Global Data Science and Machine Learning Platforms Market by Type (Open Source Data Integration Tools, Cloud-based Data Integration Tools), By Application (Small-Sized Enterprises, Medium-Sized Enterprise, Large Enterprises) and Region (North America, Latin America, Europe, Asia Pacific and Middle East & Africa), Forecast To 2028
Up Market Research published a new report titled “Data Science and Machine Learning Platforms Market research report which is segmented by Types (Open Source Data Integration Tools, Cloud-based Data Integration Tools), By Applications (Small-Sized Enterprises, Medium-Sized Enterprise, Large Enterprises), By Players/Companies SAS, Alteryx, IBM, RapidMiner, KNIME, Microsoft, Dataiku, Databricks, TIBCO Software, MathWorks, H20.ai, Anaconda, SAP, Google, Domino Data Lab, Angoss, Lexalytics, Rapid Insight”. As per the study the market is expected to grow at a CAGR of XX% in the forecast period.
Report Scope
| Report Attributes | Report Details |
| Report Title | Data Science and Machine Learning Platforms Market Research Report |
| By Type | Open Source Data Integration Tools, Cloud-based Data Integration Tools |
| By Application | Small-Sized Enterprises, Medium-Sized Enterprise, Large Enterprises |
| By Companies | SAS, Alteryx, IBM, RapidMiner, KNIME, Microsoft, Dataiku, Databricks, TIBCO Software, MathWorks, H20.ai, Anaconda, SAP, Google, Domino Data Lab, Angoss, Lexalytics, Rapid Insight |
| Regions Covered | North America, Europe, APAC, Latin America, MEA |
| Base Year | 2020 |
| Historical Year | 2018 to 2019 (Data from 2010 can be provided as per availability) |
| Forecast Year | 2028 |
| Number of Pages | 241 |
| Number of Tables & Figures | 169 |
| Customization Available | Yes, the report can be customized as per your need. |
The report covers comprehensive data on emerging trends, market drivers, growth opportunities, and restraints that can change the market dynamics of the industry. It provides an in-depth analysis of the market segments which include products, applications, and competitor analysis.
Global Data Science and Machine Learning Platforms Market Report Segments:
The market is segmented by Type Open Source Data Integration Tools, Cloud-based Data Integration Tools and By Application Small-Sized Enterprises, Medium-Sized Enterprise, Large Enterprises.
Some of the companies that are profiled in this report are:
- SAS
- Alteryx
- IBM
- RapidMiner
- KNIME
- Microsoft
- Dataiku
- Databricks
- TIBCO Software
- MathWorks
- H20.ai
- Anaconda
- SAP
- Domino Data Lab
- Angoss
- Lexalytics
- Rapid Insight
Data Science and Machine Learning Platforms Market research report delivers a close watch on leading competitors with strategic analysis, micro and macro market trend and scenarios, pricing analysis and a holistic overview of the market situations in the forecast period. It is a professional and a detailed report focusing on primary and secondary drivers, market share, leading segments and geographical analysis. Further, key players, major collaborations, merger & acquisitions along with trending innovation and business policies are reviewed in the report.
Key Benefits for Industry Participants & Stakeholders:
- Industry drivers, restraints, and opportunities covered in the study
- Neutral perspective on the market performance
- Recent industry trends and developments
- Competitive landscape & strategies of key players
- Potential & niche segments and regions exhibiting promising growth covered
- Historical, current, and projected market size, in terms of value
- In-depth analysis of the Data Science and Machine Learning Platforms Market
Overview of the regional outlook of the Data Science and Machine Learning Platforms Market:
Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa (MEA). North America region is further bifurcated into countries such as U.S., and Canada. The Europe region is further categorized into U.K., France, Germany, Italy, Spain, Russia, and Rest of Europe. Asia Pacific is further segmented into China, Japan, South Korea, India, Australia, South East Asia, and Rest of Asia Pacific. Latin America region is further segmented into Brazil, Mexico, and Rest of Latin America, and the MEA region is further divided into GCC, Turkey, South Africa, and Rest of MEA.
Highlights of The Data Science and Machine Learning Platforms Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of Data Science and Machine Learning Platforms Market.
- Historical data and forecast.
- Estimations for the forecast period 2028.
- Developments and trends in the market.
- By Type:
1. Open Source Data Integration Tools
2. Cloud-based Data Integration Tools
7. By Application:1. Small-Sized Enterprises
2. Medium-Sized Enterprise
3. Large Enterprises
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Data Science and Machine Learning Platforms Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2028.
How you may use our products:
- Correctly Positioning New Products
- Market Entry Strategies
- Business Expansion Strategies
- Consumer Insights
- Understanding Competition Scenario
- Product & Brand Management
- Channel & Customer Management
- Identifying Appropriate Advertising Appeals
Reasons to Purchase the Data Science and Machine Learning Platforms Market Report:
- The report includes a plethora of information such as market dynamics scenario and opportunities during the forecast period
- Segments and sub-segments include quantitative, qualitative, value (USD Million,) and volume (Units Million) data.
- Regional, sub-regional, and country level data includes the demand and supply forces along with their influence on the market.
- The competitive landscape comprises share of key players, new developments, and strategies in the last three years.
- Comprehensive companies offering products, relevant financial information, recent developments, SWOT analysis, and strategies by these players.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Data Science and Machine Learning Platforms Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Data Science and Machine Learning Platforms Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Data Science and Machine Learning Platforms Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Data Science and Machine Learning Platforms Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Data Science and Machine Learning Platforms Market Size & Forecast, 2018-2028
4.5.1 Data Science and Machine Learning Platforms Market Size and Y-o-Y Growth
4.5.2 Data Science and Machine Learning Platforms Market Absolute $ Opportunity
Chapter 5 Global Data Science and Machine Learning Platforms Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Data Science and Machine Learning Platforms Market Size Forecast by Type
5.2.1 Open Source Data Integration Tools
5.2.2 Cloud-based Data Integration Tools
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Data Science and Machine Learning Platforms Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Data Science and Machine Learning Platforms Market Size Forecast by Applications
6.2.1 Small-Sized Enterprises
6.2.2 Medium-Sized Enterprise
6.2.3 Large Enterprises
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Data Science and Machine Learning Platforms Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Data Science and Machine Learning Platforms Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Data Science and Machine Learning Platforms Analysis and Forecast
9.1 Introduction
9.2 North America Data Science and Machine Learning Platforms Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Data Science and Machine Learning Platforms Market Size Forecast by Type
9.6.1 Open Source Data Integration Tools
9.6.2 Cloud-based Data Integration Tools
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Data Science and Machine Learning Platforms Market Size Forecast by Applications
9.10.1 Small-Sized Enterprises
9.10.2 Medium-Sized Enterprise
9.10.3 Large Enterprises
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Data Science and Machine Learning Platforms Analysis and Forecast
10.1 Introduction
10.2 Europe Data Science and Machine Learning Platforms Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Data Science and Machine Learning Platforms Market Size Forecast by Type
10.6.1 Open Source Data Integration Tools
10.6.2 Cloud-based Data Integration Tools
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Data Science and Machine Learning Platforms Market Size Forecast by Applications
10.10.1 Small-Sized Enterprises
10.10.2 Medium-Sized Enterprise
10.10.3 Large Enterprises
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Data Science and Machine Learning Platforms Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Data Science and Machine Learning Platforms Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Data Science and Machine Learning Platforms Market Size Forecast by Type
11.6.1 Open Source Data Integration Tools
11.6.2 Cloud-based Data Integration Tools
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Data Science and Machine Learning Platforms Market Size Forecast by Applications
11.10.1 Small-Sized Enterprises
11.10.2 Medium-Sized Enterprise
11.10.3 Large Enterprises
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Data Science and Machine Learning Platforms Analysis and Forecast
12.1 Introduction
12.2 Latin America Data Science and Machine Learning Platforms Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Data Science and Machine Learning Platforms Market Size Forecast by Type
12.6.1 Open Source Data Integration Tools
12.6.2 Cloud-based Data Integration Tools
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Data Science and Machine Learning Platforms Market Size Forecast by Applications
12.10.1 Small-Sized Enterprises
12.10.2 Medium-Sized Enterprise
12.10.3 Large Enterprises
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Data Science and Machine Learning Platforms Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Data Science and Machine Learning Platforms Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Data Science and Machine Learning Platforms Market Size Forecast by Type
13.6.1 Open Source Data Integration Tools
13.6.2 Cloud-based Data Integration Tools
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Data Science and Machine Learning Platforms Market Size Forecast by Applications
13.10.1 Small-Sized Enterprises
13.10.2 Medium-Sized Enterprise
13.10.3 Large Enterprises
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Data Science and Machine Learning Platforms Market: Competitive Dashboard
14.2 Global Data Science and Machine Learning Platforms Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 SAS
14.3.2 Alteryx
14.3.3 IBM
14.3.4 RapidMiner
14.3.5 KNIME
14.3.6 Microsoft
14.3.7 Dataiku
14.3.8 Databricks
14.3.9 TIBCO Software
14.3.10 MathWorks
14.3.11 H20.ai
14.3.12 Anaconda
14.3.13 SAP
14.3.14 Google
14.3.15 Domino Data Lab
14.3.16 Angoss
14.3.17 Lexalytics
14.3.18 Rapid Insight
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Data Science and Machine Learning Platforms Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Data Science and Machine Learning Platforms Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Data Science and Machine Learning Platforms Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Data Science and Machine Learning Platforms Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Data Science and Machine Learning Platforms Market Size & Forecast, 2018-2028
4.5.1 Data Science and Machine Learning Platforms Market Size and Y-o-Y Growth
4.5.2 Data Science and Machine Learning Platforms Market Absolute $ Opportunity
Chapter 5 Global Data Science and Machine Learning Platforms Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Data Science and Machine Learning Platforms Market Size Forecast by Type
5.2.1 Open Source Data Integration Tools
5.2.2 Cloud-based Data Integration Tools
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Data Science and Machine Learning Platforms Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Data Science and Machine Learning Platforms Market Size Forecast by Applications
6.2.1 Small-Sized Enterprises
6.2.2 Medium-Sized Enterprise
6.2.3 Large Enterprises
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Data Science and Machine Learning Platforms Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Data Science and Machine Learning Platforms Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Data Science and Machine Learning Platforms Analysis and Forecast
9.1 Introduction
9.2 North America Data Science and Machine Learning Platforms Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Data Science and Machine Learning Platforms Market Size Forecast by Type
9.6.1 Open Source Data Integration Tools
9.6.2 Cloud-based Data Integration Tools
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Data Science and Machine Learning Platforms Market Size Forecast by Applications
9.10.1 Small-Sized Enterprises
9.10.2 Medium-Sized Enterprise
9.10.3 Large Enterprises
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Data Science and Machine Learning Platforms Analysis and Forecast
10.1 Introduction
10.2 Europe Data Science and Machine Learning Platforms Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Data Science and Machine Learning Platforms Market Size Forecast by Type
10.6.1 Open Source Data Integration Tools
10.6.2 Cloud-based Data Integration Tools
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Data Science and Machine Learning Platforms Market Size Forecast by Applications
10.10.1 Small-Sized Enterprises
10.10.2 Medium-Sized Enterprise
10.10.3 Large Enterprises
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Data Science and Machine Learning Platforms Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Data Science and Machine Learning Platforms Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Data Science and Machine Learning Platforms Market Size Forecast by Type
11.6.1 Open Source Data Integration Tools
11.6.2 Cloud-based Data Integration Tools
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Data Science and Machine Learning Platforms Market Size Forecast by Applications
11.10.1 Small-Sized Enterprises
11.10.2 Medium-Sized Enterprise
11.10.3 Large Enterprises
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Data Science and Machine Learning Platforms Analysis and Forecast
12.1 Introduction
12.2 Latin America Data Science and Machine Learning Platforms Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Data Science and Machine Learning Platforms Market Size Forecast by Type
12.6.1 Open Source Data Integration Tools
12.6.2 Cloud-based Data Integration Tools
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Data Science and Machine Learning Platforms Market Size Forecast by Applications
12.10.1 Small-Sized Enterprises
12.10.2 Medium-Sized Enterprise
12.10.3 Large Enterprises
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Data Science and Machine Learning Platforms Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Data Science and Machine Learning Platforms Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Data Science and Machine Learning Platforms Market Size Forecast by Type
13.6.1 Open Source Data Integration Tools
13.6.2 Cloud-based Data Integration Tools
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Data Science and Machine Learning Platforms Market Size Forecast by Applications
13.10.1 Small-Sized Enterprises
13.10.2 Medium-Sized Enterprise
13.10.3 Large Enterprises
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Data Science and Machine Learning Platforms Market: Competitive Dashboard
14.2 Global Data Science and Machine Learning Platforms Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 SAS
14.3.2 Alteryx
14.3.3 IBM
14.3.4 RapidMiner
14.3.5 KNIME
14.3.6 Microsoft
14.3.7 Dataiku
14.3.8 Databricks
14.3.9 TIBCO Software
14.3.10 MathWorks
14.3.11 H20.ai
14.3.12 Anaconda
14.3.13 SAP
14.3.14 Google
14.3.15 Domino Data Lab
14.3.16 Angoss
14.3.17 Lexalytics
14.3.18 Rapid Insight
Segments Covered in the Report
The global Data Science and Machine Learning Platforms market has been segmented based on
By Types
The global Data Science and Machine Learning Platforms market has been segmented based on
By Types
- Open Source Data Integration Tools
- Cloud-based Data Integration Tools
- Small-Sized Enterprises
- Medium-Sized Enterprise
- Large Enterprises
- Asia Pacific
- North America
- Latin America
- Europe
- Middle East & Africa
- SAS
- Alteryx
- IBM
- RapidMiner
- KNIME
- Microsoft
- Dataiku
- Databricks
- TIBCO Software
- MathWorks
- H20.ai
- Anaconda
- SAP
- Domino Data Lab
- Angoss
- Lexalytics
- Rapid Insight
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