Data Science Platform Market Size to Worth Around US$ 378.7 Billion by 2030
[150+ Pages Report] As per the latest Research and survey report issued by Precedence Research, the global data science platform market was valued at around USD 96.3 billion in 2021 and is expected to register revenues worth USD 378.7 billion by the end of 2030, growing at an exceptional CAGR of approximately 16.43% between 2022 and 2030.
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Data Science Platform Market Report Scope
A recent study by Precedence Research on the data science platform market offers a forecast for 2022 and 2030. The study analyzes crucial trends that are currently determining the growth of the data science platform market. This report explicates on vital dynamics such as the drivers, restraints, and opportunities for key market players, along with key stakeholders as well as emerging players associated with the manufacturing of data science platform. The study also provides the dynamics that are responsible for influencing the future status of the data science platform market over the forecast period.
A detailed assessment of the data science platform market value chain analysis, business execution, and supply chain analysis across regional markets has been covered in the report. A list of prominent companies operating in the data science platform market along with their product portfolio enhances the reliability of this comprehensive research study.
Competition Landscape
The report has engulfed a chapter on the global data science platform market’s competitive landscape, which provides detailed analysis and insights on companies offering data science platform. Profiles of key companies, along with a strategic overview of their M&A and expansion plans across geographies, have been delivered in this chapter. This chapter is priceless for report readers, as its enables them in gauging their growth potential in the market and implement key strategies for extending their market reach.
This chapter offers key recommendations for both new and existing market participants, enabling them to emerge sustainably and profitably. Intelligence on the market players has been delivered on the basis of their product overview, SWOT analysis, key developments, key financials and company overview. Occupancy of these market participants has been tracked by the report and portrayed via an intensity map.
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Some of the Prominent Players in the Data Science Platform Market Include:
- ALTERYX INC.
- CLOUDERA INC.
- DATAROBOT INC.
- DOMINO DATA LAB INC.
- Databricks
- IBM CORPORATION
- Rexer Analytics
- RAPIDMINER INC.
- RAPID INSIGHT
- OLFRAM
Data Science Platform Market Segmentation
By Component
- Platform
- Services
By Application
- Marketing & Sales
- Logistics
- Finance and Accounting
- Customer Support
- Others
By Industry Vertical
- BFSI
- Retail and E-Commerce
- IT and Telecom
- Transportation
- Healthcare
- Manufacturing
- Others
By Organization Size
- Small and Medium-Sized Enterprises
- Large Enterprises
By Deployment Mode
- Cloud
- On-premises
Regional Segmentation
- Asia-Pacific [China, Southeast Asia, India, Japan, Korea, Western Asia]
- Europe [Germany, UK, France, Italy, Russia, Spain, Netherlands, Turkey, Switzerland]
- North America [United States, Canada, Mexico]
- South America [Brazil, Argentina, Columbia, Chile, Peru]
- Middle East & Africa [GCC, North Africa, South Africa]
Regional Analysis
The research report includes a detailed study of regions of North America, Europe, China, Japan and Rest of the World. The report has been curated after observing and studying various factors that determine regional growth such as economic, environmental, social, technological, and political status of the particular region. Analysts have studied the data of revenue and manufacturers of each region. This section analyses region-wise revenue and volume for the forecast period of 2022 to 2030. These analyses will help the reader to understand the potential worth of investment in a particular region.
The report provides in-depth segment analysis of the global data science platform market, thereby providing valuable insights at macro as well as micro levels. Analysis of major countries, which hold growth opportunities or account for significant share has also been included as part of geographic analysis of the data science platform market.
The report includes country-wise and region-wise market size for the period 2022-2030. It also includes market size and forecast by segments in terms of production capacity, price and revenue for the period 2022-2030.
Why should you invest in this report?
If you are aiming to enter the global data science platform market, this report is a comprehensive guide that provides crystal clear insights into this niche market. All the major application areas for data science platform are covered in this report and information is given on the important regions of the world where this market is likely to boom during the forecast period of 2022-2030 so that you can plan your strategies to enter this market accordingly.
Besides, through this report, you can have a complete grasp of the level of competition you will be facing in this hugely competitive market and if you are an established player in this market already, this report will help you gauge the strategies that your competitors have adopted to stay as market leaders in this market. For new entrants to this market, the voluminous data provided in this report is invaluable.
Table of Contents
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Data Science Platform Market
5.1. COVID-19 Landscape: Data Science Platform Industry Impact
5.2. COVID 19 – Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Data Science Platform Market, By Component
8.1. Data Science Platform Market, by Component, 2022-2030
8.1.1. Platform
8.1.1.1. Market Revenue and Forecast (2017-2030)
8.1.2. Services
8.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 9. Global Data Science Platform Market, By Application
9.1. Data Science Platform Market, by Application, 2022-2030
9.1.1. Marketing & Sales
9.1.1.1. Market Revenue and Forecast (2017-2030)
9.1.2. Logistics
9.1.2.1. Market Revenue and Forecast (2017-2030)
9.1.3. Finance and Accounting
9.1.3.1. Market Revenue and Forecast (2017-2030)
9.1.4. Customer Support
9.1.4.1. Market Revenue and Forecast (2017-2030)
9.1.5. Others
9.1.5.1. Market Revenue and Forecast (2017-2030)
Chapter 10. Global Data Science Platform Market, By Industry Vertical
10.1. Data Science Platform Market, by Industry Vertical, 2022-2030
10.1.1. BFSI
10.1.1.1. Market Revenue and Forecast (2017-2030)
10.1.2. Retail and E-Commerce
10.1.2.1. Market Revenue and Forecast (2017-2030)
10.1.3. IT and Telecom
10.1.3.1. Market Revenue and Forecast (2017-2030)
10.1.4. Transportation
10.1.4.1. Market Revenue and Forecast (2017-2030)
10.1.5. Healthcare
10.1.5.1. Market Revenue and Forecast (2017-2030)
10.1.6. Manufacturing
10.1.6.1. Market Revenue and Forecast (2017-2030)
10.1.7. Others
10.1.7.1. Market Revenue and Forecast (2017-2030)
Chapter 11. Global Data Science Platform Market, By Organization Size
11.1. Data Science Platform Market, by Organization Size, 2022-2030
11.1.1. Small and Medium-Sized Enterprises
11.1.1.1. Market Revenue and Forecast (2017-2030)
11.1.2. Large Enterprises
11.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 12. Global Data Science Platform Market, By Deployment Mode
12.1. Data Science Platform Market, by Deployment Mode, 2022-2030
12.1.1. Cloud
12.1.1.1. Market Revenue and Forecast (2017-2030)
12.1.2. On-premises
12.1.2.1. Market Revenue and Forecast (2017-2030)
Chapter 13. Global Data Science Platform Market, Regional Estimates and Trend Forecast
13.1. North America
13.1.1. Market Revenue and Forecast, by Component (2017-2030)
13.1.2. Market Revenue and Forecast, by Application (2017-2030)
13.1.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.1.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.1.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.1.6. U.S.
13.1.6.1. Market Revenue and Forecast, by Component (2017-2030)
13.1.6.2. Market Revenue and Forecast, by Application (2017-2030)
13.1.6.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.1.6.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.1.6.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.1.7. Rest of North America
13.1.7.1. Market Revenue and Forecast, by Component (2017-2030)
13.1.7.2. Market Revenue and Forecast, by Application (2017-2030)
13.1.7.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.1.7.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.1.7.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.2. Europe
13.2.1. Market Revenue and Forecast, by Component (2017-2030)
13.2.2. Market Revenue and Forecast, by Application (2017-2030)
13.2.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.2.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.2.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.2.6. UK
13.2.6.1. Market Revenue and Forecast, by Component (2017-2030)
13.2.6.2. Market Revenue and Forecast, by Application (2017-2030)
13.2.6.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.2.6.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.2.6.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.2.7. Germany
13.2.7.1. Market Revenue and Forecast, by Component (2017-2030)
13.2.7.2. Market Revenue and Forecast, by Application (2017-2030)
13.2.7.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.2.7.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.2.7.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.2.8. France
13.2.8.1. Market Revenue and Forecast, by Component (2017-2030)
13.2.8.2. Market Revenue and Forecast, by Application (2017-2030)
13.2.8.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.2.8.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.2.8.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.2.9. Rest of Europe
13.2.9.1. Market Revenue and Forecast, by Component (2017-2030)
13.2.9.2. Market Revenue and Forecast, by Application (2017-2030)
13.2.9.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.2.9.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.2.9.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.3. APAC
13.3.1. Market Revenue and Forecast, by Component (2017-2030)
13.3.2. Market Revenue and Forecast, by Application (2017-2030)
13.3.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.3.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.3.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.3.6. India
13.3.6.1. Market Revenue and Forecast, by Component (2017-2030)
13.3.6.2. Market Revenue and Forecast, by Application (2017-2030)
13.3.6.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.3.6.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.3.6.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.3.7. China
13.3.7.1. Market Revenue and Forecast, by Component (2017-2030)
13.3.7.2. Market Revenue and Forecast, by Application (2017-2030)
13.3.7.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.3.7.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.3.7.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.3.8. Japan
13.3.8.1. Market Revenue and Forecast, by Component (2017-2030)
13.3.8.2. Market Revenue and Forecast, by Application (2017-2030)
13.3.8.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.3.8.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.3.8.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.3.9. Rest of APAC
13.3.9.1. Market Revenue and Forecast, by Component (2017-2030)
13.3.9.2. Market Revenue and Forecast, by Application (2017-2030)
13.3.9.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.3.9.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.3.9.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.4. MEA
13.4.1. Market Revenue and Forecast, by Component (2017-2030)
13.4.2. Market Revenue and Forecast, by Application (2017-2030)
13.4.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.4.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.4.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.4.6. GCC
13.4.6.1. Market Revenue and Forecast, by Component (2017-2030)
13.4.6.2. Market Revenue and Forecast, by Application (2017-2030)
13.4.6.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.4.6.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.4.6.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.4.7. North Africa
13.4.7.1. Market Revenue and Forecast, by Component (2017-2030)
13.4.7.2. Market Revenue and Forecast, by Application (2017-2030)
13.4.7.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.4.7.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.4.7.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.4.8. South Africa
13.4.8.1. Market Revenue and Forecast, by Component (2017-2030)
13.4.8.2. Market Revenue and Forecast, by Application (2017-2030)
13.4.8.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.4.8.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.4.8.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.4.9. Rest of MEA
13.4.9.1. Market Revenue and Forecast, by Component (2017-2030)
13.4.9.2. Market Revenue and Forecast, by Application (2017-2030)
13.4.9.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.4.9.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.4.9.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.5. Latin America
13.5.1. Market Revenue and Forecast, by Component (2017-2030)
13.5.2. Market Revenue and Forecast, by Application (2017-2030)
13.5.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.5.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.5.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.5.6. Brazil
13.5.6.1. Market Revenue and Forecast, by Component (2017-2030)
13.5.6.2. Market Revenue and Forecast, by Application (2017-2030)
13.5.6.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.5.6.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.5.6.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
13.5.7. Rest of LATAM
13.5.7.1. Market Revenue and Forecast, by Component (2017-2030)
13.5.7.2. Market Revenue and Forecast, by Application (2017-2030)
13.5.7.3. Market Revenue and Forecast, by Industry Vertical (2017-2030)
13.5.7.4. Market Revenue and Forecast, by Organization Size (2017-2030)
13.5.7.5. Market Revenue and Forecast, by Deployment Mode (2017-2030)
Chapter 14. Company Profiles
14.1. ALTERYX INC.
14.1.1. Company Overview
14.1.2. Product Offerings
14.1.3. Financial Performance
14.1.4. Recent Initiatives
14.2. CLOUDERA INC.
14.2.1. Company Overview
14.2.2. Product Offerings
14.2.3. Financial Performance
14.2.4. Recent Initiatives
14.3. DATAROBOT INC.
14.3.1. Company Overview
14.3.2. Product Offerings
14.3.3. Financial Performance
14.3.4. Recent Initiatives
14.4. DOMINO DATA LAB INC.
14.4.1. Company Overview
14.4.2. Product Offerings
14.4.3. Financial Performance
14.4.4. Recent Initiatives
14.5. Databricks
14.5.1. Company Overview
14.5.2. Product Offerings
14.5.3. Financial Performance
14.5.4. Recent Initiatives
14.6. IBM CORPORATION
14.6.1. Company Overview
14.6.2. Product Offerings
14.6.3. Financial Performance
14.6.4. Recent Initiatives
14.7. Rexer Analytics
14.7.1. Company Overview
14.7.2. Product Offerings
14.7.3. Financial Performance
14.7.4. Recent Initiatives
14.8. RAPIDMINER INC.
14.8.1. Company Overview
14.8.2. Product Offerings
14.8.3. Financial Performance
14.8.4. Recent Initiatives
14.9. RAPID INSIGHT
14.9.1. Company Overview
14.9.2. Product Offerings
14.9.3. Financial Performance
14.9.4. Recent Initiatives
14.10. OLFRAM
14.10.1. Company Overview
14.10.2. Product Offerings
14.10.3. Financial Performance
14.10.4. Recent Initiatives
Chapter 15. Research Methodology
15.1. Primary Research
15.2. Secondary Research
15.3. Assumptions
Chapter 16. Appendix
16.1. About Us
16.2. Glossary of Terms
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