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Global Data Science and Machine-Learning 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 Players Covered: Ranking by Data Science and Machine-Learning Platforms Revenue
  • 1.4 Market by Type
    • 1.4.1 Global Data Science and Machine-Learning Platforms Market Size Growth Rate by Type: 2020 VS 2026
    • 1.4.2 Open Source Data Integration Tools
    • 1.4.3 Cloud-based Data Integration Tools
  • 1.5 Market by Application
    • 1.5.1 Global Data Science and Machine-Learning Platforms Market Share by Application: 2020 VS 2026
    • 1.5.2 Small-Sized Enterprises
    • 1.5.3 Medium-Sized Enterprise
    • 1.5.4 Large Enterprises
  • 1.6 Study Objectives
  • 1.7 Years Considered

2 Global Growth Trends

  • 2.1 Global Data Science and Machine-Learning Platforms Market Perspective (2015-2026)
  • 2.2 Global Data Science and Machine-Learning Platforms Growth Trends by Regions
    • 2.2.1 Data Science and Machine-Learning Platforms Market Size by Regions: 2015 VS 2020 VS 2026
    • 2.2.2 Data Science and Machine-Learning Platforms Historic Market Share by Regions (2015-2020)
    • 2.2.3 Data Science and Machine-Learning Platforms Forecasted Market Size by Regions (2021-2026)
  • 2.3 Industry Trends and Growth Strategy
    • 2.3.1 Market Top Trends
    • 2.3.2 Market Drivers
    • 2.3.3 Market Challenges
    • 2.3.4 Porter’s Five Forces Analysis
    • 2.3.5 Data Science and Machine-Learning Platforms Market Growth Strategy
    • 2.3.6 Primary Interviews with Key Data Science and Machine-Learning Platforms Players (Opinion Leaders)

3 Competition Landscape by Key Players

  • 3.1 Global Top Data Science and Machine-Learning Platforms Players by Market Size
    • 3.1.1 Global Top Data Science and Machine-Learning Platforms Players by Revenue (2015-2020)
    • 3.1.2 Global Data Science and Machine-Learning Platforms Revenue Market Share by Players (2015-2020)
    • 3.1.3 Global Data Science and Machine-Learning Platforms Market Share by Company Type (Tier 1, Tier 2 and Tier 3)
  • 3.2 Global Data Science and Machine-Learning Platforms Market Concentration Ratio
    • 3.2.1 Global Data Science and Machine-Learning Platforms Market Concentration Ratio (CR5 and HHI)
    • 3.2.2 Global Top 10 and Top 5 Companies by Data Science and Machine-Learning Platforms Revenue in 2019
  • 3.3 Data Science and Machine-Learning Platforms Key Players Head office and Area Served
  • 3.4 Key Players Data Science and Machine-Learning Platforms Product Solution and Service
  • 3.5 Date of Enter into Data Science and Machine-Learning Platforms Market
  • 3.6 Mergers & Acquisitions, Expansion Plans

4 Market Size by Type (2015-2026)

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

5 Market Size by Application (2015-2026)

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

6 North America

  • 6.1 North America Data Science and Machine-Learning Platforms Market Size (2015-2020)
  • 6.2 Data Science and Machine-Learning Platforms Key Players in North America (2019-2020)
  • 6.3 North America Data Science and Machine-Learning Platforms Market Size by Type (2015-2020)
  • 6.4 North America Data Science and Machine-Learning Platforms Market Size by Application (2015-2020)

7 Europe

  • 7.1 Europe Data Science and Machine-Learning Platforms Market Size (2015-2020)
  • 7.2 Data Science and Machine-Learning Platforms Key Players in Europe (2019-2020)
  • 7.3 Europe Data Science and Machine-Learning Platforms Market Size by Type (2015-2020)
  • 7.4 Europe Data Science and Machine-Learning Platforms Market Size by Application (2015-2020)

8 China

  • 8.1 China Data Science and Machine-Learning Platforms Market Size (2015-2020)
  • 8.2 Data Science and Machine-Learning Platforms Key Players in China (2019-2020)
  • 8.3 China Data Science and Machine-Learning Platforms Market Size by Type (2015-2020)
  • 8.4 China Data Science and Machine-Learning Platforms Market Size by Application (2015-2020)

9 Japan

  • 9.1 Japan Data Science and Machine-Learning Platforms Market Size (2015-2020)
  • 9.2 Data Science and Machine-Learning Platforms Key Players in Japan (2019-2020)
  • 9.3 Japan Data Science and Machine-Learning Platforms Market Size by Type (2015-2020)
  • 9.4 Japan Data Science and Machine-Learning Platforms Market Size by Application (2015-2020)

10 Southeast Asia

  • 10.1 Southeast Asia Data Science and Machine-Learning Platforms Market Size (2015-2020)
  • 10.2 Data Science and Machine-Learning Platforms Key Players in Southeast Asia (2019-2020)
  • 10.3 Southeast Asia Data Science and Machine-Learning Platforms Market Size by Type (2015-2020)
  • 10.4 Southeast Asia Data Science and Machine-Learning Platforms Market Size by Application (2015-2020)

11 India

  • 11.1 India Data Science and Machine-Learning Platforms Market Size (2015-2020)
  • 11.2 Data Science and Machine-Learning Platforms Key Players in India (2019-2020)
  • 11.3 India Data Science and Machine-Learning Platforms Market Size by Type (2015-2020)
  • 11.4 India Data Science and Machine-Learning Platforms Market Size by Application (2015-2020)

12 Central & South America

  • 12.1 Central & South America Data Science and Machine-Learning Platforms Market Size (2015-2020)
  • 12.2 Data Science and Machine-Learning Platforms Key Players in Central & South America (2019-2020)
  • 12.3 Central & South America Data Science and Machine-Learning Platforms Market Size by Type (2015-2020)
  • 12.4 Central & South America Data Science and Machine-Learning Platforms Market Size by Application (2015-2020)

13 Key Players Profiles

  • 13.1 SAS
    • 13.1.1 SAS Company Details
    • 13.1.2 SAS Business Overview
    • 13.1.3 SAS Data Science and Machine-Learning Platforms Introduction
    • 13.1.4 SAS Revenue in Data Science and Machine-Learning Platforms Business (2015-2020))
    • 13.1.5 SAS Recent Development
  • 13.2 Alteryx
    • 13.2.1 Alteryx Company Details
    • 13.2.2 Alteryx Business Overview
    • 13.2.3 Alteryx Data Science and Machine-Learning Platforms Introduction
    • 13.2.4 Alteryx Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 13.2.5 Alteryx Recent Development
  • 13.3 IBM
    • 13.3.1 IBM Company Details
    • 13.3.2 IBM Business Overview
    • 13.3.3 IBM Data Science and Machine-Learning Platforms Introduction
    • 13.3.4 IBM Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 13.3.5 IBM Recent Development
  • 13.4 RapidMiner
    • 13.4.1 RapidMiner Company Details
    • 13.4.2 RapidMiner Business Overview
    • 13.4.3 RapidMiner Data Science and Machine-Learning Platforms Introduction
    • 13.4.4 RapidMiner Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 13.4.5 RapidMiner Recent Development
  • 13.5 KNIME
    • 13.5.1 KNIME Company Details
    • 13.5.2 KNIME Business Overview
    • 13.5.3 KNIME Data Science and Machine-Learning Platforms Introduction
    • 13.5.4 KNIME Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 13.5.5 KNIME Recent Development
  • 13.6 Microsoft
    • 13.6.1 Microsoft Company Details
    • 13.6.2 Microsoft Business Overview
    • 13.6.3 Microsoft Data Science and Machine-Learning Platforms Introduction
    • 13.6.4 Microsoft Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 13.6.5 Microsoft Recent Development
  • 13.7 Dataiku
    • 13.7.1 Dataiku Company Details
    • 13.7.2 Dataiku Business Overview
    • 13.7.3 Dataiku Data Science and Machine-Learning Platforms Introduction
    • 13.7.4 Dataiku Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 13.7.5 Dataiku Recent Development
  • 13.8 Databricks
    • 13.8.1 Databricks Company Details
    • 13.8.2 Databricks Business Overview
    • 13.8.3 Databricks Data Science and Machine-Learning Platforms Introduction
    • 13.8.4 Databricks Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 13.8.5 Databricks Recent Development
  • 13.9 TIBCO Software
    • 13.9.1 TIBCO Software Company Details
    • 13.9.2 TIBCO Software Business Overview
    • 13.9.3 TIBCO Software Data Science and Machine-Learning Platforms Introduction
    • 13.9.4 TIBCO Software Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 13.9.5 TIBCO Software Recent Development
  • 13.10 MathWorks
    • 13.10.1 MathWorks Company Details
    • 13.10.2 MathWorks Business Overview
    • 13.10.3 MathWorks Data Science and Machine-Learning Platforms Introduction
    • 13.10.4 MathWorks Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 13.10.5 MathWorks Recent Development
  • 13.11 H20.ai
    • 10.11.1 H20.ai Company Details
    • 10.11.2 H20.ai Business Overview
    • 10.11.3 H20.ai Data Science and Machine-Learning Platforms Introduction
    • 10.11.4 H20.ai Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 10.11.5 H20.ai Recent Development
  • 13.12 Anaconda
    • 10.12.1 Anaconda Company Details
    • 10.12.2 Anaconda Business Overview
    • 10.12.3 Anaconda Data Science and Machine-Learning Platforms Introduction
    • 10.12.4 Anaconda Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 10.12.5 Anaconda Recent Development
  • 13.13 SAP
    • 10.13.1 SAP Company Details
    • 10.13.2 SAP Business Overview
    • 10.13.3 SAP Data Science and Machine-Learning Platforms Introduction
    • 10.13.4 SAP Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 10.13.5 SAP Recent Development
  • 13.14 Google
    • 10.14.1 Google Company Details
    • 10.14.2 Google Business Overview
    • 10.14.3 Google Data Science and Machine-Learning Platforms Introduction
    • 10.14.4 Google Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 10.14.5 Google Recent Development
  • 13.15 Domino Data Lab
    • 10.15.1 Domino Data Lab Company Details
    • 10.15.2 Domino Data Lab Business Overview
    • 10.15.3 Domino Data Lab Data Science and Machine-Learning Platforms Introduction
    • 10.15.4 Domino Data Lab Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 10.15.5 Domino Data Lab Recent Development
  • 13.16 Angoss
    • 10.16.1 Angoss Company Details
    • 10.16.2 Angoss Business Overview
    • 10.16.3 Angoss Data Science and Machine-Learning Platforms Introduction
    • 10.16.4 Angoss Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 10.16.5 Angoss Recent Development
  • 13.17 Lexalytics
    • 10.17.1 Lexalytics Company Details
    • 10.17.2 Lexalytics Business Overview
    • 10.17.3 Lexalytics Data Science and Machine-Learning Platforms Introduction
    • 10.17.4 Lexalytics Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 10.17.5 Lexalytics Recent Development
  • 13.18 Rapid Insight
    • 10.18.1 Rapid Insight Company Details
    • 10.18.2 Rapid Insight Business Overview
    • 10.18.3 Rapid Insight Data Science and Machine-Learning Platforms Introduction
    • 10.18.4 Rapid Insight Revenue in Data Science and Machine-Learning Platforms Business (2015-2020)
    • 10.18.5 Rapid Insight Recent Development

14 Analyst's Viewpoints/Conclusions

    15 Appendix

    • 15.1 Research Methodology
      • 15.1.1 Methodology/Research Approach
      • 15.1.2 Data Source
    • 15.2 Disclaimer

    Data Science and Machine-Learning Platforms market is segmented by Type, and by Application. Players, stakeholders, and other participants in the global Data Science and Machine-Learning 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.

    The key players covered in this study
    SAS
    Alteryx
    IBM
    RapidMiner
    KNIME
    Microsoft
    Dataiku
    Databricks
    TIBCO Software
    MathWorks
    H20.ai
    Anaconda
    SAP
    Google
    Domino Data Lab
    Angoss
    Lexalytics
    Rapid Insight

    Market segment by Type, the product can be split into
    Open Source Data Integration Tools
    Cloud-based Data Integration Tools
    Market segment by Application, split into
    Small-Sized Enterprises
    Medium-Sized Enterprise
    Large Enterprises

    Market segment by Regions/Countries, this report covers
    North America
    Europe
    China
    Japan
    Southeast Asia
    India
    Central & South America

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