications, industry experts, third party database, and our in-house databases.
This report also includes a discussion of the major players across each regional Data Science and Machine-Learning Platforms market. Further, it explains the major drivers and regional dynamics of the global Data Science and Machine-Learning Platforms market and current trends within the industry.
Key Companies Covered
In this section of the report, the researchers have done a comprehensive analysis of the prominent players operating and the strategies they are focusing on to combat the intense competition. Company profiles and market share analysis of the prominent players are also provided in this section. Additionally, the specialists have done an all-encompassing analysis of each player. They have also provided reliable revenue, market share and rank data of the companies for the period 2017-2022. With the assistance of this report, key players, stakeholders, and other participants will be able to stay abreast of the recent and upcoming developments in the business, further enabling them to make efficient choices. Mentioned below are the prime players taken into account in this research report:
SAS
Alteryx
IBM
RapidMiner
KNIME
Microsoft
Dataiku
Databricks
TIBCO Software
MathWorks
H20.ai
Anaconda
SAP
Google
Domino Data Lab
Angoss
Lexalytics
Rapid Insight
Market Segments
This report has explored the key segments: by Type and by Application. The lucrativeness and growth potential have been looked into by the industry experts in this report. This report also provides revenue forecast data by type and by application segments based on value for the period 2017-2028.
Data Science and Machine-Learning Platforms Segment by Type
Open Source Data Integration Tools
Cloud-based Data Integration Tools
Data Science and Machine-Learning Platforms Segment by Application
Small-Sized Enterprises
Medium-Sized Enterprise
Large Enterprises
Key Regions & Countries
This section of the report provides key insights regarding various regions and the key players operating in each region. Economic, social, environmental, technological, and political factors have been taken into consideration while assessing the growth of the particular region/country. The readers will also get their hands on the value data of each region and country for the period 2017-2028.
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Key Drivers & Barriers
High-impact rendering factors and drivers have been studied in this report to aid the readers to understand the general development. Moreover, the report includes restraints and challenges that may act as stumbling blocks on the way of the players. This will assist the users to be attentive and make informed decisions related to business. Specialists have also laid their focus on the upcoming business prospects.
COVID-19 and Russia-Ukraine War Influence Analysis
The readers in the section will understand how the Data Science and Machine-Learning Platforms market scenario changed across the globe during the pandemic, post-pandemic and Russia-Ukraine War. The study is done keeping in view the changes in aspects such as demand, consumption, transportation, consumer behavior, supply chain management, export and import, and production. The industry experts have also highlighted the key factors that will help create opportunities for players and stabilize the overall industry in the years to come.
Report Includes:
This report presents an overview of global market for Data Science and Machine-Learning Platforms market size. Analyses of the global market trends, with historic market revenue data for 2017 - 2021, estimates for 2022, and projections of CAGR through 2028.
This report researches the key producers of Data Science and Machine-Learning Platforms, also provides the revenue of main regions and countries. Highlights of the upcoming market potential for Data Science and Machine-Learning Platforms, and key regions/countries of focus to forecast this market into various segments and sub-segments. Country specific data and market value analysis for the U.S., Canada, Mexico, Brazil, China, Japan, South Korea, Southeast Asia, India, Germany, the U.K., Italy, Middle East, Africa, and Other Countries.
This report focuses on the Data Science and Machine-Learning Platforms revenue, market share and industry ranking of main companies, data from 2017 to 2022. Identification of the major stakeholders in the global Data Science and Machine-Learning Platforms market, and analysis of their competitive landscape and market positioning based on recent developments and segmental revenues. This report will help stakeholders to understand the competitive landscape and gain more insights and position their businesses and market strategies in a better way.
This report analyzes the segments data by type and by application, revenue, and growth rate, from 2017 to 2028. Evaluation and forecast the market size for Data Science and Machine-Learning Platforms revenue, projected growth trends, production technology, application and end-user industry.
Descriptive company profiles of the major global players, including SAS, Alteryx, IBM, RapidMiner, KNIME, Microsoft, Dataiku, Databricks and TIBCO Software, etc.
1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Data Science and Machine-Learning Platforms Market Size Growth Rate by Type: 2017 VS 2021 VS 2028
1.2.2 Open Source Data Integration Tools
1.2.3 Cloud-based Data Integration Tools
1.3 Market by Application
1.3.1 Global Data Science and Machine-Learning Platforms Market Growth Rate by Application: 2017 VS 2021 VS 2028
1.3.2 Small-Sized Enterprises
1.3.3 Medium-Sized Enterprise
1.3.4 Large Enterprises
1.4 Study Objectives
1.5 Years Considered
2 Market Perspective
2.1 Global Data Science and Machine-Learning Platforms Market Size (2017-2028)
2.2 Data Science and Machine-Learning Platforms Market Size across Key Geographies Worldwide: 2017 VS 2021 VS 2028
2.3 Global Data Science and Machine-Learning Platforms Market Size by Region (2017-2022)
2.4 Global Data Science and Machine-Learning Platforms Market Size Forecast by Region (2023-2028)
2.5 Global Top Data Science and Machine-Learning Platforms Countries Ranking by Market Size
3 Data Science and Machine-Learning Platforms Competitive by Company
3.1 Global Data Science and Machine-Learning Platforms Revenue by Players
3.1.1 Global Data Science and Machine-Learning Platforms Revenue by Players (2017-2022)
3.1.2 Global Data Science and Machine-Learning Platforms Market Share by Players (2017-2022)
3.2 Global Data Science and Machine-Learning Platforms Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Company Covered: Ranking by Data Science and Machine-Learning Platforms Revenue
3.4 Global Data Science and Machine-Learning Platforms Market Concentration Ratio
3.4.1 Global Data Science and Machine-Learning Platforms Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Data Science and Machine-Learning Platforms Revenue in 2021
3.5 Global Data Science and Machine-Learning Platforms Key Players Head office and Area Served
3.6 Key Players Data Science and Machine-Learning Platforms Product Solution and Service
3.7 Date of Enter into Data Science and Machine-Learning Platforms Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Global Data Science and Machine-Learning Platforms Breakdown Data by Type
4.1 Global Data Science and Machine-Learning Platforms Historic Revenue by Type (2017-2022)
4.2 Global Data Science and Machine-Learning Platforms Forecasted Revenue by Type (2023-2028)
5 Global Data Science and Machine-Learning Platforms Breakdown Data by Application
5.1 Global Data Science and Machine-Learning Platforms Historic Market Size by Application (2017-2022)
5.2 Global Data Science and Machine-Learning Platforms Forecasted Market Size by Application (2023-2028)
6 North America
6.1 North America Data Science and Machine-Learning Platforms Revenue by Company (2020-2022)
6.2 North America Data Science and Machine-Learning Platforms Revenue by Type (2017-2028)
6.3 North America Data Science and Machine-Learning Platforms Revenue by Application (2017-2028)
6.4 North America Data Science and Machine-Learning Platforms Revenue by Country (2017-2028)
6.4.1 U.S.
6.4.2 Canada
7 Europe
7.1 Europe Data Science and Machine-Learning Platforms Revenue by Company (2020-2022)
7.2 Europe Data Science and Machine-Learning Platforms Revenue by Type (2017-2028)
7.3 Europe Data Science and Machine-Learning Platforms Revenue by Application (2017-2028)
7.4 Europe Data Science and Machine-Learning Platforms Revenue by Country (2017-2028)
7.4.1 Germany
7.4.2 France
7.4.3 U.K.
7.4.4 Italy
7.4.5 Russia
8 Asia Pacific
8.1 Asia Pacific Data Science and Machine-Learning Platforms Revenue by Company (2020-2022)
8.2 Asia Pacific Data Science and Machine-Learning Platforms Revenue by Type (2017-2028)
8.3 Asia Pacific Data Science and Machine-Learning Platforms Revenue by Application (2017-2028)
8.4 Asia Pacific Data Science and Machine-Learning Platforms Revenue by Region (2017-2028)
8.4.1 China
8.4.2 Japan
8.4.3 South Korea
8.4.4 India
8.4.5 Australia
8.4.6 Taiwan
8.4.7 Indonesia
8.4.8 Thailand
8.4.9 Malaysia
8.4.10 Philippines
8.4.11 Vietnam
9 Latin America
9.1 Latin America Data Science and Machine-Learning Platforms Revenue by Company (2020-2022)
9.2 Latin America Data Science and Machine-Learning Platforms Revenue by Type (2017-2028)
9.3 Latin America Data Science and Machine-Learning Platforms Revenue by Application (2017-2028)
9.4 Latin America Data Science and Machine-Learning Platforms Revenue by Country (2017-2028)
9.4.1 Mexico
9.4.2 Brazil
9.4.3 Argentina
10 Middle East and Africa
10.1 Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Company (2020-2022)
10.2 Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Type (2017-2028)
10.3 Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Application (2017-2028)
10.4 Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Country (2017-2028)
10.4.1 Turkey
10.4.2 Saudi Arabia
10.4.3 UAE
11 Company Profiles
11.1 SAS
11.1.1 SAS Company Details
11.1.2 SAS Business Overview
11.1.3 SAS Data Science and Machine-Learning Platforms Products and Services
11.1.4 SAS Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.1.5 SAS Data Science and Machine-Learning Platforms SWOT Analysis
11.1.6 SAS Recent Developments
11.2 Alteryx
11.2.1 Alteryx Company Details
11.2.2 Alteryx Business Overview
11.2.3 Alteryx Data Science and Machine-Learning Platforms Products and Services
11.2.4 Alteryx Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.2.5 Alteryx Data Science and Machine-Learning Platforms SWOT Analysis
11.2.6 Alteryx Recent Developments
11.3 IBM
11.3.1 IBM Company Details
11.3.2 IBM Business Overview
11.3.3 IBM Data Science and Machine-Learning Platforms Products and Services
11.3.4 IBM Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.3.5 IBM Data Science and Machine-Learning Platforms SWOT Analysis
11.3.6 IBM Recent Developments
11.4 RapidMiner
11.4.1 RapidMiner Company Details
11.4.2 RapidMiner Business Overview
11.4.3 RapidMiner Data Science and Machine-Learning Platforms Products and Services
11.4.4 RapidMiner Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.4.5 RapidMiner Data Science and Machine-Learning Platforms SWOT Analysis
11.4.6 RapidMiner Recent Developments
11.5 KNIME
11.5.1 KNIME Company Details
11.5.2 KNIME Business Overview
11.5.3 KNIME Data Science and Machine-Learning Platforms Products and Services
11.5.4 KNIME Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.5.5 KNIME Data Science and Machine-Learning Platforms SWOT Analysis
11.5.6 KNIME Recent Developments
11.6 Microsoft
11.6.1 Microsoft Company Details
11.6.2 Microsoft Business Overview
11.6.3 Microsoft Data Science and Machine-Learning Platforms Products and Services
11.6.4 Microsoft Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.6.5 Microsoft Data Science and Machine-Learning Platforms SWOT Analysis
11.6.6 Microsoft Recent Developments
11.7 Dataiku
11.7.1 Dataiku Company Details
11.7.2 Dataiku Business Overview
11.7.3 Dataiku Data Science and Machine-Learning Platforms Products and Services
11.7.4 Dataiku Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.7.5 Dataiku Data Science and Machine-Learning Platforms SWOT Analysis
11.7.6 Dataiku Recent Developments
11.8 Databricks
11.8.1 Databricks Company Details
11.8.2 Databricks Business Overview
11.8.3 Databricks Data Science and Machine-Learning Platforms Products and Services
11.8.4 Databricks Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.8.5 Databricks Data Science and Machine-Learning Platforms SWOT Analysis
11.8.6 Databricks Recent Developments
11.9 TIBCO Software
11.9.1 TIBCO Software Company Details
11.9.2 TIBCO Software Business Overview
11.9.3 TIBCO Software Data Science and Machine-Learning Platforms Products and Services
11.9.4 TIBCO Software Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.9.5 TIBCO Software Data Science and Machine-Learning Platforms SWOT Analysis
11.9.6 TIBCO Software Recent Developments
11.10 MathWorks
11.10.1 MathWorks Company Details
11.10.2 MathWorks Business Overview
11.10.3 MathWorks Data Science and Machine-Learning Platforms Products and Services
11.10.4 MathWorks Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.10.5 MathWorks Data Science and Machine-Learning Platforms SWOT Analysis
11.10.6 MathWorks Recent Developments
11.11 H20.ai
11.11.1 H20.ai Company Details
11.11.2 H20.ai Business Overview
11.11.3 H20.ai Data Science and Machine-Learning Platforms Products and Services
11.11.4 H20.ai Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.11.5 H20.ai Recent Developments
11.12 Anaconda
11.12.1 Anaconda Company Details
11.12.2 Anaconda Business Overview
11.12.3 Anaconda Data Science and Machine-Learning Platforms Products and Services
11.12.4 Anaconda Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.12.5 Anaconda Recent Developments
11.13 SAP
11.13.1 SAP Company Details
11.13.2 SAP Business Overview
11.13.3 SAP Data Science and Machine-Learning Platforms Products and Services
11.13.4 SAP Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.13.5 SAP Recent Developments
11.14 Google
11.14.1 Google Company Details
11.14.2 Google Business Overview
11.14.3 Google Data Science and Machine-Learning Platforms Products and Services
11.14.4 Google Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.14.5 Google Recent Developments
11.15 Domino Data Lab
11.15.1 Domino Data Lab Company Details
11.15.2 Domino Data Lab Business Overview
11.15.3 Domino Data Lab Data Science and Machine-Learning Platforms Products and Services
11.15.4 Domino Data Lab Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.15.5 Domino Data Lab Recent Developments
11.16 Angoss
11.16.1 Angoss Company Details
11.16.2 Angoss Business Overview
11.16.3 Angoss Data Science and Machine-Learning Platforms Products and Services
11.16.4 Angoss Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.16.5 Angoss Recent Developments
11.17 Lexalytics
11.17.1 Lexalytics Company Details
11.17.2 Lexalytics Business Overview
11.17.3 Lexalytics Data Science and Machine-Learning Platforms Products and Services
11.17.4 Lexalytics Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.17.5 Lexalytics Recent Developments
11.18 Rapid Insight
11.18.1 Rapid Insight Company Details
11.18.2 Rapid Insight Business Overview
11.18.3 Rapid Insight Data Science and Machine-Learning Platforms Products and Services
11.18.4 Rapid Insight Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022)
11.18.5 Rapid Insight Recent Developments
12 Data Science and Machine-Learning Platforms Market Dynamics
12.1 Data Science and Machine-Learning Platforms Market Trends
12.2 Data Science and Machine-Learning Platforms Market Drivers
12.3 Data Science and Machine-Learning Platforms Market Challenges
12.4 Data Science and Machine-Learning Platforms Market Restraints
13 Research Findings and Conclusion
14 Appendix
14.1 Research Methodology
14.1.1 Methodology/Research Approach
14.1.2 Data Source
14.2 Author Details
List of Tables
Table 1. Global Data Science and Machine-Learning Platforms Market Size Growth Rate by Type (US$ Million), 2017 VS 2021 VS 2028
Table 2. Key Players of Open Source Data Integration Tools
Table 3. Key Players of Cloud-based Data Integration Tools
Table 4. Global Data Science and Machine-Learning Platforms Market Size Growth Rate by Application (US$ Million), 2017 VS 2021 VS 2028
Table 5. Global Data Science and Machine-Learning Platforms Market Size (US$ Million) by Region: 2017 VS 2021 VS 2028
Table 6. Global Data Science and Machine-Learning Platforms Revenue by Region (2017-2022) & (US$ Million)
Table 7. Global Data Science and Machine-Learning Platforms Revenue Market Share by Region (2017-2022)
Table 8. Global Data Science and Machine-Learning Platforms Revenue by Players (2017-2022) & (US$ Million)
Table 9. Global Data Science and Machine-Learning Platforms Market Share by Players (2017-2022)
Table 10. Global Top Data Science and Machine-Learning Platforms Players by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Data Science and Machine-Learning Platforms as of 2021)
Table 11. Ranking of Global Top Data Science and Machine-Learning Platforms Companies by Revenue (US$ Million) in 2021
Table 12. Global 5 Largest Players Market Share by Data Science and Machine-Learning Platforms Revenue (CR5 and HHI) & (2017-2022)
Table 13. Key Players Headquarters and Area Served
Table 14. Key Players Data Science and Machine-Learning Platforms Product Solution and Service
Table 15. Date of Key Manufacturers Enter into Data Science and Machine-Learning Platforms Market
Table 16. Mergers & Acquisitions, Expansion Plans
Table 17. Global Data Science and Machine-Learning Platforms Market Size by Type (2017-2022) & (US$ Million)
Table 18. Global Data Science and Machine-Learning Platforms Revenue Market Share by Type (2017-2022)
Table 19. Global Data Science and Machine-Learning Platforms Forecasted Market Size by Type (2023-2028) & (US$ Million)
Table 20. Global Data Science and Machine-Learning Platforms Revenue Market Share by Type (2023-2028)
Table 21. Global Data Science and Machine-Learning Platforms Market Size by Application (2017-2022) & (US$ Million)
Table 22. Global Data Science and Machine-Learning Platforms Revenue Market Share by Application (2017-2022)
Table 23. Global Data Science and Machine-Learning Platforms Forecasted Market Size by Application (2023-2028) & (US$ Million)
Table 24. Global Data Science and Machine-Learning Platforms Revenue Market Share by Application (2023-2028)
Table 25. North America Data Science and Machine-Learning Platforms Revenue by Company (2020-2022) & (US$ Million)
Table 26. North America Data Science and Machine-Learning Platforms Revenue by Type (2017-2022) & (US$ Million)
Table 27. North America Data Science and Machine-Learning Platforms Revenue by Type (2023-2028) & (US$ Million)
Table 28. North America Data Science and Machine-Learning Platforms Revenue by Application (2017-2022) & (US$ Million)
Table 29. North America Data Science and Machine-Learning Platforms Revenue by Application (2023-2028) & (US$ Million)
Table 30. North America Data Science and Machine-Learning Platforms Revenue by Country (2017-2022) & (US$ Million)
Table 31. North America Data Science and Machine-Learning Platforms Revenue by Country (2023-2028) & (US$ Million)
Table 32. Europe Data Science and Machine-Learning Platforms Revenue by Company (2020-2022) & (US$ Million)
Table 33. Europe Data Science and Machine-Learning Platforms Revenue by Type (2017-2022) & (US$ Million)
Table 34. Europe Data Science and Machine-Learning Platforms Revenue by Type (2023-2028) & (US$ Million)
Table 35. Europe Data Science and Machine-Learning Platforms Revenue by Application (2017-2022) & (US$ Million)
Table 36. Europe Data Science and Machine-Learning Platforms Revenue by Application (2023-2028) & (US$ Million)
Table 37. Europe Data Science and Machine-Learning Platforms Revenue by Country (2017-2022) & (US$ Million)
Table 38. Europe Data Science and Machine-Learning Platforms Revenue by Country (2023-2028) & (US$ Million)
Table 39. Asia Pacific Data Science and Machine-Learning Platforms Revenue by Company (2020-2022) & (US$ Million)
Table 40. Asia Pacific Data Science and Machine-Learning Platforms Revenue by Type (2017-2022) & (US$ Million)
Table 41. Asia Pacific Data Science and Machine-Learning Platforms Revenue by Type (2023-2028) & (US$ Million)
Table 42. Asia Pacific Data Science and Machine-Learning Platforms Revenue by Application (2017-2022) & (US$ Million)
Table 43. Asia Pacific Data Science and Machine-Learning Platforms Revenue by Application (2023-2028) & (US$ Million)
Table 44. Asia Pacific Data Science and Machine-Learning Platforms Revenue by Region (2017-2022) & (US$ Million)
Table 45. Asia Pacific Data Science and Machine-Learning Platforms Revenue by Region (2023-2028) & (US$ Million)
Table 46. Latin America Data Science and Machine-Learning Platforms Revenue by Company (2020-2022) & (US$ Million)
Table 47. Latin America Data Science and Machine-Learning Platforms Revenue by Type (2017-2022) & (US$ Million)
Table 48. Latin America Data Science and Machine-Learning Platforms Revenue by Type (2023-2028) & (US$ Million)
Table 49. Latin America Data Science and Machine-Learning Platforms Revenue by Application (2017-2022) & (US$ Million)
Table 50. Latin America Data Science and Machine-Learning Platforms Revenue by Application (2023-2028) & (US$ Million)
Table 51. Latin America Data Science and Machine-Learning Platforms Revenue by Country (2017-2022) & (US$ Million)
Table 52. Latin America Data Science and Machine-Learning Platforms Revenue by Country (2023-2028) & (US$ Million)
Table 53. Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Company (2020-2022) & (US$ Million)
Table 54. Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Type (2017-2022) & (US$ Million)
Table 55. Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Type (2023-2028) & (US$ Million)
Table 56. Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Application (2017-2022) & (US$ Million)
Table 57. Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Application (2023-2028) & (US$ Million)
Table 58. Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Country (2017-2022) & (US$ Million)
Table 59. Middle East and Africa Data Science and Machine-Learning Platforms Revenue by Country (2023-2028) & (US$ Million)
Table 60. SAS Company Details
Table 61. SAS Business Overview
Table 62. SAS Data Science and Machine-Learning Platforms Product and Services
Table 63. SAS Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 64. SAS Data Science and Machine-Learning Platforms SWOT Analysis
Table 65. SAS Recent Developments
Table 66. Alteryx Company Details
Table 67. Alteryx Business Overview
Table 68. Alteryx Data Science and Machine-Learning Platforms Product and Services
Table 69. Alteryx Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 70. Alteryx Data Science and Machine-Learning Platforms SWOT Analysis
Table 71. Alteryx Recent Developments
Table 72. IBM Company Details
Table 73. IBM Business Overview
Table 74. IBM Data Science and Machine-Learning Platforms Product and Services
Table 75. IBM Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 76. IBM Data Science and Machine-Learning Platforms SWOT Analysis
Table 77. IBM Recent Developments
Table 78. RapidMiner Company Details
Table 79. RapidMiner Business Overview
Table 80. RapidMiner Data Science and Machine-Learning Platforms Product and Services
Table 81. RapidMiner Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 82. RapidMiner Data Science and Machine-Learning Platforms SWOT Analysis
Table 83. RapidMiner Recent Developments
Table 84. KNIME Company Details
Table 85. KNIME Business Overview
Table 86. KNIME Data Science and Machine-Learning Platforms Product and Services
Table 87. KNIME Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 88. KNIME Data Science and Machine-Learning Platforms SWOT Analysis
Table 89. KNIME Recent Developments
Table 90. Microsoft Company Details
Table 91. Microsoft Business Overview
Table 92. Microsoft Data Science and Machine-Learning Platforms Product and Services
Table 93. Microsoft Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 94. Microsoft Data Science and Machine-Learning Platforms SWOT Analysis
Table 95. Microsoft Recent Developments
Table 96. Dataiku Company Details
Table 97. Dataiku Business Overview
Table 98. Dataiku Data Science and Machine-Learning Platforms Product and Services
Table 99. Dataiku Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 100. Dataiku Data Science and Machine-Learning Platforms SWOT Analysis
Table 101. Dataiku Recent Developments
Table 102. Databricks Company Details
Table 103. Databricks Business Overview
Table 104. Databricks Data Science and Machine-Learning Platforms Product and Services
Table 105. Databricks Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 106. Databricks Data Science and Machine-Learning Platforms SWOT Analysis
Table 107. Databricks Recent Developments
Table 108. TIBCO Software Company Details
Table 109. TIBCO Software Business Overview
Table 110. TIBCO Software Data Science and Machine-Learning Platforms Product and Services
Table 111. TIBCO Software Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 112. TIBCO Software Data Science and Machine-Learning Platforms SWOT Analysis
Table 113. TIBCO Software Recent Developments
Table 114. MathWorks Company Details
Table 115. MathWorks Business Overview
Table 116. MathWorks Data Science and Machine-Learning Platforms Product and Services
Table 117. MathWorks Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 118. MathWorks Data Science and Machine-Learning Platforms SWOT Analysis
Table 119. MathWorks Recent Developments
Table 120. H20.ai Company Details
Table 121. H20.ai Business Overview
Table 122. H20.ai Data Science and Machine-Learning Platforms Product and Services
Table 123. H20.ai Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 124. H20.ai Recent Developments
Table 125. Anaconda Company Details
Table 126. Anaconda Business Overview
Table 127. Anaconda Data Science and Machine-Learning Platforms Product and Services
Table 128. Anaconda Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 129. Anaconda Recent Developments
Table 130. SAP Company Details
Table 131. SAP Business Overview
Table 132. SAP Data Science and Machine-Learning Platforms Product and Services
Table 133. SAP Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 134. SAP Recent Developments
Table 135. Google Company Details
Table 136. Google Business Overview
Table 137. Google Data Science and Machine-Learning Platforms Product and Services
Table 138. Google Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 139. Google Recent Developments
Table 140. Domino Data Lab Company Details
Table 141. Domino Data Lab Business Overview
Table 142. Domino Data Lab Data Science and Machine-Learning Platforms Product and Services
Table 143. Domino Data Lab Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 144. Domino Data Lab Recent Developments
Table 145. Angoss Company Details
Table 146. Angoss Business Overview
Table 147. Angoss Data Science and Machine-Learning Platforms Product and Services
Table 148. Angoss Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 149. Angoss Recent Developments
Table 150. Lexalytics Company Details
Table 151. Lexalytics Business Overview
Table 152. Lexalytics Data Science and Machine-Learning Platforms Product and Services
Table 153. Lexalytics Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 154. Lexalytics Recent Developments
Table 155. Rapid Insight Company Details
Table 156. Rapid Insight Business Overview
Table 157. Rapid Insight Data Science and Machine-Learning Platforms Product and Services
Table 158. Rapid Insight Data Science and Machine-Learning Platforms Revenue in Data Science and Machine-Learning Platforms Business (2017-2022) & (US$ Million)
Table 159. Rapid Insight Recent Developments
Table 160. Data Science and Machine-Learning Platforms Market Trends
Table 161. Data Science and Machine-Learning Platforms Market Drivers
Table 162. Data Science and Machine-Learning Platforms Market Challenges
Table 163. Data Science and Machine-Learning Platforms Market Restraints
Table 164. Research Programs/Design for This Report
Table 165. Key Data Information from Secondary Sources
Table 166. Key Data Information from Primary Sources
List of Figures
Figure 1. Global Data Science and Machine-Learning Platforms Sales Market Share by Type: 2021 VS 2028
Figure 2. Open Source Data Integration Tools Features
Figure 3. Cloud-based Data Integration Tools Features
Figure 4. Global Data Science and Machine-Learning Platforms Sales Market Share by Application: 2021 VS 2028
Figure 5. Small-Sized Enterprises Case Studies
Figure 6. Medium-Sized Enterprise Case Studies
Figure 7. Large Enterprises Case Studies
Figure 8. Data Science and Machine-Learning Platforms Report Years Considered
Figure 9. Global Data Science and Machine-Learning Platforms Revenue, (US$ Million), 2017 VS 2021 VS 2028
Figure 10. Global Data Science and Machine-Learning Platforms Market Size 2017-2028 (US$ Million)
Figure 11. Global Data Science and Machine-Learning Platforms Market Size Market Share by Region: 2021 VS 2028
Figure 12. Global Data Science and Machine-Learning Platforms Revenue Market Share by Region in 2017 VS 2022
Figure 13. Global Top 10 Data Science and Machine-Learning Platforms Countries Ranking by Market Size (US$ Million) in 2021
Figure 14. Global Data Science and Machine-Learning Platforms Market Share by Players in 2021
Figure 15. Global Top Data Science and Machine-Learning Platforms Players by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Data Science and Machine-Learning Platforms as of 2021)
Figure 16. The Top 10 and 5 Players Market Share by Data Science and Machine-Learning Platforms Revenue in 2021
Figure 17. North America Data Science and Machine-Learning Platforms Revenue Market Share by Company in 2021
Figure 18. North America Data Science and Machine-Learning Platforms Revenue Market Share by Type (2017-2028)
Figure 19. North America Data Science and Machine-Learning Platforms Revenue Market Share by Application (2017-2028)
Figure 20. North America Data Science and Machine-Learning Platforms Revenue Share by Country (2017-2028)
Figure 21. U.S. Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 22. Canada Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 23. Europe Data Science and Machine-Learning Platforms Revenue Market Share by Company in 2021
Figure 24. Europe Data Science and Machine-Learning Platforms Revenue Market Share by Type (2017-2028)
Figure 25. Europe Data Science and Machine-Learning Platforms Revenue Market Share by Application (2017-2028)
Figure 26. Europe Data Science and Machine-Learning Platforms Revenue Share by Country (2017-2028)
Figure 27. Germany Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 28. France Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 29. U.K. Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 30. Italy Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 31. Russia Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 32. Asia Pacific Data Science and Machine-Learning Platforms Revenue Market Share by Company in 2021
Figure 33. Asia Pacific Data Science and Machine-Learning Platforms Revenue Market Share by Type (2017-2028)
Figure 34. Asia Pacific Data Science and Machine-Learning Platforms Revenue Market Share by Application (2017-2028)
Figure 35. Asia Pacific Data Science and Machine-Learning Platforms Revenue Share by Region (2017-2028)
Figure 36. China Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 37. Japan Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 38. South Korea Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 39. India Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 40. Australia Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 41. Taiwan Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 42. Indonesia Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 43. Thailand Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 44. Malaysia Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 45. Philippines Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 46. Vietnam Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 47. Latin America Data Science and Machine-Learning Platforms Revenue Market Share by Company in 2021
Figure 48. Latin America Data Science and Machine-Learning Platforms Revenue Market Share by Type (2017-2028)
Figure 49. Latin America Data Science and Machine-Learning Platforms Revenue Market Share by Application (2017-2028)
Figure 50. Latin America Data Science and Machine-Learning Platforms Revenue Share by Country (2017-2028)
Figure 51. Mexico Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 52. Brazil Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 53. Argentina Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 54. Middle East and Africa Data Science and Machine-Learning Platforms Revenue Market Share by Company in 2021
Figure 55. Middle East and Africa Data Science and Machine-Learning Platforms Revenue Market Share by Type (2017-2028)
Figure 56. Middle East and Africa Data Science and Machine-Learning Platforms Revenue Market Share by Application (2017-2028)
Figure 57. Middle East and Africa Data Science and Machine-Learning Platforms Revenue Share by Country (2017-2028)
Figure 58. Turkey Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 59. Saudi Arabia Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 60. UAE Data Science and Machine-Learning Platforms Revenue (2017-2028) & (US$ Million)
Figure 61. SAS Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 62. Alteryx Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 63. IBM Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 64. RapidMiner Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 65. KNIME Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 66. Microsoft Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 67. Dataiku Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 68. Databricks Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 69. TIBCO Software Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 70. MathWorks Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 71. H20.ai Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 72. Anaconda Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 73. SAP Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 74. Google Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 75. Domino Data Lab Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 76. Angoss Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 77. Lexalytics Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 78. Rapid Insight Revenue Growth Rate in Data Science and Machine-Learning Platforms Business (2017-2022)
Figure 79. Bottom-up and Top-down Approaches for This Report
Figure 80. Data Triangulation
Figure 81. Key Executives Interviewed
SECONDARY RESEARCH
Secondary Research Information is collected from a number of publicly available as well as paid databases. Public sources involve publications by different associations and governments, annual reports and statements of companies, white papers and research publications by recognized industry experts and renowned academia etc. Paid data sources include third party authentic industry databases.
PRIMARY RESEARCH
Once data collection is done through secondary research, primary interviews are conducted with different stakeholders across the value chain like manufacturers, distributors, ingredient/input suppliers, end customers and other key opinion leaders of the industry. Primary research is used both to validate the data points obtained from secondary research and to fill in the data gaps after secondary research.
MARKET ENGINEERING
The market engineering phase involves analyzing the data collected, market breakdown and forecasting. Macroeconomic indicators and bottom-up and top-down approaches are used to arrive at a complete set of data points that give way to valuable qualitative and quantitative insights. Each data point is verified by the process of data triangulation to validate the numbers and arrive at close estimates.
EXPERT VALIDATION
The market engineered data is verified and validated by a number of experts, both in-house and external.
REPORT WRITING/ PRESENTATION
After the data is curated by the mentioned highly sophisticated process, the analysts begin to write the report. Garnering insights from data and forecasts, insights are drawn to visualize the entire ecosystem in a single report.
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