Global Automated Data Science and Machine Learning Platforms Market Size, Status and Forecast 2020-2026
1 Report Overview
- 1.1 Study Scope
- 1.2 Key Market Segments
- 1.3 Market Analysis by Type
- 1.3.1 Global Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Market Perspective (2015-2026)
- 2.2 Automated Data Science and Machine Learning Platforms Growth Trends by Regions
- 2.2.1 Automated Data Science and Machine Learning Platforms Market Size by Regions: 2015 VS 2020 VS 2026
- 2.2.2 Automated Data Science and Machine Learning Platforms Historic Market Share by Regions (2015-2020)
- 2.2.3 Automated Data Science and Machine Learning Platforms Forecasted Market Size by Regions (2021-2026)
- 2.3 Automated Data Science and Machine Learning Platforms Industry Dynamic
- 2.3.1 Automated Data Science and Machine Learning Platforms Market Trends
- 2.3.2 Automated Data Science and Machine Learning Platforms Market Drivers
- 2.3.3 Automated Data Science and Machine Learning Platforms Market Challenges
- 2.3.4 Automated Data Science and Machine Learning Platforms Market Restraints
3 Competition Landscape by Key Players
- 3.1 Global Top Automated Data Science and Machine Learning Platforms Players by Market Size
- 3.1.1 Global Top Automated Data Science and Machine Learning Platforms Players by Revenue (2015-2020)
- 3.1.2 Global Automated Data Science and Machine Learning Platforms Revenue Market Share by Players (2015-2020)
- 3.2 Global Automated Data Science and Machine Learning Platforms Market Share by Company Type (Tier 1, Tier 2 and Tier 3)
- 3.3 Players Covered: Ranking by Automated Data Science and Machine Learning Platforms Revenue
- 3.4 Global Automated Data Science and Machine Learning Platforms Market Concentration Ratio
- 3.4.1 Global Automated Data Science and Machine Learning Platforms Market Concentration Ratio (CR5 and HHI)
- 3.4.2 Global Top 10 and Top 5 Companies by Automated Data Science and Machine Learning Platforms Revenue in 2019
- 3.5 Key Players Automated Data Science and Machine Learning Platforms Area Served
- 3.6 Key Players Automated Data Science and Machine Learning Platforms Product Solution and Service
- 3.7 Date of Enter into Automated Data Science and Machine Learning Platforms Market
- 3.8 Mergers & Acquisitions, Expansion Plans
4 Automated Data Science and Machine Learning Platforms Breakdown Data by Type
- 4.1 Global Automated Data Science and Machine Learning Platforms Historic Market Size by Type (2015-2020)
- 4.2 Global Automated Data Science and Machine Learning Platforms Forecasted Market Size by Type (2021-2026)
5 Automated Data Science and Machine Learning Platforms Breakdown Data by Application
- 5.1 Global Automated Data Science and Machine Learning Platforms Historic Market Size by Application (2015-2020)
- 5.2 Global Automated Data Science and Machine Learning Platforms Forecasted Market Size by Application (2021-2026)
6 North America
- 6.1 North America Automated Data Science and Machine Learning Platforms Market Size (2015-2026)
- 6.2 North America Automated Data Science and Machine Learning Platforms Market Size by Type (2015-2020)
- 6.3 North America Automated Data Science and Machine Learning Platforms Market Size by Application (2015-2020)
- 6.4 North America Automated Data Science and Machine Learning Platforms Market Size by Country (2015-2020)
- 6.4.1 United States
- 6.4.2 Canada
7 Europe
- 7.1 Europe Automated Data Science and Machine Learning Platforms Market Size (2015-2026)
- 7.2 Europe Automated Data Science and Machine Learning Platforms Market Size by Type (2015-2020)
- 7.3 Europe Automated Data Science and Machine Learning Platforms Market Size by Application (2015-2020)
- 7.4 Europe Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Market Size (2015-2026)
- 8.2 Asia-Pacific Automated Data Science and Machine Learning Platforms Market Size by Type (2015-2020)
- 8.3 Asia-Pacific Automated Data Science and Machine Learning Platforms Market Size by Application (2015-2020)
- 8.4 Asia-Pacific Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Market Size (2015-2026)
- 9.2 Latin America Automated Data Science and Machine Learning Platforms Market Size by Type (2015-2020)
- 9.3 Latin America Automated Data Science and Machine Learning Platforms Market Size by Application (2015-2020)
- 9.4 Latin America Automated Data Science and Machine Learning Platforms Market Size by Country (2015-2020)
- 9.4.1 Mexico
- 9.4.2 Brazil
10 Middle East & Africa
- 10.1 Middle East & Africa Automated Data Science and Machine Learning Platforms Market Size (2015-2026)
- 10.2 Middle East & Africa Automated Data Science and Machine Learning Platforms Market Size by Type (2015-2020)
- 10.3 Middle East & Africa Automated Data Science and Machine Learning Platforms Market Size by Application (2015-2020)
- 10.4 Middle East & Africa Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 11.1.4 Palantier Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 11.2.4 MathWorks Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 11.3.4 Alteryx Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 11.4.4 SAS Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 11.5.4 Databricks Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 11.6.4 TIBCO Software Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 11.7.4 Dataiku Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 11.8.4 H2O.ai Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 11.9.4 IBM Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 11.10.4 Microsoft Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 10.11.4 Google Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 10.12.4 KNIME Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 10.13.4 DataRobot Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 10.14.4 RapidMiner Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 10.15.4 Anaconda Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 10.16.4 Domino Revenue in Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning Platforms Introduction
- 10.17.4 Altair Revenue in Automated Data Science and Machine Learning 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
Automated Data Science and Machine Learning Platforms market is segmented by company, region (country), by Type, and by Application. Players, stakeholders, and other participants in the global Automated 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.
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 Automated Data Science and Machine Learning 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 Automated Data Science and Machine Learning 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