The global data science platform market size was US$ 69.07 billion in 2021. The global data science platform market size is forecast to reach US$ 1028.7 billion by 2030, growing at a compound annual growth rate (CAGR) of 35% during the forecast period from 2022 to 2030.

A data science platform is a software hub where all the analytical work and data science work takes place. This data science platform includes all the resources required for the entire life cycle of a data science project, including ideation, model development, installation, discovery, and implementation. A data science application combines data collection, analysis, and the method that helps interpret the results. The data science platform allows data scientists to run, track, replicate, analyze, and share their work more quickly.

Factors Influencing Market Growth

• Among the key growth drivers for the market are the focus of enterprises on ease of use methods to drive business and the need to gain deeper insights from large amounts of data.
• Increasing enterprise interest in data-intensive business strategies and the rising adoption of advanced technologies present a number of opportunities for data science platform makers.
• Its version control feature allows data science teams to team up on projects without losing work they have already completed. It is a major driver of market growth.
• Data protection concerns and a lack of domain expertise may slow down the growth of the Data Science Platform market.

Impact of COVID-19

During COVID-19, cloud computing emerged as an effective model in helping businesses facilitate some of their most significant transformations. Despite the COVID-19 outbreak, many organizations (both SMBs and enterprises) plan to use the cloud more heavily in the future. Many countries were much more encouraging, with key sectors such as education, healthcare, entertainment, and gaming moving to the cloud consistently to ensure business continuity and resilience. There was significant demand for data science platforms. Thus, these factors have positively affected the global data science platform market growth.

Regional Insights

During the forecast period, Asia Pacific is forecast to hold the highest CAGR in the data science platform industry. Cloud, Internet of Things, and edge solutions are generating enormous amounts of data, increasing the demand for advanced data processing technologies. Data processing is driving the demand for a data science platform in the APAC region. Additionally, investment from major tech companies is also likely to drive regional market growth.

Leading Competitors

The leading prominent companies profiled in the global data science platform market are: 

• IBM Corporation
• Microsoft Corporation
• Alphabet Incorporated (Google)
• Altair Engineering, Incorporated
• Alteryx, Incorporated
• MathWorks
• SAS Institute Incorporated
• RapidMiner, Incorporated
• Cloudera, Incorporated
• Anaconda, Incorporated
• Wolfram
• Dataiku
• Civis Analytics
• H2O.ai.
• Domino Data Lab, Incorporated
• RStudio, Incorporated
• Rapid Insight
• DataRobot, Incorporated
• Rexer Analytics
• Other Prominent Players

Scope of the Report

The global data science platform market segmentation focuses on Components, Industry Verticals, Deployment Modes, Business Functions, Organization Size, and Region.

Segmentation based on Components

• Platform
• Services
  • Managed Services
  • Professional Services
• Training and Consulting
• Integration and Deployment
• Support and Maintenance

Segmentation based on Industry Verticals

• Banking, Financial Services, and Insurance (BFSI)
• Telecom and IT
• Retail and eCommerce
• Healthcare and Life sciences
• Manufacturing
• Energy and Utilities
• Media and Entertainment
• Transportation and Logistics
• Government
• Others (travel and hospitality, education, and research)

Segmentation based on Deployment Modes

• Cloud
• On-premises

Segmentation based on Business Functions

• Marketing
• Sales
• Logistics
• Finance and Accounting
• Customer Support
• Others (operation and HR)

Segmentation based on Organization Size

• Small and Medium-sized Enterprises (SMEs)
• Large Enterprises

Segmentation based on Region

• North America
  • The U.S.
  • Canada
  • Mexico
• Europe
  • Western Europe
    • The UK
    • Germany
    • France
    • Italy
    • Spain
    • Rest of Western Europe
  • Eastern Europe
    • Poland
    • Russia
    • Rest of Eastern Europe
• Asia Pacific
  • China
  • India
  • Japan
  • Australia & New Zealand
  • ASEAN
  • Rest of Asia Pacific
• Middle East & Africa (MEA)
  • UAE
  • Saudi Arabia
  • South Africa
  • Rest of MEA
• South America
  • Brazil
  • Argentina
  • Rest of South America

[Table of Content]

1 INTRODUCTION OF GLOBAL DATA SCIENCE PLATFORM MARKET
1.1 OVERVIEW OF THE MARKET
1.2 SCOPE OF REPORT
1.3 ASSUMPTIONS

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY
3.1 DATA MINING
3.2 VALIDATION
3.3 PRIMARY INTERVIEWS
3.4 LIST OF DATA SOURCES

4 GLOBAL DATA SCIENCE PLATFORM MARKET OUTLOOK
4.1 OVERVIEW
4.2 MARKET DYNAMICS
4.2.1 DRIVERS
4.2.2 RESTRAINTS
4.2.3 OPPORTUNITIES
4.3 PORTERS FIVE FORCE MODEL
4.4 VALUE CHAIN ANALYSIS

5 GLOBAL DATA SCIENCE PLATFORM MARKET, BY COMPONENTS
5.1 OVERVIEW
5.2 PLATFORM
5.3 SERVICES
5.3.1 MANAGED SERVICES
5.3.2 PROFESSIONAL SERVICES
5.4TRAINING AND CONSULTING
5.5INTEGRATION AND DEPLOYMENT
5.6 SUPPORT AND MAINTENANCE

6 GLOBAL DATA SCIENCE PLATFORM MARKET, BY DEPLOYMENT MODE
6.1 OVERVIEW
6.2 CLOUD
6.3 ON-PREMISES

7 GLOBAL DATA SCIENCE PLATFORM MARKET, BY INDUSTRY VERTICAL
7.1 OVERVIEW
7.2 BANKING, FINANCIAL SERVICES, AND INSURANCE (BFSI)
7.3 TELECOM AND IT
7.4 RETAIL AND ECOMMERCE
7.5 HEALTHCARE AND LIFE SCIENCES
7.6 MANUFACTURING
7.7 ENERGY AND UTILITIES
7.8 MEDIA AND ENTERTAINMENT
7.9 TRANSPORTATION AND LOGISTICS
7.10 GOVERNMENT
7.11 OTHERS (TRAVEL AND HOSPITALITY, EDUCATION, AND RESEARCH)

8 GLOBAL DATA SCIENCE PLATFORM MARKET, BY BUSINESS FUNCTIONS
8.1 OVERVIEW
8.2 MARKETING
8.3 SALES
8.4 LOGISTICS
8.5 FINANCE AND ACCOUNTING
8.6 CUSTOMER SUPPORT
8.7 OTHERS (OPERATION AND HR)

9 GLOBAL DATA SCIENCE PLATFORM MARKET, BY ORGANIZATION SIZE
9.1 OVERVIEW
9.2 SMALL AND MEDIUM-SIZED ENTERPRISES (SMES)
9.3 LARGE ENTERPRISES

10 MARKET, BY GEOGRAPHY
10.1 OVERVIEW

10.2 NORTH AMERICA

10.2.1 NORTH AMERICA MARKET SNAPSHOT
10.2.2 U.S.
10.2.3 CANADA
10.2.4 MEXICO

10.3 EUROPE

10.3.1 EUROPE MARKET SNAPSHOT
10.3.2 WESTERN EUROPE
10.3.2.1THE UK
10.3.2.2GERMANY
10.3.2.3FRANCE
10.3.2.4ITALY
10.3.2.5SPAIN
10.3.2.6REST OF WESTERN EUROPE
10.3.3EASTERN EUROPE
10.3.3.1POLAND
10.3.3.2RUSSIA
10.3.3.3REST OF EASTERN EUROPE

10.4 ASIA PACIFIC

10.4.1 ASIA PACIFIC MARKET SNAPSHOT
10.4.2 CHINA
10.4.3 JAPAN
10.4.4 INDIA
10.4.5 AUSTRALIA & NEW ZEALAND
10.4.6 ASEAN
10.4.7 REST OF ASIA PACIFIC

10.5 MIDDLE EAST & AFRICA

10.5.1 MIDDLE EAST & AFRICA MARKET SNAPSHOT
10.5.2 UAE
10.5.3 SAUDI ARABIA
10.5.4 SOUTH AFRICA
10.5.5 REST OF MEA

10.6 SOUTH AMERICA

10.6.1 SOUTH AMERICA MARKET SNAPSHOT
10.6.2 BRAZIL
10.6.3 ARGENTINA
10.6.4 REST OF SOUTH AMERICA

11 GLOBAL DATA SCIENCE PLATFORM MARKET COMPETITIVE LANDSCAPE
11.1 OVERVIEW
11.2 COMPANY MARKET RANKING
11.3 KEY DEVELOPMENT STRATEGIES

12 COMPANY PROFILES

12.1 IBM CORPORATION
12.1.1 OVERVIEW
12.1.2 FINANCIAL PERFORMANCE
12.1.3 PRODUCT OUTLOOK
12.1.4 KEY DEVELOPMENTS

12.2 MICROSOFT CORPORATION
12.2.1 OVERVIEW
12.2.2 FINANCIAL PERFORMANCE
12.2.3 PRODUCT OUTLOOK
12.2.4 KEY DEVELOPMENTS

12.3 ALPHABET INCORPORATED (GOOGLE)
12.3.1 OVERVIEW
12.3.2 FINANCIAL PERFORMANCE
12.3.3 PRODUCT OUTLOOK
12.3.4 KEY DEVELOPMENTS

12.4 ALTAIR ENGINEERING, INCORPORATED
12.4.1 OVERVIEW
12.4.2 FINANCIAL PERFORMANCE
12.4.3 PRODUCT OUTLOOK
12.4.4 KEY DEVELOPMENTS

12.5 ALTERYX, INCORPORATED
12.5.1 OVERVIEW
12.5.2 FINANCIAL PERFORMANCE
12.5.3 PRODUCT OUTLOOK
12.5.4 KEY DEVELOPMENTS

12.6 MATHWORKS
12.6.1 OVERVIEW
12.6.2 FINANCIAL PERFORMANCE
12.6.3 PRODUCT OUTLOOK
12.6.4 KEY DEVELOPMENTS

12.7 SAS INSTITUTE INCORPORATED
12.7.1 OVERVIEW
12.7.2 FINANCIAL PERFORMANCE
12.7.3 PRODUCT OUTLOOK
12.7.4 KEY DEVELOPMENTS

12.8 RAPIDMINER, INCORPORATED
12.8.1 OVERVIEW
12.8.2 FINANCIAL PERFORMANCE
12.8.3 PRODUCT OUTLOOK
12.8.4 KEY DEVELOPMENTS

12.9 CLOUDERA, INCORPORATED
12.9.1 OVERVIEW
12.9.2 FINANCIAL PERFORMANCE
12.9.3 PRODUCT OUTLOOK
12.9.4 KEY DEVELOPMENTS

12.10 ANACONDA, INCORPORATED
12.10.1 OVERVIEW
12.10.2 FINANCIAL PERFORMANCE
12.10.3 PRODUCT OUTLOOK
12.10.4 KEY DEVELOPMENTS

12.11 WOLFRAM
12.11.1 OVERVIEW
12.11.2 FINANCIAL PERFORMANCE
12.11.3 PRODUCT OUTLOOK
12.11.4 KEY DEVELOPMENTS

12.12 DATAIKU
12.12.1 OVERVIEW
12.12.2 FINANCIAL PERFORMANCE
12.12.3 PRODUCT OUTLOOK
12.12.4 KEY DEVELOPMENTS

12.13 CIVIS ANALYTICS
12.13.1 OVERVIEW
12.13.2 FINANCIAL PERFORMANCE
12.13.3 PRODUCT OUTLOOK
12.13.4 KEY DEVELOPMENTS

12.14 H2O.AI.
12.14.1 OVERVIEW
12.14.2 FINANCIAL PERFORMANCE
12.14.3 PRODUCT OUTLOOK
12.14.4 KEY DEVELOPMENTS

12.15 DOMINO DATA LAB, INCORPORATED
12.15.1 OVERVIEW
12.15.2 FINANCIAL PERFORMANCE
12.15.3 PRODUCT OUTLOOK
12.15.4 KEY DEVELOPMENTS

12.16 RSTUDIO, INCORPORATED
12.16.1 OVERVIEW
12.16.2 FINANCIAL PERFORMANCE
12.16.3 PRODUCT OUTLOOK
12.16.4 KEY DEVELOPMENTS

12.17 RAPID INSIGHT
12.17.1 OVERVIEW
12.17.2 FINANCIAL PERFORMANCE
12.17.3 PRODUCT OUTLOOK
12.17.4 KEY DEVELOPMENTS

12.18 DATAROBOT, INCORPORATED
12.18.1 OVERVIEW
12.18.2 FINANCIAL PERFORMANCE
12.18.3 PRODUCT OUTLOOK
12.18.4 KEY DEVELOPMENTS

12.19 REXER ANALYTICS
12.19.1 OVERVIEW
12.19.2 FINANCIAL PERFORMANCE
12.19.3 PRODUCT OUTLOOK
12.19.4 KEY DEVELOPMENTS