by Precedence Research a new report on data science platform market size, share, growth, industry trends, and forecast 2030, covering various industry elements and growth trends helpful for predicting the market’s future. The global data science platform market size was valued at US$ 96.3 billion in 2021. The global data science platform market is projected to reach US$ 378.7 billion by 2030, registering a compound annual growth rate (CAGR) of 16.43% during the forecast period from 2022 to 2030.
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The global data science platform market report offers various segments analysis by size, trends, growth factors, opportunities and key country outlook to 2030. The report offers a detailed analysis and information as per data science platform, market segments helping our readers to get a comprehensive overview of the global market. Several players are planning to focus on developing cost-effective products or services, aiming to maintain a strong foothold in the market.
Data Science Platform Market Report Scope
| Report Coverage | Details |
| Market Size in 2022 | USD 112.12 Billion |
| Market Size by 2030 | USD 378.7 Billion |
| Growth Rate from 2022 to 2030 | CAGR of 16.43% |
| Base Year | 2021 |
| Forecast Period | 2022 to 2030 |
| Segments Covered | Component, Application, Industry Vertical, Organization Size, Deployment Mode, Geography |
The company profiling of leading market players is included this report with Porter’s five forces analysis and Value Chain analysis. Further, the strategies exercised by the companies for expansion of business through mergers, acquisitions, and other business development measures are discussed in the report. The financial parameters which are assessed include the sales, profits and the overall revenue generated by the key players of Market.
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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]
Key Questions are
- What are the key factors influencing the data science platform market in each region?
- How much value will the global market generate by the end of the forecast period?
- What will be the CAGR of the global market between 2022 and 2030?
- What would be the Y-o-Y growth trend of the global market between 2022 and 2030?
- What is the future scope and current trends in technologies of the global market?
- What is the revenue of the global market based on segments?
- Which key strategies are used by top players of the global market?
- Which are the leading companies in the global market?
- What are the essential strategies by key stakeholders in the market to expand their geographic presence?
- What are the major advancements witnessed in the global market?
Research Objectives and Research Approach
The comprehensive report on the global data science platform market begins with an overview, followed by the scope and objectives of the study. The report provides detailed explanation of the objectives behind this study and key vendors and distributors operating in the market and regulatory scenario for approval of products. Following this, the report provides detailed explanation of objectives of this study and laid down by accredited agencies in the purview of research in the global data science platform market.
It is followed by market introduction, market dynamics, and an overview of the global market, which includes analysis of market drivers, restraints, and trends pertaining to the global market. Furthermore, Y-o-Y growth analysis with elaborated insights has been provided in order to understand the Y-o-Y growth trend of the global market.
For reading comprehensibility, the report has been compiled in a chapter-wise layout, with each section divided into smaller sections. The report comprises an exhaustive collection of graphs and tables that are appropriately interspersed. Pictorial representation of actual and projected values of key segments is visually appealing to readers. This also allows comparison of the market shares of key segments in the past and at the end of the forecast period.
The report analyzes the global data science platform market in terms of type, application, region and others. Key segments under each criteria are studied at length, and the market share for each of these at the end of 2030 has also been provided. Such valuable insights enable market stakeholders in making informed business decisions for investment in the global market.
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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