The Market Reports
Call: +1-631-407-1315 / +91-750-729-1479
Email: sales@themarketreports.com
Data Science and Machine-Learning Platforms-Global Market Insights and Sales Trends 2025
Synopsis
The global Data Science and Machine-Learning Platforms market size is expected to reach US$ million by 2029, growing at a CAGR of % from 2023 to 2029. The market is mainly driven by the significant applications of Data Science and Machine-Learning Platforms in various end use industries. The expanding demands from the Small-Sized Enterprises, Medium-Sized Enterprise and Large Enterprises,, are propelling Data Science and Machine-Learning Platforms market. Open Source Data Integration Tools, one of the segments analysed in this report, is projected to record % CAGR and reach US$ million by the end of the analysis period. Growth in the Cloud-based Data Integration Tools segment is estimated at % CAGR for the next seven-year period.
Asia Pacific shows high growth potential for Data Science and Machine-Learning Platforms market, driven by demand from China, the second largest economy with some signs of stabilising, the Data Science and Machine-Learning Platforms market in China is forecast to reach US$ million by 2029, trailing a CAGR of % over the 2023-2029 period, while the U.S. market will reach US$ million by 2029, exhibiting a CAGR of % during the same period.
Report Objectives
This report provides market insight on the different segments, by players, by Type, by Application. Market size and forecast (2018-2029) has been provided in the report. The primary objectives of this report are to provide 1) global market size and forecasts, growth rates, market dynamics, industry structure and developments, market situation, trends; 2) global market share and ranking by company; 3) comprehensive presentation of the global market for Data Science and Machine-Learning Platforms, with both quantitative and qualitative analysis through detailed segmentation; 4) detailed value chain analysis and review of growth factors essential for the existing market players and new entrants; 5) emerging opportunities in the market and the future impact of major drivers and restraints of the market.
Key Features of The Study:
This report provides in-depth analysis of the global Data Science and Machine-Learning Platforms market, and provides market size (US$ million) and CAGR for the forecast period (2023-2029), considering 2022 as the base year.
This report profiles key players in the global Data Science and Machine-Learning Platforms market based on the following parameters - company details (found date, headquarters, manufacturing bases), products portfolio, Data Science and Machine-Learning Platforms sales data, market share and ranking.
This report elucidates potential market opportunities across different segments and explains attractive investment proposition matrices for this market.
This report illustrates key insights about market drivers, restraints, opportunities, market trends, regional outlook.
Key companies of Data Science and Machine-Learning Platforms covered in this report include SAS, Alteryx, IBM, RapidMiner, KNIME, Microsoft, Dataiku, Databricks and TIBCO Software, etc.
The global Data Science and Machine-Learning Platforms market report caters to various stakeholders in this industry including investors, suppliers, product players, distributors, new entrants, and financial analysts.
Market Segmentation
Company Profiles:
SAS
Alteryx
IBM
RapidMiner
KNIME
Microsoft
Dataiku
Databricks
TIBCO Software
MathWorks
H20.ai
Anaconda
SAP
Google
Domino Data Lab
Angoss
Lexalytics
Rapid Insight
Global Data Science and Machine-Learning Platforms market, by region:
North America (U.S., Canada, Mexico)
Europe (Germany, France, UK, Italy, etc.)
Asia Pacific (China, Japan, South Korea, Southeast Asia, India, etc.)
South America (Brazil, etc.)
Middle East and Africa (Turkey, GCC Countries, Africa, etc.)
Global Data Science and Machine-Learning Platforms market, Segment by Type:
Open Source Data Integration Tools
Cloud-based Data Integration Tools
Global Data Science and Machine-Learning Platforms market, by Application
Small-Sized Enterprises
Medium-Sized Enterprise
Large Enterprises
Core Chapters
Chapter One: Introduces the report scope of the report, executive summary of global and regional market size and CAGR for the history and forecast period (2018-2023, 2024-2029). It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter Two: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter Three: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter Four: Detailed analysis of Data Science and Machine-Learning Platforms companies’ competitive landscape, revenue, market share and ranking, latest development plan, merger, and acquisition information, etc.
Chapter Five: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product introduction, revenue, recent development, etc.
Chapter Six, Seven, Eight, Nine and Ten: North America, Europe, Asia Pacific, Latin America, Middle East & Africa, revenue by country.
Chapter Eleven: this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter Twelve: Research Finding/Conclusion
The global Data Science and Machine-Learning Platforms market size is expected to reach US$ million by 2029, growing at a CAGR of % from 2023 to 2029. The market is mainly driven by the significant applications of Data Science and Machine-Learning Platforms in various end use industries. The expanding demands from the Small-Sized Enterprises, Medium-Sized Enterprise and Large Enterprises,, are propelling Data Science and Machine-Learning Platforms market. Open Source Data Integration Tools, one of the segments analysed in this report, is projected to record % CAGR and reach US$ million by the end of the analysis period. Growth in the Cloud-based Data Integration Tools segment is estimated at % CAGR for the next seven-year period.
Asia Pacific shows high growth potential for Data Science and Machine-Learning Platforms market, driven by demand from China, the second largest economy with some signs of stabilising, the Data Science and Machine-Learning Platforms market in China is forecast to reach US$ million by 2029, trailing a CAGR of % over the 2023-2029 period, while the U.S. market will reach US$ million by 2029, exhibiting a CAGR of % during the same period.
Report Objectives
This report provides market insight on the different segments, by players, by Type, by Application. Market size and forecast (2018-2029) has been provided in the report. The primary objectives of this report are to provide 1) global market size and forecasts, growth rates, market dynamics, industry structure and developments, market situation, trends; 2) global market share and ranking by company; 3) comprehensive presentation of the global market for Data Science and Machine-Learning Platforms, with both quantitative and qualitative analysis through detailed segmentation; 4) detailed value chain analysis and review of growth factors essential for the existing market players and new entrants; 5) emerging opportunities in the market and the future impact of major drivers and restraints of the market.
Key Features of The Study:
This report provides in-depth analysis of the global Data Science and Machine-Learning Platforms market, and provides market size (US$ million) and CAGR for the forecast period (2023-2029), considering 2022 as the base year.
This report profiles key players in the global Data Science and Machine-Learning Platforms market based on the following parameters - company details (found date, headquarters, manufacturing bases), products portfolio, Data Science and Machine-Learning Platforms sales data, market share and ranking.
This report elucidates potential market opportunities across different segments and explains attractive investment proposition matrices for this market.
This report illustrates key insights about market drivers, restraints, opportunities, market trends, regional outlook.
Key companies of Data Science and Machine-Learning Platforms covered in this report include SAS, Alteryx, IBM, RapidMiner, KNIME, Microsoft, Dataiku, Databricks and TIBCO Software, etc.
The global Data Science and Machine-Learning Platforms market report caters to various stakeholders in this industry including investors, suppliers, product players, distributors, new entrants, and financial analysts.
Market Segmentation
Company Profiles:
SAS
Alteryx
IBM
RapidMiner
KNIME
Microsoft
Dataiku
Databricks
TIBCO Software
MathWorks
H20.ai
Anaconda
SAP
Domino Data Lab
Angoss
Lexalytics
Rapid Insight
Global Data Science and Machine-Learning Platforms market, by region:
North America (U.S., Canada, Mexico)
Europe (Germany, France, UK, Italy, etc.)
Asia Pacific (China, Japan, South Korea, Southeast Asia, India, etc.)
South America (Brazil, etc.)
Middle East and Africa (Turkey, GCC Countries, Africa, etc.)
Global Data Science and Machine-Learning Platforms market, Segment by Type:
Open Source Data Integration Tools
Cloud-based Data Integration Tools
Global Data Science and Machine-Learning Platforms market, by Application
Small-Sized Enterprises
Medium-Sized Enterprise
Large Enterprises
Core Chapters
Chapter One: Introduces the report scope of the report, executive summary of global and regional market size and CAGR for the history and forecast period (2018-2023, 2024-2029). It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter Two: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter Three: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter Four: Detailed analysis of Data Science and Machine-Learning Platforms companies’ competitive landscape, revenue, market share and ranking, latest development plan, merger, and acquisition information, etc.
Chapter Five: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product introduction, revenue, recent development, etc.
Chapter Six, Seven, Eight, Nine and Ten: North America, Europe, Asia Pacific, Latin America, Middle East & Africa, revenue by country.
Chapter Eleven: this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter Twelve: Research Finding/Conclusion
Index1 Market Overview of Data Science and Machine-Learning Platforms
1.1 Data Science and Machine-Learning Platforms Market Overview
1.1.1 Data Science and Machine-Learning Platforms Product Scope
1.1.2 Data Science and Machine-Learning Platforms Market Status and Outlook
1.2 Global Data Science and Machine-Learning Platforms Market Size Overview by Region 2018 VS 2022 VS 2029
1.3 Global Data Science and Machine-Learning Platforms Market Size by Region (2018-2029)
1.4 Global Data Science and Machine-Learning Platforms Historic Market Size by Region (2018-2023)
1.5 Global Data Science and Machine-Learning Platforms Market Size Forecast by Region (2024-2029)
1.6 Key Regions, Data Science and Machine-Learning Platforms Market Size (2018-2029)
1.6.1 North America Data Science and Machine-Learning Platforms Market Size (2018-2029)
1.6.2 Europe Data Science and Machine-Learning Platforms Market Size (2018-2029)
1.6.3 Asia-Pacific Data Science and Machine-Learning Platforms Market Size (2018-2029)
1.6.4 Latin America Data Science and Machine-Learning Platforms Market Size (2018-2029)
1.6.5 Middle East & Africa Data Science and Machine-Learning Platforms Market Size (2018-2029)
2 Data Science and Machine-Learning Platforms Market by Type
2.1 Introduction
2.1.1 Open Source Data Integration Tools
2.1.2 Cloud-based Data Integration Tools
2.2 Global Data Science and Machine-Learning Platforms Market Size by Type: 2018 VS 2022 VS 2029
2.2.1 Global Data Science and Machine-Learning Platforms Historic Market Size by Type (2018-2023)
2.2.2 Global Data Science and Machine-Learning Platforms Forecasted Market Size by Type (2024-2029)
2.3 Key Regions Market Size by Type
2.3.1 North America Data Science and Machine-Learning Platforms Revenue Breakdown by Type (2018-2029)
2.3.2 Europe Data Science and Machine-Learning Platforms Revenue Breakdown by Type (2018-2029)
2.3.3 Asia-Pacific Data Science and Machine-Learning Platforms Revenue Breakdown by Type (2018-2029)
2.3.4 Latin America Data Science and Machine-Learning Platforms Revenue Breakdown by Type (2018-2029)
2.3.5 Middle East and Africa Data Science and Machine-Learning Platforms Revenue Breakdown by Type (2018-2029)
3 Data Science and Machine-Learning Platforms Market Overview by Application
3.1 Introduction
3.1.1 Small-Sized Enterprises
3.1.2 Medium-Sized Enterprise
3.1.3 Large Enterprises
3.2 Global Data Science and Machine-Learning Platforms Market Size by Application: 2018 VS 2022 VS 2029
3.2.1 Global Data Science and Machine-Learning Platforms Historic Market Size by Application (2018-2023)
3.2.2 Global Data Science and Machine-Learning Platforms Forecasted Market Size by Application (2024-2029)
3.3 Key Regions Market Size by Application
3.3.1 North America Data Science and Machine-Learning Platforms Revenue Breakdown by Application (2018-2029)
3.3.2 Europe Data Science and Machine-Learning Platforms Revenue Breakdown by Application (2018-2029)
3.3.3 Asia-Pacific Data Science and Machine-Learning Platforms Revenue Breakdown by Application (2018-2029)
3.3.4 Latin America Data Science and Machine-Learning Platforms Revenue Breakdown by Application (2018-2029)
3.3.5 Middle East and Africa Data Science and Machine-Learning Platforms Revenue Breakdown by Application (2018-2029)
4 Data Science and Machine-Learning Platforms Competition Analysis by Players
4.1 Global Data Science and Machine-Learning Platforms Market Size by Players (2018-2023)
4.2 Global Top Players by Company Type (Tier 1, Tier 2 and Tier 3) & (based on the Revenue in Data Science and Machine-Learning Platforms as of 2022)
4.3 Date of Key Players Enter into Data Science and Machine-Learning Platforms Market
4.4 Global Top Players Data Science and Machine-Learning Platforms Headquarters and Area Served
4.5 Key Players Data Science and Machine-Learning Platforms Product Solution and Service
4.6 Competitive Status
4.6.1 Data Science and Machine-Learning Platforms Market Concentration Rate
4.6.2 Mergers & Acquisitions, Expansion Plans
5 Company (Top Players) Profiles
5.1 SAS
5.1.1 SAS Profile
5.1.2 SAS Main Business
5.1.3 SAS Data Science and Machine-Learning Platforms Products, Services and Solutions
5.1.4 SAS Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.1.5 SAS Recent Developments
5.2 Alteryx
5.2.1 Alteryx Profile
5.2.2 Alteryx Main Business
5.2.3 Alteryx Data Science and Machine-Learning Platforms Products, Services and Solutions
5.2.4 Alteryx Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.2.5 Alteryx Recent Developments
5.3 IBM
5.3.1 IBM Profile
5.3.2 IBM Main Business
5.3.3 IBM Data Science and Machine-Learning Platforms Products, Services and Solutions
5.3.4 IBM Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.3.5 RapidMiner Recent Developments
5.4 RapidMiner
5.4.1 RapidMiner Profile
5.4.2 RapidMiner Main Business
5.4.3 RapidMiner Data Science and Machine-Learning Platforms Products, Services and Solutions
5.4.4 RapidMiner Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.4.5 RapidMiner Recent Developments
5.5 KNIME
5.5.1 KNIME Profile
5.5.2 KNIME Main Business
5.5.3 KNIME Data Science and Machine-Learning Platforms Products, Services and Solutions
5.5.4 KNIME Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.5.5 KNIME Recent Developments
5.6 Microsoft
5.6.1 Microsoft Profile
5.6.2 Microsoft Main Business
5.6.3 Microsoft Data Science and Machine-Learning Platforms Products, Services and Solutions
5.6.4 Microsoft Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.6.5 Microsoft Recent Developments
5.7 Dataiku
5.7.1 Dataiku Profile
5.7.2 Dataiku Main Business
5.7.3 Dataiku Data Science and Machine-Learning Platforms Products, Services and Solutions
5.7.4 Dataiku Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.7.5 Dataiku Recent Developments
5.8 Databricks
5.8.1 Databricks Profile
5.8.2 Databricks Main Business
5.8.3 Databricks Data Science and Machine-Learning Platforms Products, Services and Solutions
5.8.4 Databricks Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.8.5 Databricks Recent Developments
5.9 TIBCO Software
5.9.1 TIBCO Software Profile
5.9.2 TIBCO Software Main Business
5.9.3 TIBCO Software Data Science and Machine-Learning Platforms Products, Services and Solutions
5.9.4 TIBCO Software Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.9.5 TIBCO Software Recent Developments
5.10 MathWorks
5.10.1 MathWorks Profile
5.10.2 MathWorks Main Business
5.10.3 MathWorks Data Science and Machine-Learning Platforms Products, Services and Solutions
5.10.4 MathWorks Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.10.5 MathWorks Recent Developments
5.11 H20.ai
5.11.1 H20.ai Profile
5.11.2 H20.ai Main Business
5.11.3 H20.ai Data Science and Machine-Learning Platforms Products, Services and Solutions
5.11.4 H20.ai Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.11.5 H20.ai Recent Developments
5.12 Anaconda
5.12.1 Anaconda Profile
5.12.2 Anaconda Main Business
5.12.3 Anaconda Data Science and Machine-Learning Platforms Products, Services and Solutions
5.12.4 Anaconda Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.12.5 Anaconda Recent Developments
5.13 SAP
5.13.1 SAP Profile
5.13.2 SAP Main Business
5.13.3 SAP Data Science and Machine-Learning Platforms Products, Services and Solutions
5.13.4 SAP Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.13.5 SAP Recent Developments
5.14 Google
5.14.1 Google Profile
5.14.2 Google Main Business
5.14.3 Google Data Science and Machine-Learning Platforms Products, Services and Solutions
5.14.4 Google Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.14.5 Google Recent Developments
5.15 Domino Data Lab
5.15.1 Domino Data Lab Profile
5.15.2 Domino Data Lab Main Business
5.15.3 Domino Data Lab Data Science and Machine-Learning Platforms Products, Services and Solutions
5.15.4 Domino Data Lab Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.15.5 Domino Data Lab Recent Developments
5.16 Angoss
5.16.1 Angoss Profile
5.16.2 Angoss Main Business
5.16.3 Angoss Data Science and Machine-Learning Platforms Products, Services and Solutions
5.16.4 Angoss Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.16.5 Angoss Recent Developments
5.17 Lexalytics
5.17.1 Lexalytics Profile
5.17.2 Lexalytics Main Business
5.17.3 Lexalytics Data Science and Machine-Learning Platforms Products, Services and Solutions
5.17.4 Lexalytics Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.17.5 Lexalytics Recent Developments
5.18 Rapid Insight
5.18.1 Rapid Insight Profile
5.18.2 Rapid Insight Main Business
5.18.3 Rapid Insight Data Science and Machine-Learning Platforms Products, Services and Solutions
5.18.4 Rapid Insight Data Science and Machine-Learning Platforms Revenue (US$ Million) & (2018-2023)
5.18.5 Rapid Insight Recent Developments
6 North America
6.1 North America Data Science and Machine-Learning Platforms Market Size by Country (2018-2029)
6.2 U.S.
6.3 Canada
7 Europe
7.1 Europe Data Science and Machine-Learning Platforms Market Size by Country (2018-2029)
7.2 Germany
7.3 France
7.4 U.K.
7.5 Italy
7.6 Russia
7.7 Nordic Countries
7.8 Rest of Europe
8 Asia-Pacific
8.1 Asia-Pacific Data Science and Machine-Learning Platforms Market Size by Region (2018-2029)
8.2 China
8.3 Japan
8.4 South Korea
8.5 Southeast Asia
8.6 India
8.7 Australia
8.8 Rest of Asia-Pacific
9 Latin America
9.1 Latin America Data Science and Machine-Learning Platforms Market Size by Country (2018-2029)
9.2 Mexico
9.3 Brazil
9.4 Rest of Latin America
10 Middle East & Africa
10.1 Middle East & Africa Data Science and Machine-Learning Platforms Market Size by Country (2018-2029)
10.2 Turkey
10.3 Saudi Arabia
10.4 UAE
10.5 Rest of Middle East & Africa
11 Data Science and Machine-Learning Platforms Market Dynamics
11.1 Data Science and Machine-Learning Platforms Industry Trends
11.2 Data Science and Machine-Learning Platforms Market Drivers
11.3 Data Science and Machine-Learning Platforms Market Challenges
11.4 Data Science and Machine-Learning Platforms Market Restraints
12 Research Finding /Conclusion
13 Methodology and Data Source
13.1 Methodology/Research Approach
13.1.1 Research Programs/Design
13.1.2 Market Size Estimation
13.1.3 Market Breakdown and Data Triangulation
13.2 Data Source
13.2.1 Secondary Sources
13.2.2 Primary Sources
13.3 Disclaimer
13.4 Author List
Published By : QY Research
Why ‘The Market Reports’
In Business:
Pre Sales Support:
Post Sales Support:
Turn Around Time:
Clients Served:
Clients Assisted:
Client Types:
Payment:
- Accept global payments [Credit Card / PayPal / Wire Transfer]
- Accept local payments in South Korea, Germany, China and India [Can pay in local currency]
Latest IT & Electronics Market Reports
Payments Accepted From
Connect with us at
Complete Secure Website
