Data Science Platform Market Size & Share Analysis - Growth Trends & Forecasts (2025 - 2030)

The Report Covers Data Science Platform Market Companies & Industry Share and It is Segmented by Service (professional, Managed), Application (marketing, Sales, Logistics), Deployment (on-Premises, Cloud-Based), End-User Industry (IT & Telecommunication, Healthcare, BFSI, Manufacturing, Retail, Government and Defense, Energy, and Utilities), and Geography (North America, Europe, Asia-Pacific, Latin America, Middle East, and Africa). The Market Sizes and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

Data Science Platform Market Size & Share Analysis - Growth Trends & Forecasts (2025 - 2030)

Data Science Platform Market Size

Data Science Platform Market Summary
Study Period 2019 - 2030
Market Size (2025) USD 12.54 Billion
Market Size (2030) USD 36.01 Billion
CAGR (2025 - 2030) 23.50 %
Fastest Growing Market Asia Pacific
Largest Market North America
Market Concentration Low

Major Players

Data Science Platform Market Major Players

*Disclaimer: Major Players sorted in no particular order

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Data Science Platform Market Analysis

The Data Science Platform Market size is estimated at USD 12.54 billion in 2025, and is expected to reach USD 36.01 billion by 2030, at a CAGR of 23.5% during the forecast period (2025-2030).

Data Science is emerging to provide solutions to organizations to transform data sets into a valuable resource that helps get business value with actionable insights. As the number of business enterprises and organizations grows exponentially, data science is becoming essential in various aspects of business and plays a pivotal role in business models.

  • The data science platforms offer a suite of tools and services that allow organizations to manage, access, and analyze their data and enable organizations to streamline their data analysis processes and scale their data analysis capabilities. The adoption of data science platforms is growing due to benefits such as predictive analytics to automated machine learning processes, informed decisions, and better utilization of their data.
  • There is an increasing emphasis on businesses boosting their internal data science resources to build machine learning models and fill the hiring gap of in-demand professionals, resulting in increased adoption of data science as a service (DSaaS). For many businesses, it becomes essential as it helps them scale their analytics capabilities to meet critical needs and get the desired outcomes of business.
  • As technologies such as artificial intelligence (AI) and machine learning (ML) are advancing rapidly, businesses are receiving a significantly larger amount of data, including new data based on previously existing datasets and new forms of data altogether. Thus, to use these data, businesses are moving to adopt data science solutions that are compatible with their requirements.
  • One of the primary obstacles arising from the lack of a skilled workforce is the inability to derive meaningful insights from the vast volumes of data organizations generate. Data science platforms are designed to allow users to analyze and interpret complex datasets, but the shortage of skilled professionals capable of guiding these platforms diminishes their effectiveness. Organizations struggle to bridge the gap between the advanced functionalities of data science platforms and the expertise needed to leverage these functionalities optimally.
  • The COVID-19 pandemic accelerated the digitization of businesses and industries, leading to a surge in the need for data-driven insights. Organizations across sectors turned to data science to make informed decisions about resource and risk management and customer behavior. Further, the shift to remote work spurred the adoption of cloud-based data science platforms and tools, enabling data scientists to collaborate effectively from any location. This flexibility and accessibility further fueled the demand for data science expertise.

Data Science Platform Industry Overview

The Data Science Platform Market is semi-consolidated and is characterized by high product differentiation, growing levels of product penetration, and rapid advancements in technology, leading to difficulty in maintaining a competitive advantage, forcing them to continuously adopt and innovate solutions. Some of major players include Alteryx, IBM Corporation, Google LLC (Alphabet Inc.), SAS, Alteryx, Microsoft Corporation.

  • November 2023 - IBM collaborated with Amazon Web Services (AWS) on the general availability of Amazon Relational Database Service (Amazon RDS) for Db2, a fully managed cloud offering designed to make it easier for database customers to manage data for artificial intelligence (AI) workloads across hybrid cloud environments. It will allow the users to leverage an array of the company’s integrated data and AI capabilities on AWS to manage data and scale AI workloads. 
  • August 2023 - Google Cloud and NVIDIA announced a partnership expansion to advance AI computing, software, and services for customers to build and deploy massive models for generative AI and speed data science workloads. The partnership will bring end-to-end machine learning services to some of the largest AI customers in the world — including by making it easy to run AI supercomputers with Google Cloud offerings built on NVIDIA technologies. 

Data Science Platform Market Leaders

  1. IBM Corporation

  2. Google LLC (Alphabet Inc.)

  3. Microsoft Corporation

  4. SAS

  5. Alteryx

  6. *Disclaimer: Major Players sorted in no particular order
Data Science Platform Market Concentration
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Data Science Platform Market News

  • November 2023 - Stagwell announced a partnership with Google Cloud and SADA, a Google Cloud premier partner, to develop generative AI (gen AI) marketing solutions that support Stagwell agencies, client partners, and product development within the Stagwell Marketing Cloud (SMC). The partnership will help in harnessing data analytics and insights by developing and training a proprietary Stagwell large language model (LLM) purpose-built for Stagwell clients, productizing data assets via APIs to create new digital experiences for brands, and multiplying the value of their first-party data ecosystems to drive new revenue streams using Vertex AI and open source-based models.
  • May 2023 - IBM launched a new AI and data platform, watsonx, it is aimed at allowing businesses to accelerate advanced AI usage with trusted data, speed and governance. IBM also introduced GPU-as-a-service, which is designed to support AI intensive workloads, with an AI dashboard to measure, track and help report on cloud carbon emissions. With watsonx, IBM offers an AI development studio with access to IBMcurated and trained foundation models and open-source models, access to a data store to gather and clean up training and tune data,

Data Science Platform Market Report - Table of Contents

1. INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2. RESEARCH METHODOLOGY

3. EXECUTIVE SUMMARY

4. MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Bargaining Power of Suppliers
    • 4.2.2 Bargaining Power of Consumers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitutes
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Impact of Macroeconomic Trends

5. MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Rapid Increase in Big Data
    • 5.1.2 Emerging Promising Use Cases of Data Science and Machine Learning
    • 5.1.3 Shift of Organizations Toward Data-intensive Approach and Decisions
  • 5.2 Market Restraints
    • 5.2.1 Lack of Skillset in Workforce
    • 5.2.2 Data Security and Reliability Concerns
  • 5.3 Key Use Cases
  • 5.4 Ecosystem Analysis
  • 5.5 Analysis of Pricing and Pricing Models
  • 5.6 Key Capabilities of Data Science Platforms (AI & Ml, Analytics, Visualization, Exploration, Modelling)

6. MARKET SEGMENTATION

  • 6.1 By Offering
    • 6.1.1 Platform
    • 6.1.2 Services
  • 6.2 By Deployment
    • 6.2.1 On-premise
    • 6.2.2 Cloud
  • 6.3 By Size of Enterprises
    • 6.3.1 Small and Medium Enterprises
    • 6.3.2 Large Enterprises
  • 6.4 By Industry Vertical
    • 6.4.1 IT and Telecom
    • 6.4.2 BFSI
    • 6.4.3 Retail and E-commerce
    • 6.4.4 Oil Gas and Energy
    • 6.4.5 Manufacturing
    • 6.4.6 Government and Defense
    • 6.4.7 Other Industry Verticals
  • 6.5 By Geography
    • 6.5.1 North America
    • 6.5.1.1 United States
    • 6.5.1.2 Canada
    • 6.5.2 Europe
    • 6.5.2.1 United Kingdom
    • 6.5.2.2 Germany
    • 6.5.2.3 France
    • 6.5.2.4 Italy
    • 6.5.2.5 Spain
    • 6.5.2.6 Greece
    • 6.5.2.7 Rest of Europe
    • 6.5.3 Asia Pacific
    • 6.5.3.1 China
    • 6.5.3.2 India
    • 6.5.3.3 Japan
    • 6.5.3.4 Australia
    • 6.5.3.5 Southeast Asia
    • 6.5.3.5.1 Indonesia
    • 6.5.3.5.2 Philippines
    • 6.5.3.5.3 Malaysia
    • 6.5.3.5.4 Singapore
    • 6.5.3.5.5 Rest of Southeast Asia
    • 6.5.3.6 Rest of Asia Pacific
    • 6.5.4 Latin America
    • 6.5.4.1 Brazil
    • 6.5.4.2 Argentina
    • 6.5.4.3 Mexico
    • 6.5.4.4 Rest of Latin America
    • 6.5.5 Middle East and Africa
    • 6.5.5.1 Saudi Arabia
    • 6.5.5.2 GCC
    • 6.5.5.2.1 United Arab Emirates
    • 6.5.5.2.2 Rest of GCC
    • 6.5.5.3 South Africa
    • 6.5.5.4 Rest of Middle East and Africa

7. COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 IBM Corporation
    • 7.1.2 Google LLC (Alphabet Inc.)
    • 7.1.3 Microsoft Corporation
    • 7.1.4 SAS
    • 7.1.5 Alteryx
    • 7.1.6 The MathWorks Inc.
    • 7.1.7 RapidMiner
    • 7.1.8 Databricks
    • 7.1.9 Amazon Web Services Inc. (AMAZON.COM INC.)
    • 7.1.10 DataRobot Inc.
  • *List Not Exhaustive

8. VENDOR SHARE ANALYSIS

9. RANKING OF VENDORS AT A REGIONAL LEVEL

10. INVESTMENT ANALYSIS

11. FUTURE OF THE MARKET

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Data Science Platform Industry Segmentation

The data science platform puts the entire data modeling process in the hands of data science teams so they can focus on deriving insights from data and communicating them to key stakeholders in the business. The market studied comprises applications such as marketing and sales. And others, which are mainly deployed on-premises and cloud-based with the platform.

The data science platform market is segmented by offering (platform, services), deployment (on-premise, cloud), size of enterprises (small and medium enterprises, large enterprises), industry vertical (IT and telecom, BFSI, manufacturing, Retail and E-commerce, government and defense and oil gas and energy), and geography (North America [United States, Canada], Europe [Germany, United Kingdom, France, Italy, Spain, Greece, Rest of Europe], Asia Pacific [China, Japan, India, Australia, Southeast Asia [[Indonesia, Philippines, Malaysia, Singapore, Rest of Southeast Asia]], Rest of Asia Pacific], Latin America [Brazil, Argentina, Mexico, Rest of Latin America], Middle East & Africa [Saudi Arabia, GCC [United Arab Emirates, Rest of GCC], South Africa, Rest of Middle East & Africa]). The report offers market forecasts and size in value (USD) for all the above segments.

By Offering Platform
Services
By Deployment On-premise
Cloud
By Size of Enterprises Small and Medium Enterprises
Large Enterprises
By Industry Vertical IT and Telecom
BFSI
Retail and E-commerce
Oil Gas and Energy
Manufacturing
Government and Defense
Other Industry Verticals
By Geography North America United States
Canada
Europe United Kingdom
Germany
France
Italy
Spain
Greece
Rest of Europe
Asia Pacific China
India
Japan
Australia
Southeast Asia Indonesia
Philippines
Malaysia
Singapore
Rest of Southeast Asia
Rest of Asia Pacific
Latin America Brazil
Argentina
Mexico
Rest of Latin America
Middle East and Africa Saudi Arabia
GCC United Arab Emirates
Rest of GCC
South Africa
Rest of Middle East and Africa
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Data Science Platform Market Research FAQs

How big is the Data Science Platform Market?

The Data Science Platform Market size is expected to reach USD 12.54 billion in 2025 and grow at a CAGR of 23.5% to reach USD 36.01 billion by 2030.

What is the current Data Science Platform Market size?

In 2025, the Data Science Platform Market size is expected to reach USD 12.54 billion.

Who are the key players in Data Science Platform Market?

IBM Corporation, Google LLC (Alphabet Inc.), Microsoft Corporation, SAS and Alteryx are the major companies operating in the Data Science Platform Market.

Which is the fastest growing region in Data Science Platform Market?

Asia Pacific is estimated to grow at the highest CAGR over the forecast period (2025-2030).

Which region has the biggest share in Data Science Platform Market?

In 2025, the North America accounts for the largest market share in Data Science Platform Market.

What years does this Data Science Platform Market cover, and what was the market size in 2024?

In 2024, the Data Science Platform Market size was estimated at USD 9.59 billion. The report covers the Data Science Platform Market historical market size for years: 2019, 2020, 2021, 2022, 2023 and 2024. The report also forecasts the Data Science Platform Market size for years: 2025, 2026, 2027, 2028, 2029 and 2030.

Data Science Platform Industry Report

Statistics for the 2025 Data Science Platform market share, size and revenue growth rate, created by Mordor Intelligence™ Industry Reports. Data Science Platform analysis includes a market forecast outlook for 2025 to 2030 and historical overview. Get a sample of this industry analysis as a free report PDF download.