Report Detail
Global Data Science and Machine-Learning Platforms Market 2024 by Company, Regions, Type and Application, Forecast to 2030
- RnM4592667 |
- 05 June, 2024 |
- Global |
- 127 Pages |
- GIR (Global Info Research) |
- Service & Software
According to our (Global Info Research) latest study, the global Data Science and Machine-Learning Platforms market size was valued at USD million in 2023 and is forecast to a readjusted size of USD million by 2030 with a CAGR of % during review period.
The Global Info Research report includes an overview of the development of the Data Science and Machine-Learning Platforms industry chain, the market status of Small-Sized Enterprises (Open Source Data Integration Tools, Cloud-based Data Integration Tools), Medium-Sized Enterprise (Open Source Data Integration Tools, Cloud-based Data Integration Tools), and key enterprises in developed and developing market, and analysed the cutting-edge technology, patent, hot applications and market trends of Data Science and Machine-Learning Platforms.
Regionally, the report analyzes the Data Science and Machine-Learning Platforms markets in key regions. North America and Europe are experiencing steady growth, driven by government initiatives and increasing consumer awareness. Asia-Pacific, particularly China, leads the global Data Science and Machine-Learning Platforms market, with robust domestic demand, supportive policies, and a strong manufacturing base.
Key Features:
The report presents comprehensive understanding of the Data Science and Machine-Learning Platforms market. It provides a holistic view of the industry, as well as detailed insights into individual components and stakeholders. The report analysis market dynamics, trends, challenges, and opportunities within the Data Science and Machine-Learning Platforms industry.
The report involves analyzing the market at a macro level:
Market Sizing and Segmentation: Report collect data on the overall market size, including the revenue generated, and market share of different by Type (e.g., Open Source Data Integration Tools, Cloud-based Data Integration Tools).
Industry Analysis: Report analyse the broader industry trends, such as government policies and regulations, technological advancements, consumer preferences, and market dynamics. This analysis helps in understanding the key drivers and challenges influencing the Data Science and Machine-Learning Platforms market.
Regional Analysis: The report involves examining the Data Science and Machine-Learning Platforms market at a regional or national level. Report analyses regional factors such as government incentives, infrastructure development, economic conditions, and consumer behaviour to identify variations and opportunities within different markets.
Market Projections: Report covers the gathered data and analysis to make future projections and forecasts for the Data Science and Machine-Learning Platforms market. This may include estimating market growth rates, predicting market demand, and identifying emerging trends.
The report also involves a more granular approach to Data Science and Machine-Learning Platforms:
Company Analysis: Report covers individual Data Science and Machine-Learning Platforms players, suppliers, and other relevant industry players. This analysis includes studying their financial performance, market positioning, product portfolios, partnerships, and strategies.
Consumer Analysis: Report covers data on consumer behaviour, preferences, and attitudes towards Data Science and Machine-Learning Platforms This may involve surveys, interviews, and analysis of consumer reviews and feedback from different by Application (Small-Sized Enterprises, Medium-Sized Enterprise).
Technology Analysis: Report covers specific technologies relevant to Data Science and Machine-Learning Platforms. It assesses the current state, advancements, and potential future developments in Data Science and Machine-Learning Platforms areas.
Competitive Landscape: By analyzing individual companies, suppliers, and consumers, the report present insights into the competitive landscape of the Data Science and Machine-Learning Platforms market. This analysis helps understand market share, competitive advantages, and potential areas for differentiation among industry players.
Market Validation: The report involves validating findings and projections through primary research, such as surveys, interviews, and focus groups.
Market Segmentation
Data Science and Machine-Learning Platforms market is split by Type and by Application. For the period 2019-2030, the growth among segments provides accurate calculations and forecasts for consumption value by Type, and by Application in terms of value.
Market segment by Type
Open Source Data Integration Tools
Cloud-based Data Integration Tools
Market segment by Application
Small-Sized Enterprises
Medium-Sized Enterprise
Large Enterprises
Market segment by players, this report covers
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 regions, regional analysis covers
North America (United States, Canada, and Mexico)
Europe (Germany, France, UK, Russia, Italy, and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia and Rest of Asia-Pacific)
South America (Brazil, Argentina and Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
The content of the study subjects, includes a total of 13 chapters:
Chapter 1, to describe Data Science and Machine-Learning Platforms product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top players of Data Science and Machine-Learning Platforms, with revenue, gross margin and global market share of Data Science and Machine-Learning Platforms from 2019 to 2024.
Chapter 3, the Data Science and Machine-Learning Platforms competitive situation, revenue and global market share of top players are analyzed emphatically by landscape contrast.
Chapter 4 and 5, to segment the market size by Type and application, with consumption value and growth rate by Type, application, from 2019 to 2030.
Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2019 to 2024.and Data Science and Machine-Learning Platforms market forecast, by regions, type and application, with consumption value, from 2025 to 2030.
Chapter 11, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
Chapter 12, the key raw materials and key suppliers, and industry chain of Data Science and Machine-Learning Platforms.
Chapter 13, to describe Data Science and Machine-Learning Platforms research findings and conclusion.
1 Market Overview
- 1.1 Product Overview and Scope of Data Science and Machine-Learning Platforms
- 1.2 Market Estimation Caveats and Base Year
- 1.3 Classification of Data Science and Machine-Learning Platforms by Type
- 1.3.1 Overview: Global Data Science and Machine-Learning Platforms Market Size by Type: 2019 Versus 2023 Versus 2030
- 1.3.2 Global Data Science and Machine-Learning Platforms Consumption Value Market Share by Type in 2023
- 1.3.3 Open Source Data Integration Tools
- 1.3.4 Cloud-based Data Integration Tools
- 1.4 Global Data Science and Machine-Learning Platforms Market by Application
- 1.4.1 Overview: Global Data Science and Machine-Learning Platforms Market Size by Application: 2019 Versus 2023 Versus 2030
- 1.4.2 Small-Sized Enterprises
- 1.4.3 Medium-Sized Enterprise
- 1.4.4 Large Enterprises
- 1.5 Global Data Science and Machine-Learning Platforms Market Size & Forecast
- 1.6 Global Data Science and Machine-Learning Platforms Market Size and Forecast by Region
- 1.6.1 Global Data Science and Machine-Learning Platforms Market Size by Region: 2019 VS 2023 VS 2030
- 1.6.2 Global Data Science and Machine-Learning Platforms Market Size by Region, (2019-2030)
- 1.6.3 North America Data Science and Machine-Learning Platforms Market Size and Prospect (2019-2030)
- 1.6.4 Europe Data Science and Machine-Learning Platforms Market Size and Prospect (2019-2030)
- 1.6.5 Asia-Pacific Data Science and Machine-Learning Platforms Market Size and Prospect (2019-2030)
- 1.6.6 South America Data Science and Machine-Learning Platforms Market Size and Prospect (2019-2030)
- 1.6.7 Middle East and Africa Data Science and Machine-Learning Platforms Market Size and Prospect (2019-2030)
2 Company Profiles
- 2.1 SAS
- 2.1.1 SAS Details
- 2.1.2 SAS Major Business
- 2.1.3 SAS Data Science and Machine-Learning Platforms Product and Solutions
- 2.1.4 SAS Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.1.5 SAS Recent Developments and Future Plans
- 2.2 Alteryx
- 2.2.1 Alteryx Details
- 2.2.2 Alteryx Major Business
- 2.2.3 Alteryx Data Science and Machine-Learning Platforms Product and Solutions
- 2.2.4 Alteryx Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.2.5 Alteryx Recent Developments and Future Plans
- 2.3 IBM
- 2.3.1 IBM Details
- 2.3.2 IBM Major Business
- 2.3.3 IBM Data Science and Machine-Learning Platforms Product and Solutions
- 2.3.4 IBM Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.3.5 IBM Recent Developments and Future Plans
- 2.4 RapidMiner
- 2.4.1 RapidMiner Details
- 2.4.2 RapidMiner Major Business
- 2.4.3 RapidMiner Data Science and Machine-Learning Platforms Product and Solutions
- 2.4.4 RapidMiner Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.4.5 RapidMiner Recent Developments and Future Plans
- 2.5 KNIME
- 2.5.1 KNIME Details
- 2.5.2 KNIME Major Business
- 2.5.3 KNIME Data Science and Machine-Learning Platforms Product and Solutions
- 2.5.4 KNIME Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.5.5 KNIME Recent Developments and Future Plans
- 2.6 Microsoft
- 2.6.1 Microsoft Details
- 2.6.2 Microsoft Major Business
- 2.6.3 Microsoft Data Science and Machine-Learning Platforms Product and Solutions
- 2.6.4 Microsoft Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.6.5 Microsoft Recent Developments and Future Plans
- 2.7 Dataiku
- 2.7.1 Dataiku Details
- 2.7.2 Dataiku Major Business
- 2.7.3 Dataiku Data Science and Machine-Learning Platforms Product and Solutions
- 2.7.4 Dataiku Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.7.5 Dataiku Recent Developments and Future Plans
- 2.8 Databricks
- 2.8.1 Databricks Details
- 2.8.2 Databricks Major Business
- 2.8.3 Databricks Data Science and Machine-Learning Platforms Product and Solutions
- 2.8.4 Databricks Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.8.5 Databricks Recent Developments and Future Plans
- 2.9 TIBCO Software
- 2.9.1 TIBCO Software Details
- 2.9.2 TIBCO Software Major Business
- 2.9.3 TIBCO Software Data Science and Machine-Learning Platforms Product and Solutions
- 2.9.4 TIBCO Software Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.9.5 TIBCO Software Recent Developments and Future Plans
- 2.10 MathWorks
- 2.10.1 MathWorks Details
- 2.10.2 MathWorks Major Business
- 2.10.3 MathWorks Data Science and Machine-Learning Platforms Product and Solutions
- 2.10.4 MathWorks Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.10.5 MathWorks Recent Developments and Future Plans
- 2.11 H20.ai
- 2.11.1 H20.ai Details
- 2.11.2 H20.ai Major Business
- 2.11.3 H20.ai Data Science and Machine-Learning Platforms Product and Solutions
- 2.11.4 H20.ai Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.11.5 H20.ai Recent Developments and Future Plans
- 2.12 Anaconda
- 2.12.1 Anaconda Details
- 2.12.2 Anaconda Major Business
- 2.12.3 Anaconda Data Science and Machine-Learning Platforms Product and Solutions
- 2.12.4 Anaconda Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.12.5 Anaconda Recent Developments and Future Plans
- 2.13 SAP
- 2.13.1 SAP Details
- 2.13.2 SAP Major Business
- 2.13.3 SAP Data Science and Machine-Learning Platforms Product and Solutions
- 2.13.4 SAP Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.13.5 SAP Recent Developments and Future Plans
- 2.14 Google
- 2.14.1 Google Details
- 2.14.2 Google Major Business
- 2.14.3 Google Data Science and Machine-Learning Platforms Product and Solutions
- 2.14.4 Google Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.14.5 Google Recent Developments and Future Plans
- 2.15 Domino Data Lab
- 2.15.1 Domino Data Lab Details
- 2.15.2 Domino Data Lab Major Business
- 2.15.3 Domino Data Lab Data Science and Machine-Learning Platforms Product and Solutions
- 2.15.4 Domino Data Lab Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.15.5 Domino Data Lab Recent Developments and Future Plans
- 2.16 Angoss
- 2.16.1 Angoss Details
- 2.16.2 Angoss Major Business
- 2.16.3 Angoss Data Science and Machine-Learning Platforms Product and Solutions
- 2.16.4 Angoss Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.16.5 Angoss Recent Developments and Future Plans
- 2.17 Lexalytics
- 2.17.1 Lexalytics Details
- 2.17.2 Lexalytics Major Business
- 2.17.3 Lexalytics Data Science and Machine-Learning Platforms Product and Solutions
- 2.17.4 Lexalytics Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.17.5 Lexalytics Recent Developments and Future Plans
- 2.18 Rapid Insight
- 2.18.1 Rapid Insight Details
- 2.18.2 Rapid Insight Major Business
- 2.18.3 Rapid Insight Data Science and Machine-Learning Platforms Product and Solutions
- 2.18.4 Rapid Insight Data Science and Machine-Learning Platforms Revenue, Gross Margin and Market Share (2019-2024)
- 2.18.5 Rapid Insight Recent Developments and Future Plans
3 Market Competition, by Players
- 3.1 Global Data Science and Machine-Learning Platforms Revenue and Share by Players (2019-2024)
- 3.2 Market Share Analysis (2023)
- 3.2.1 Market Share of Data Science and Machine-Learning Platforms by Company Revenue
- 3.2.2 Top 3 Data Science and Machine-Learning Platforms Players Market Share in 2023
- 3.2.3 Top 6 Data Science and Machine-Learning Platforms Players Market Share in 2023
- 3.3 Data Science and Machine-Learning Platforms Market: Overall Company Footprint Analysis
- 3.3.1 Data Science and Machine-Learning Platforms Market: Region Footprint
- 3.3.2 Data Science and Machine-Learning Platforms Market: Company Product Type Footprint
- 3.3.3 Data Science and Machine-Learning Platforms Market: Company Product Application Footprint
- 3.4 New Market Entrants and Barriers to Market Entry
- 3.5 Mergers, Acquisition, Agreements, and Collaborations
4 Market Size Segment by Type
- 4.1 Global Data Science and Machine-Learning Platforms Consumption Value and Market Share by Type (2019-2024)
- 4.2 Global Data Science and Machine-Learning Platforms Market Forecast by Type (2025-2030)
5 Market Size Segment by Application
- 5.1 Global Data Science and Machine-Learning Platforms Consumption Value Market Share by Application (2019-2024)
- 5.2 Global Data Science and Machine-Learning Platforms Market Forecast by Application (2025-2030)
6 North America
- 6.1 North America Data Science and Machine-Learning Platforms Consumption Value by Type (2019-2030)
- 6.2 North America Data Science and Machine-Learning Platforms Consumption Value by Application (2019-2030)
- 6.3 North America Data Science and Machine-Learning Platforms Market Size by Country
- 6.3.1 North America Data Science and Machine-Learning Platforms Consumption Value by Country (2019-2030)
- 6.3.2 United States Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 6.3.3 Canada Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 6.3.4 Mexico Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
7 Europe
- 7.1 Europe Data Science and Machine-Learning Platforms Consumption Value by Type (2019-2030)
- 7.2 Europe Data Science and Machine-Learning Platforms Consumption Value by Application (2019-2030)
- 7.3 Europe Data Science and Machine-Learning Platforms Market Size by Country
- 7.3.1 Europe Data Science and Machine-Learning Platforms Consumption Value by Country (2019-2030)
- 7.3.2 Germany Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 7.3.3 France Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 7.3.4 United Kingdom Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 7.3.5 Russia Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 7.3.6 Italy Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
8 Asia-Pacific
- 8.1 Asia-Pacific Data Science and Machine-Learning Platforms Consumption Value by Type (2019-2030)
- 8.2 Asia-Pacific Data Science and Machine-Learning Platforms Consumption Value by Application (2019-2030)
- 8.3 Asia-Pacific Data Science and Machine-Learning Platforms Market Size by Region
- 8.3.1 Asia-Pacific Data Science and Machine-Learning Platforms Consumption Value by Region (2019-2030)
- 8.3.2 China Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 8.3.3 Japan Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 8.3.4 South Korea Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 8.3.5 India Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 8.3.6 Southeast Asia Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 8.3.7 Australia Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
9 South America
- 9.1 South America Data Science and Machine-Learning Platforms Consumption Value by Type (2019-2030)
- 9.2 South America Data Science and Machine-Learning Platforms Consumption Value by Application (2019-2030)
- 9.3 South America Data Science and Machine-Learning Platforms Market Size by Country
- 9.3.1 South America Data Science and Machine-Learning Platforms Consumption Value by Country (2019-2030)
- 9.3.2 Brazil Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 9.3.3 Argentina Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
10 Middle East & Africa
- 10.1 Middle East & Africa Data Science and Machine-Learning Platforms Consumption Value by Type (2019-2030)
- 10.2 Middle East & Africa Data Science and Machine-Learning Platforms Consumption Value by Application (2019-2030)
- 10.3 Middle East & Africa Data Science and Machine-Learning Platforms Market Size by Country
- 10.3.1 Middle East & Africa Data Science and Machine-Learning Platforms Consumption Value by Country (2019-2030)
- 10.3.2 Turkey Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 10.3.3 Saudi Arabia Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
- 10.3.4 UAE Data Science and Machine-Learning Platforms Market Size and Forecast (2019-2030)
11 Market Dynamics
- 11.1 Data Science and Machine-Learning Platforms Market Drivers
- 11.2 Data Science and Machine-Learning Platforms Market Restraints
- 11.3 Data Science and Machine-Learning Platforms Trends Analysis
- 11.4 Porters Five Forces Analysis
- 11.4.1 Threat of New Entrants
- 11.4.2 Bargaining Power of Suppliers
- 11.4.3 Bargaining Power of Buyers
- 11.4.4 Threat of Substitutes
- 11.4.5 Competitive Rivalry
12 Industry Chain Analysis
- 12.1 Data Science and Machine-Learning Platforms Industry Chain
- 12.2 Data Science and Machine-Learning Platforms Upstream Analysis
- 12.3 Data Science and Machine-Learning Platforms Midstream Analysis
- 12.4 Data Science and Machine-Learning Platforms Downstream Analysis
13 Research Findings and Conclusion
14 Appendix
- 14.1 Methodology
- 14.2 Research Process and Data Source
Summary:
Get latest Market Research Reports on Data Science and Machine-Learning Platforms. Industry analysis & Market Report on Data Science and Machine-Learning Platforms is a syndicated market report, published as Global Data Science and Machine-Learning Platforms Market 2024 by Company, Regions, Type and Application, Forecast to 2030. It is complete Research Study and Industry Analysis of Data Science and Machine-Learning Platforms market, to understand, Market Demand, Growth, trends analysis and Factor Influencing market.
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