Data Science Platform Market Size
| Study Period | 2019-2029 |
| Market Size (2024) | USD 10.15 Billion |
| Market Size (2029) | USD 29.98 Billion |
| CAGR (2024 - 2029) | 23.50 % |
| Fastest Growing Market | Asia Pacific |
| Largest Market | North America |
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 10.15 billion in 2024, and is expected to reach USD 29.98 billion by 2029, growing at a CAGR of 23.5% during the forecast period (2024-2029).
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 Market Trends
Small and Medium Enterprises to Witness Major Growth
- Small-sized organizations have less than 100 employees, whereas medium-sized enterprises have between 100 to 999 employees. One of the major applications of data science for small businesses is using it to track clients throughout the various stages of the sales cycle. Small businesses can utilize data analytics to determine a particular segment of consumers willing to buy. Data-driven industry growth is making evidence-based conclusions to enhance sales, performance, and operations, among others, through which businesses can achieve sustainable development.
- SMEs often operate with limited resources, making every decision critical. Data science platforms empower SMEs to make more precise and informed decisions, reducing risks. The platforms help SMEs identify inefficiencies in their operations and supply chains, reducing costs.
- In August 2023, Infor Nexus and DBS Bank, in partnership, announced the launch of pre-shipment financing for small and medium-sized enterprises (SME) suppliers in the Infor Nexus supply chain ecosystem. This solution utilizes historical data from the Infor Nexus platform to provide data-based lending solutions that help suppliers meet their working capital requirements.
- Cloud adoption is expected to boost the market's growth. It has revolutionized how SMEs access and utilize data science platforms. Cloud infrastructure offers scalability, allowing SMEs to seamlessly scale their data science capabilities up or down based on their changing needs. In November 2023, AnniQ launched a new service focusing on data analytics to support the strategic capabilities of small and medium-sized enterprises (SMEs). This service is designed to enhance how SMEs engage with and utilize data in their business operations, emphasizing providing actionable insights and facilitating strategic execution.
North America to Hold Significant Market Share
- Fueled by data's increasing volume and complexity, the United States continues to innovate and consolidate its position in the global market in the data science platforms. The embracing of advanced technologies such as advanced analytics, Artificial Intelligence (AI), and Machine Learning (ML) in the market studied has also directly impacted the national economy.
- According to Telecom Advisory Services, the estimated Internet traffic in the United States has jumped from 64 million exabytes per month in 2021 to 98.64 million exabytes per month in 2023. Such a significant increase in data traffic needs more advanced data science solutions to manage a large amount of data and improve the solutions based on extracted data. Additionally, organizations are generating more data than ever, which is becoming increasingly complex and diverse. This makes it difficult to analyze and extract insights from data using traditional methods. Data science platforms provide the tools and infrastructure to manage and analyze large and complex databases.
- Moreover, all the major vendors studied in the market are US-based. Additionally, the country is on the brink of the fourth industrial revolution, where data is being utilized in large-scale production while integrating the data with a wide variety of manufacturing systems throughout the supply chain. This is accelerating the adoption of advanced technologies in the country.
- The government in the region is also promoting the adoption of robotics by taking initiatives to support the growth of modern technologies in the market. For instance, the US federal government has launched the National Robotics Initiative (NRI) program to strengthen the capabilities of building domestic robots in the nation and encourage research activities in the field. Such initiatives are further expected to create a positive outlook for the market growth.
- In addition, the strong focus on research and innovation in Canada in sectors like healthcare, artificial intelligence, and renewable energy supports the market requiring data science platforms to analyze complex data sets and gain research insights. Canada's tech industry is flourishing, and the country has made a concerted effort to attract technological know-how. A rising number of sectors, including banking, healthcare, finance, insurance, media and entertainment, telecom, and e-commerce, need qualified Data Scientists and AI experts. Professionals are in greater demand right now than they are available. Expanding technological capabilities and the demand for high-end IT solutions, AI, and ML will drive the market for data science platforms in Canada.
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
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IBM Corporation
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Google LLC (Alphabet Inc.)
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Microsoft Corporation
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SAS
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Alteryx
*Disclaimer: Major Players sorted in no particular order
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
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 | ||||||||||||||
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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 10.15 billion in 2024 and grow at a CAGR of 23.5% to reach USD 29.98 billion by 2029.
What is the current Data Science Platform Market size?
In 2024, the Data Science Platform Market size is expected to reach USD 10.15 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 (2024-2029).
Which region has the biggest share in Data Science Platform Market?
In 2024, the North America accounts for the largest market share in Data Science Platform Market.
Data Science Platform Industry Report
Statistics for the 2024 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 to for 2024 to 2029 and historical overview. Get a sample of this industry analysis as a free report PDF download.
