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Global Data Science and ML Platforms Market 2024 by Company, Regions, Type and Application, Forecast to 2030

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1 Market Overview

  • 1.1 Product Overview and Scope of Data Science and ML Platforms
  • 1.2 Market Estimation Caveats and Base Year
  • 1.3 Classification of Data Science and ML Platforms by Type
    • 1.3.1 Overview: Global Data Science and ML Platforms Market Size by Type: 2019 Versus 2023 Versus 2030
    • 1.3.2 Global Data Science and ML Platforms Consumption Value Market Share by Type in 2023
    • 1.3.3 Cloud-based
    • 1.3.4 On-premises
  • 1.4 Global Data Science and ML Platforms Market by Application
    • 1.4.1 Overview: Global Data Science and ML Platforms Market Size by Application: 2019 Versus 2023 Versus 2030
    • 1.4.2 Small and Medium Enterprises (SMEs)
    • 1.4.3 Large Enterprises
  • 1.5 Global Data Science and ML Platforms Market Size & Forecast
  • 1.6 Global Data Science and ML Platforms Market Size and Forecast by Region
    • 1.6.1 Global Data Science and ML Platforms Market Size by Region: 2019 VS 2023 VS 2030
    • 1.6.2 Global Data Science and ML Platforms Market Size by Region, (2019-2030)
    • 1.6.3 North America Data Science and ML Platforms Market Size and Prospect (2019-2030)
    • 1.6.4 Europe Data Science and ML Platforms Market Size and Prospect (2019-2030)
    • 1.6.5 Asia-Pacific Data Science and ML Platforms Market Size and Prospect (2019-2030)
    • 1.6.6 South America Data Science and ML Platforms Market Size and Prospect (2019-2030)
    • 1.6.7 Middle East and Africa Data Science and ML Platforms Market Size and Prospect (2019-2030)

2 Company Profiles

  • 2.1 Palantier
    • 2.1.1 Palantier Details
    • 2.1.2 Palantier Major Business
    • 2.1.3 Palantier Data Science and ML Platforms Product and Solutions
    • 2.1.4 Palantier Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.1.5 Palantier Recent Developments and Future Plans
  • 2.2 MathWorks
    • 2.2.1 MathWorks Details
    • 2.2.2 MathWorks Major Business
    • 2.2.3 MathWorks Data Science and ML Platforms Product and Solutions
    • 2.2.4 MathWorks Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.2.5 MathWorks Recent Developments and Future Plans
  • 2.3 Alteryx
    • 2.3.1 Alteryx Details
    • 2.3.2 Alteryx Major Business
    • 2.3.3 Alteryx Data Science and ML Platforms Product and Solutions
    • 2.3.4 Alteryx Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.3.5 Alteryx Recent Developments and Future Plans
  • 2.4 SAS
    • 2.4.1 SAS Details
    • 2.4.2 SAS Major Business
    • 2.4.3 SAS Data Science and ML Platforms Product and Solutions
    • 2.4.4 SAS Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.4.5 SAS Recent Developments and Future Plans
  • 2.5 Databricks
    • 2.5.1 Databricks Details
    • 2.5.2 Databricks Major Business
    • 2.5.3 Databricks Data Science and ML Platforms Product and Solutions
    • 2.5.4 Databricks Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.5.5 Databricks Recent Developments and Future Plans
  • 2.6 TIBCO Software
    • 2.6.1 TIBCO Software Details
    • 2.6.2 TIBCO Software Major Business
    • 2.6.3 TIBCO Software Data Science and ML Platforms Product and Solutions
    • 2.6.4 TIBCO Software Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.6.5 TIBCO Software Recent Developments and Future Plans
  • 2.7 Dataiku
    • 2.7.1 Dataiku Details
    • 2.7.2 Dataiku Major Business
    • 2.7.3 Dataiku Data Science and ML Platforms Product and Solutions
    • 2.7.4 Dataiku Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.7.5 Dataiku Recent Developments and Future Plans
  • 2.8 H2O.ai
    • 2.8.1 H2O.ai Details
    • 2.8.2 H2O.ai Major Business
    • 2.8.3 H2O.ai Data Science and ML Platforms Product and Solutions
    • 2.8.4 H2O.ai Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.8.5 H2O.ai Recent Developments and Future Plans
  • 2.9 IBM
    • 2.9.1 IBM Details
    • 2.9.2 IBM Major Business
    • 2.9.3 IBM Data Science and ML Platforms Product and Solutions
    • 2.9.4 IBM Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.9.5 IBM Recent Developments and Future Plans
  • 2.10 Microsoft
    • 2.10.1 Microsoft Details
    • 2.10.2 Microsoft Major Business
    • 2.10.3 Microsoft Data Science and ML Platforms Product and Solutions
    • 2.10.4 Microsoft Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.10.5 Microsoft Recent Developments and Future Plans
  • 2.11 Google
    • 2.11.1 Google Details
    • 2.11.2 Google Major Business
    • 2.11.3 Google Data Science and ML Platforms Product and Solutions
    • 2.11.4 Google Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.11.5 Google Recent Developments and Future Plans
  • 2.12 KNIME
    • 2.12.1 KNIME Details
    • 2.12.2 KNIME Major Business
    • 2.12.3 KNIME Data Science and ML Platforms Product and Solutions
    • 2.12.4 KNIME Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.12.5 KNIME Recent Developments and Future Plans
  • 2.13 DataRobot
    • 2.13.1 DataRobot Details
    • 2.13.2 DataRobot Major Business
    • 2.13.3 DataRobot Data Science and ML Platforms Product and Solutions
    • 2.13.4 DataRobot Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.13.5 DataRobot Recent Developments and Future Plans
  • 2.14 RapidMiner
    • 2.14.1 RapidMiner Details
    • 2.14.2 RapidMiner Major Business
    • 2.14.3 RapidMiner Data Science and ML Platforms Product and Solutions
    • 2.14.4 RapidMiner Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.14.5 RapidMiner Recent Developments and Future Plans
  • 2.15 Anaconda
    • 2.15.1 Anaconda Details
    • 2.15.2 Anaconda Major Business
    • 2.15.3 Anaconda Data Science and ML Platforms Product and Solutions
    • 2.15.4 Anaconda Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.15.5 Anaconda Recent Developments and Future Plans
  • 2.16 Domino
    • 2.16.1 Domino Details
    • 2.16.2 Domino Major Business
    • 2.16.3 Domino Data Science and ML Platforms Product and Solutions
    • 2.16.4 Domino Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.16.5 Domino Recent Developments and Future Plans
  • 2.17 Altair
    • 2.17.1 Altair Details
    • 2.17.2 Altair Major Business
    • 2.17.3 Altair Data Science and ML Platforms Product and Solutions
    • 2.17.4 Altair Data Science and ML Platforms Revenue, Gross Margin and Market Share (2019-2024)
    • 2.17.5 Altair Recent Developments and Future Plans

3 Market Competition, by Players

  • 3.1 Global Data Science and ML Platforms Revenue and Share by Players (2019-2024)
  • 3.2 Market Share Analysis (2023)
    • 3.2.1 Market Share of Data Science and ML Platforms by Company Revenue
    • 3.2.2 Top 3 Data Science and ML Platforms Players Market Share in 2023
    • 3.2.3 Top 6 Data Science and ML Platforms Players Market Share in 2023
  • 3.3 Data Science and ML Platforms Market: Overall Company Footprint Analysis
    • 3.3.1 Data Science and ML Platforms Market: Region Footprint
    • 3.3.2 Data Science and ML Platforms Market: Company Product Type Footprint
    • 3.3.3 Data Science and ML Platforms Market: Company Product Application Footprint
  • 3.4 New Market Entrants and Barriers to Market Entry
  • 3.5 Mergers, Acquisition, Agreements, and Collaborations

4 Market Size Segment by Type

  • 4.1 Global Data Science and ML Platforms Consumption Value and Market Share by Type (2019-2024)
  • 4.2 Global Data Science and ML Platforms Market Forecast by Type (2025-2030)

5 Market Size Segment by Application

  • 5.1 Global Data Science and ML Platforms Consumption Value Market Share by Application (2019-2024)
  • 5.2 Global Data Science and ML Platforms Market Forecast by Application (2025-2030)

6 North America

  • 6.1 North America Data Science and ML Platforms Consumption Value by Type (2019-2030)
  • 6.2 North America Data Science and ML Platforms Consumption Value by Application (2019-2030)
  • 6.3 North America Data Science and ML Platforms Market Size by Country
    • 6.3.1 North America Data Science and ML Platforms Consumption Value by Country (2019-2030)
    • 6.3.2 United States Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 6.3.3 Canada Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 6.3.4 Mexico Data Science and ML Platforms Market Size and Forecast (2019-2030)

7 Europe

  • 7.1 Europe Data Science and ML Platforms Consumption Value by Type (2019-2030)
  • 7.2 Europe Data Science and ML Platforms Consumption Value by Application (2019-2030)
  • 7.3 Europe Data Science and ML Platforms Market Size by Country
    • 7.3.1 Europe Data Science and ML Platforms Consumption Value by Country (2019-2030)
    • 7.3.2 Germany Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 7.3.3 France Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 7.3.4 United Kingdom Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 7.3.5 Russia Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 7.3.6 Italy Data Science and ML Platforms Market Size and Forecast (2019-2030)

8 Asia-Pacific

  • 8.1 Asia-Pacific Data Science and ML Platforms Consumption Value by Type (2019-2030)
  • 8.2 Asia-Pacific Data Science and ML Platforms Consumption Value by Application (2019-2030)
  • 8.3 Asia-Pacific Data Science and ML Platforms Market Size by Region
    • 8.3.1 Asia-Pacific Data Science and ML Platforms Consumption Value by Region (2019-2030)
    • 8.3.2 China Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 8.3.3 Japan Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 8.3.4 South Korea Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 8.3.5 India Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 8.3.6 Southeast Asia Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 8.3.7 Australia Data Science and ML Platforms Market Size and Forecast (2019-2030)

9 South America

  • 9.1 South America Data Science and ML Platforms Consumption Value by Type (2019-2030)
  • 9.2 South America Data Science and ML Platforms Consumption Value by Application (2019-2030)
  • 9.3 South America Data Science and ML Platforms Market Size by Country
    • 9.3.1 South America Data Science and ML Platforms Consumption Value by Country (2019-2030)
    • 9.3.2 Brazil Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 9.3.3 Argentina Data Science and ML Platforms Market Size and Forecast (2019-2030)

10 Middle East & Africa

  • 10.1 Middle East & Africa Data Science and ML Platforms Consumption Value by Type (2019-2030)
  • 10.2 Middle East & Africa Data Science and ML Platforms Consumption Value by Application (2019-2030)
  • 10.3 Middle East & Africa Data Science and ML Platforms Market Size by Country
    • 10.3.1 Middle East & Africa Data Science and ML Platforms Consumption Value by Country (2019-2030)
    • 10.3.2 Turkey Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 10.3.3 Saudi Arabia Data Science and ML Platforms Market Size and Forecast (2019-2030)
    • 10.3.4 UAE Data Science and ML Platforms Market Size and Forecast (2019-2030)

11 Market Dynamics

  • 11.1 Data Science and ML Platforms Market Drivers
  • 11.2 Data Science and ML Platforms Market Restraints
  • 11.3 Data Science and ML Platforms Trends Analysis
  • 11.4 Porters Five Forces Analysis
    • 11.4.1 Threat of New Entrants
    • 11.4.2 Bargaining Power of Suppliers
    • 11.4.3 Bargaining Power of Buyers
    • 11.4.4 Threat of Substitutes
    • 11.4.5 Competitive Rivalry

12 Industry Chain Analysis

  • 12.1 Data Science and ML Platforms Industry Chain
  • 12.2 Data Science and ML Platforms Upstream Analysis
  • 12.3 Data Science and ML Platforms Midstream Analysis
  • 12.4 Data Science and ML Platforms Downstream Analysis

13 Research Findings and Conclusion

    14 Appendix

    • 14.1 Methodology
    • 14.2 Research Process and Data Source

    According to our (Global Info Research) latest study, the global Data Science and ML Platforms market size was valued at USD million in 2023 and is forecast to a readjusted size of USD million by 2030 with a CAGR of % during review period.
    The Global Info Research report includes an overview of the development of the Data Science and ML Platforms industry chain, the market status of Small and Medium Enterprises (SMEs) (Cloud-based, On-premises), Large Enterprises (Cloud-based, On-premises), and key enterprises in developed and developing market, and analysed the cutting-edge technology, patent, hot applications and market trends of Data Science and ML Platforms.
    Regionally, the report analyzes the Data Science and ML Platforms markets in key regions. North America and Europe are experiencing steady growth, driven by government initiatives and increasing consumer awareness. Asia-Pacific, particularly China, leads the global Data Science and ML Platforms market, with robust domestic demand, supportive policies, and a strong manufacturing base.
    Key Features:
    The report presents comprehensive understanding of the Data Science and ML Platforms market. It provides a holistic view of the industry, as well as detailed insights into individual components and stakeholders. The report analysis market dynamics, trends, challenges, and opportunities within the Data Science and ML Platforms industry.
    The report involves analyzing the market at a macro level:
    Market Sizing and Segmentation: Report collect data on the overall market size, including the revenue generated, and market share of different by Type (e.g., Cloud-based, On-premises).
    Industry Analysis: Report analyse the broader industry trends, such as government policies and regulations, technological advancements, consumer preferences, and market dynamics. This analysis helps in understanding the key drivers and challenges influencing the Data Science and ML Platforms market.
    Regional Analysis: The report involves examining the Data Science and ML Platforms market at a regional or national level. Report analyses regional factors such as government incentives, infrastructure development, economic conditions, and consumer behaviour to identify variations and opportunities within different markets.
    Market Projections: Report covers the gathered data and analysis to make future projections and forecasts for the Data Science and ML Platforms market. This may include estimating market growth rates, predicting market demand, and identifying emerging trends.
    The report also involves a more granular approach to Data Science and ML Platforms:
    Company Analysis: Report covers individual Data Science and ML Platforms players, suppliers, and other relevant industry players. This analysis includes studying their financial performance, market positioning, product portfolios, partnerships, and strategies.
    Consumer Analysis: Report covers data on consumer behaviour, preferences, and attitudes towards Data Science and ML Platforms This may involve surveys, interviews, and analysis of consumer reviews and feedback from different by Application (Small and Medium Enterprises (SMEs), Large Enterprises).
    Technology Analysis: Report covers specific technologies relevant to Data Science and ML Platforms. It assesses the current state, advancements, and potential future developments in Data Science and ML Platforms areas.
    Competitive Landscape: By analyzing individual companies, suppliers, and consumers, the report present insights into the competitive landscape of the Data Science and ML Platforms market. This analysis helps understand market share, competitive advantages, and potential areas for differentiation among industry players.
    Market Validation: The report involves validating findings and projections through primary research, such as surveys, interviews, and focus groups.
    Market Segmentation
    Data Science and ML Platforms market is split by Type and by Application. For the period 2019-2030, the growth among segments provides accurate calculations and forecasts for consumption value by Type, and by Application in terms of value.
    Market segment by Type
    Cloud-based
    On-premises
    Market segment by Application
    Small and Medium Enterprises (SMEs)
    Large Enterprises
    Market segment by players, this report covers
    Palantier
    MathWorks
    Alteryx
    SAS
    Databricks
    TIBCO Software
    Dataiku
    H2O.ai
    IBM
    Microsoft
    Google
    KNIME
    DataRobot
    RapidMiner
    Anaconda
    Domino
    Altair
    Market segment by regions, regional analysis covers
    North America (United States, Canada, and Mexico)
    Europe (Germany, France, UK, Russia, Italy, and Rest of Europe)
    Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia and Rest of Asia-Pacific)
    South America (Brazil, Argentina and Rest of South America)
    Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
    The content of the study subjects, includes a total of 13 chapters:
    Chapter 1, to describe Data Science and ML Platforms product scope, market overview, market estimation caveats and base year.
    Chapter 2, to profile the top players of Data Science and ML Platforms, with revenue, gross margin and global market share of Data Science and ML Platforms from 2019 to 2024.
    Chapter 3, the Data Science and ML Platforms competitive situation, revenue and global market share of top players are analyzed emphatically by landscape contrast.
    Chapter 4 and 5, to segment the market size by Type and application, with consumption value and growth rate by Type, application, from 2019 to 2030.
    Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2019 to 2024.and Data Science and ML Platforms market forecast, by regions, type and application, with consumption value, from 2025 to 2030.
    Chapter 11, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
    Chapter 12, the key raw materials and key suppliers, and industry chain of Data Science and ML Platforms.
    Chapter 13, to describe Data Science and ML Platforms research findings and conclusion.

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