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Global Data Science and ML Platforms Market Size, Status and Forecast 2020-2026

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1 Report Overview

  • 1.1 Study Scope
  • 1.2 Key Market Segments
  • 1.3 Market Analysis by Type
    • 1.3.1 Global Data Science and ML Platforms Market Size Growth Rate by Type: 2020 VS 2026
    • 1.3.2 Cloud-based
    • 1.3.3 On-premises
  • 1.4 Market by Application
    • 1.4.1 Global Data Science and ML Platforms Market Share by Application: 2020 VS 2026
    • 1.4.2 Small and Medium Enterprises (SMEs)
    • 1.4.3 Large Enterprises
  • 1.5 Study Objectives
  • 1.6 Years Considered

2 Global Growth Trends

  • 2.1 Global Data Science and ML Platforms Market Perspective (2015-2026)
  • 2.2 Data Science and ML Platforms Growth Trends by Regions
    • 2.2.1 Data Science and ML Platforms Market Size by Regions: 2015 VS 2020 VS 2026
    • 2.2.2 Data Science and ML Platforms Historic Market Share by Regions (2015-2020)
    • 2.2.3 Data Science and ML Platforms Forecasted Market Size by Regions (2021-2026)
  • 2.3 Data Science and ML Platforms Industry Dynamic
    • 2.3.1 Data Science and ML Platforms Market Trends
    • 2.3.2 Data Science and ML Platforms Market Drivers
    • 2.3.3 Data Science and ML Platforms Market Challenges
    • 2.3.4 Data Science and ML Platforms Market Restraints

3 Competition Landscape by Key Players

  • 3.1 Global Top Data Science and ML Platforms Players by Market Size
    • 3.1.1 Global Top Data Science and ML Platforms Players by Revenue (2015-2020)
    • 3.1.2 Global Data Science and ML Platforms Revenue Market Share by Players (2015-2020)
  • 3.2 Global Data Science and ML Platforms Market Share by Company Type (Tier 1, Tier 2 and Tier 3)
  • 3.3 Players Covered: Ranking by Data Science and ML Platforms Revenue
  • 3.4 Global Data Science and ML Platforms Market Concentration Ratio
    • 3.4.1 Global Data Science and ML Platforms Market Concentration Ratio (CR5 and HHI)
    • 3.4.2 Global Top 10 and Top 5 Companies by Data Science and ML Platforms Revenue in 2019
  • 3.5 Key Players Data Science and ML Platforms Area Served
  • 3.6 Key Players Data Science and ML Platforms Product Solution and Service
  • 3.7 Date of Enter into Data Science and ML Platforms Market
  • 3.8 Mergers & Acquisitions, Expansion Plans

4 Data Science and ML Platforms Breakdown Data by Type

  • 4.1 Global Data Science and ML Platforms Historic Market Size by Type (2015-2020)
  • 4.2 Global Data Science and ML Platforms Forecasted Market Size by Type (2021-2026)

5 Data Science and ML Platforms Breakdown Data by Application

  • 5.1 Global Data Science and ML Platforms Historic Market Size by Application (2015-2020)
  • 5.2 Global Data Science and ML Platforms Forecasted Market Size by Application (2021-2026)

6 North America

  • 6.1 North America Data Science and ML Platforms Market Size (2015-2026)
  • 6.2 North America Data Science and ML Platforms Market Size by Type (2015-2020)
  • 6.3 North America Data Science and ML Platforms Market Size by Application (2015-2020)
  • 6.4 North America Data Science and ML Platforms Market Size by Country (2015-2020)
    • 6.4.1 United States
    • 6.4.2 Canada

7 Europe

  • 7.1 Europe Data Science and ML Platforms Market Size (2015-2026)
  • 7.2 Europe Data Science and ML Platforms Market Size by Type (2015-2020)
  • 7.3 Europe Data Science and ML Platforms Market Size by Application (2015-2020)
  • 7.4 Europe Data Science and ML Platforms Market Size by Country (2015-2020)
    • 7.4.1 Germany
    • 7.4.2 France
    • 7.4.3 U.K.
    • 7.4.4 Italy
    • 7.4.5 Russia
    • 7.4.6 Nordic

8 Asia-Pacific

  • 8.1 Asia-Pacific Data Science and ML Platforms Market Size (2015-2026)
  • 8.2 Asia-Pacific Data Science and ML Platforms Market Size by Type (2015-2020)
  • 8.3 Asia-Pacific Data Science and ML Platforms Market Size by Application (2015-2020)
  • 8.4 Asia-Pacific Data Science and ML Platforms Market Size by Region (2015-2020)
    • 8.4.1 China
    • 8.4.2 Japan
    • 8.4.3 South Korea
    • 8.4.4 Southeast Asia
    • 8.4.5 India
    • 8.4.6 Australia

9 Latin America

  • 9.1 Latin America Data Science and ML Platforms Market Size (2015-2026)
  • 9.2 Latin America Data Science and ML Platforms Market Size by Type (2015-2020)
  • 9.3 Latin America Data Science and ML Platforms Market Size by Application (2015-2020)
  • 9.4 Latin America Data Science and ML Platforms Market Size by Country (2015-2020)
    • 9.4.1 Mexico
    • 9.4.2 Brazil

10 Middle East & Africa

  • 10.1 Middle East & Africa Data Science and ML Platforms Market Size (2015-2026)
  • 10.2 Middle East & Africa Data Science and ML Platforms Market Size by Type (2015-2020)
  • 10.3 Middle East & Africa Data Science and ML Platforms Market Size by Application (2015-2020)
  • 10.4 Middle East & Africa Data Science and ML Platforms Market Size by Country (2015-2020)
    • 10.4.1 Turkey
    • 10.4.2 Saudi Arabia
    • 10.4.3 UAE

11Key Players Profiles

  • 11.1 Palantier
    • 11.1.1 Palantier Company Details
    • 11.1.2 Palantier Business Overview
    • 11.1.3 Palantier Data Science and ML Platforms Introduction
    • 11.1.4 Palantier Revenue in Data Science and ML Platforms Business (2015-2020))
    • 11.1.5 Palantier Recent Development
  • 11.2 MathWorks
    • 11.2.1 MathWorks Company Details
    • 11.2.2 MathWorks Business Overview
    • 11.2.3 MathWorks Data Science and ML Platforms Introduction
    • 11.2.4 MathWorks Revenue in Data Science and ML Platforms Business (2015-2020)
    • 11.2.5 MathWorks Recent Development
  • 11.3 Alteryx
    • 11.3.1 Alteryx Company Details
    • 11.3.2 Alteryx Business Overview
    • 11.3.3 Alteryx Data Science and ML Platforms Introduction
    • 11.3.4 Alteryx Revenue in Data Science and ML Platforms Business (2015-2020)
    • 11.3.5 Alteryx Recent Development
  • 11.4 SAS
    • 11.4.1 SAS Company Details
    • 11.4.2 SAS Business Overview
    • 11.4.3 SAS Data Science and ML Platforms Introduction
    • 11.4.4 SAS Revenue in Data Science and ML Platforms Business (2015-2020)
    • 11.4.5 SAS Recent Development
  • 11.5 Databricks
    • 11.5.1 Databricks Company Details
    • 11.5.2 Databricks Business Overview
    • 11.5.3 Databricks Data Science and ML Platforms Introduction
    • 11.5.4 Databricks Revenue in Data Science and ML Platforms Business (2015-2020)
    • 11.5.5 Databricks Recent Development
  • 11.6 TIBCO Software
    • 11.6.1 TIBCO Software Company Details
    • 11.6.2 TIBCO Software Business Overview
    • 11.6.3 TIBCO Software Data Science and ML Platforms Introduction
    • 11.6.4 TIBCO Software Revenue in Data Science and ML Platforms Business (2015-2020)
    • 11.6.5 TIBCO Software Recent Development
  • 11.7 Dataiku
    • 11.7.1 Dataiku Company Details
    • 11.7.2 Dataiku Business Overview
    • 11.7.3 Dataiku Data Science and ML Platforms Introduction
    • 11.7.4 Dataiku Revenue in Data Science and ML Platforms Business (2015-2020)
    • 11.7.5 Dataiku Recent Development
  • 11.8 H2O.ai
    • 11.8.1 H2O.ai Company Details
    • 11.8.2 H2O.ai Business Overview
    • 11.8.3 H2O.ai Data Science and ML Platforms Introduction
    • 11.8.4 H2O.ai Revenue in Data Science and ML Platforms Business (2015-2020)
    • 11.8.5 H2O.ai Recent Development
  • 11.9 IBM
    • 11.9.1 IBM Company Details
    • 11.9.2 IBM Business Overview
    • 11.9.3 IBM Data Science and ML Platforms Introduction
    • 11.9.4 IBM Revenue in Data Science and ML Platforms Business (2015-2020)
    • 11.9.5 IBM Recent Development
  • 11.10 Microsoft
    • 11.10.1 Microsoft Company Details
    • 11.10.2 Microsoft Business Overview
    • 11.10.3 Microsoft Data Science and ML Platforms Introduction
    • 11.10.4 Microsoft Revenue in Data Science and ML Platforms Business (2015-2020)
    • 11.10.5 Microsoft Recent Development
  • 11.11 Google
    • 10.11.1 Google Company Details
    • 10.11.2 Google Business Overview
    • 10.11.3 Google Data Science and ML Platforms Introduction
    • 10.11.4 Google Revenue in Data Science and ML Platforms Business (2015-2020)
    • 10.11.5 Google Recent Development
  • 11.12 KNIME
    • 10.12.1 KNIME Company Details
    • 10.12.2 KNIME Business Overview
    • 10.12.3 KNIME Data Science and ML Platforms Introduction
    • 10.12.4 KNIME Revenue in Data Science and ML Platforms Business (2015-2020)
    • 10.12.5 KNIME Recent Development
  • 11.13 DataRobot
    • 10.13.1 DataRobot Company Details
    • 10.13.2 DataRobot Business Overview
    • 10.13.3 DataRobot Data Science and ML Platforms Introduction
    • 10.13.4 DataRobot Revenue in Data Science and ML Platforms Business (2015-2020)
    • 10.13.5 DataRobot Recent Development
  • 11.14 RapidMiner
    • 10.14.1 RapidMiner Company Details
    • 10.14.2 RapidMiner Business Overview
    • 10.14.3 RapidMiner Data Science and ML Platforms Introduction
    • 10.14.4 RapidMiner Revenue in Data Science and ML Platforms Business (2015-2020)
    • 10.14.5 RapidMiner Recent Development
  • 11.15 Anaconda
    • 10.15.1 Anaconda Company Details
    • 10.15.2 Anaconda Business Overview
    • 10.15.3 Anaconda Data Science and ML Platforms Introduction
    • 10.15.4 Anaconda Revenue in Data Science and ML Platforms Business (2015-2020)
    • 10.15.5 Anaconda Recent Development
  • 11.16 Domino
    • 10.16.1 Domino Company Details
    • 10.16.2 Domino Business Overview
    • 10.16.3 Domino Data Science and ML Platforms Introduction
    • 10.16.4 Domino Revenue in Data Science and ML Platforms Business (2015-2020)
    • 10.16.5 Domino Recent Development
  • 11.17 Altair
    • 10.17.1 Altair Company Details
    • 10.17.2 Altair Business Overview
    • 10.17.3 Altair Data Science and ML Platforms Introduction
    • 10.17.4 Altair Revenue in Data Science and ML Platforms Business (2015-2020)
    • 10.17.5 Altair Recent Development

12Analyst's Viewpoints/Conclusions

    13Appendix

    • 13.1 Research Methodology
      • 13.1.1 Methodology/Research Approach
      • 13.1.2 Data Source
    • 13.2 Disclaimer

    Data Science and ML Platforms market is segmented by company, region (country), by Type, and by Application. Players, stakeholders, and other participants in the global Data Science and ML Platforms market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by Type and by Application in terms of revenue and forecast for the period 2015-2026.

    Market segment by Type, the product can be split into
    Cloud-based
    On-premises

    Market segment by Application, split into
    Small and Medium Enterprises (SMEs)
    Large Enterprises

    Based on regional and country-level analysis, the Data Science and ML Platforms market has been segmented as follows:
    North America
    United States
    Canada
    Europe
    Germany
    France
    U.K.
    Italy
    Russia
    Nordic
    Asia-Pacific
    China
    Japan
    South Korea
    Southeast Asia
    India
    Australia
    Latin America
    Mexico
    Brazil
    Middle East & Africa
    Turkey
    Saudi Arabia
    UAE

    In the competitive analysis section of the report, leading as well as prominent players of the global Data Science and ML Platforms market are broadly studied on the basis of key factors. The report offers comprehensive analysis and accurate statistics on revenue by the player for the period 2015-2020. It also offers detailed analysis supported by reliable statistics on price and revenue (global level) by player for the period 2015-2020.
    The key players covered in this study
    Palantier
    MathWorks
    Alteryx
    SAS
    Databricks
    TIBCO Software
    Dataiku
    H2O.ai
    IBM
    Microsoft
    Google
    KNIME
    DataRobot
    RapidMiner
    Anaconda
    Domino

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