Data Science Platform Market Size and Share
Data Science Platform Market Analysis by Mordor Intelligence
The data science platform market is valued at USD 111.23 billion in 2025 and is forecast to climb to USD 275.67 billion in 2030, advancing at a 21.43% CAGR. Demand escalates as enterprises consolidate machine-learning operations, data engineering, and business-intelligence workflows on a single stack that satisfies tighter governance rules under the EU AI Act and similar frameworks. [1]ISACA, “Understanding the EU AI Act: Requirements and Next Steps,” isaca.org Momentum also stems from growing edge-to-cloud fabrics that accommodate unstructured IoT and video streams, the need for scalable feature stores, and cloud providers’ rollout of high-density GPU instances. North American leadership remains anchored in mature cloud infrastructure, while Asia-Pacific’s accelerating investment in generative AI and data-center capacity underpins its status as the fastest-growing region. Competitive intensity is rising as hyperscalers embed native AI tooling and specialist vendors differentiate through open-format data sharing, hybrid deployment, and domain-specific accelerators.
Key Report Takeaways
- By offering, platforms held 72% of the data science platform market share in 2024; services are projected to expand at a 24.3% CAGR to 2030.
- By deployment, cloud models commanded 78% of the data science platform market size in 2024 and are set to grow at a 21.9% CAGR through 2030.
- By enterprise size, large enterprises captured 65% of the data science platform market share in 2024, while small and medium enterprises lead growth at 22.4% CAGR.
- By end-user industry, BFSI led with a 24% revenue share of the data science platform market size in 2024; retail and e-commerce is advancing at a 22.1% CAGR through 2030.
- By geography, North America retained 40% of the data science platform market share in 2024; Asia-Pacific is forecast to grow at a 25.7% CAGR to 2030.
Global Data Science Platform Market Trends and Insights
Drivers Impact Analysis
Driver | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
---|---|---|---|
Proliferation of Open-Source ML Frameworks Catalyzing Platform Convergence | +3.2% | Global, with concentration in North America and EU | Medium term (2-4 years) |
Stricter Model-Governance Regulations (EU AI Act et al.) Triggering Managed-Platform Uptake | +2.8% | EU core, spill-over to North America and APAC | Short term (≤ 2 years) |
Edge-to-Cloud Data-Fabric Adoption Enabling Hybrid DS Platforms in Manufacturing | +2.1% | Global, with early gains in Germany, Japan, China | Medium term (2-4 years) |
Explosion of Unstructured IoT and Video Data Requiring Scalable Feature Stores | +4.3% | Global, particularly strong in APAC manufacturing hubs | Long term (≥ 4 years) |
Source: Mordor Intelligence
Proliferation of Open-Source ML Frameworks Catalyzing Platform Convergence
TensorFlow and PyTorch have evolved into full-stack ecosystems that cut model-prototyping time and simplify distributed training, encouraging enterprises to shift from bespoke stacks to vendor-managed platforms that remain framework agnostic. The resulting convergence allows mid-market firms to plug into unified environments without heavy engineering overhead, accelerating time-to-value. Patent families addressing AI/ML infrastructure climbed 45% year-over-year, signaling continued innovation that platform providers harness to avoid vendor lock-in and bolster governance. [2]World Intellectual Property Organization, “Global Patenting and Research in GenAI,” wipo.int
Stricter Model-Governance Regulations Triggering Managed-Platform Uptake
The EU AI Act, effective August 2024, imposes risk-management and audit-trail duties that favor turnkey platforms offering built-in compliance dashboards, automated documentation, and continuous monitoring. Extraterritorial reach compels non-EU firms to adopt similar capabilities to serve European customers, while penalties up to 7% of global turnover sharpen the cost of non-compliance. Government initiatives such as France’s EUR 30 billion (USD 33 billion) AI fund strengthen demand for compliant infrastructure.
Edge-to-Cloud Data-Fabric Adoption Enabling Hybrid Platforms in Manufacturing
Automakers and electronics assemblers deploy data fabrics that unify factory-floor sensors with centralized lakes, reducing operational expenses by double-digit percentages and enabling sub-millisecond response times for quality inspection. [3]International Journal of Engineering Research & Technology, “Empowering Industry 4.0 with Industrial Data Platforms,” ijgis.pubpub.org Hybrid designs let local nodes pre-process high-frequency signals while cloud hubs orchestrate model retraining and governance, blending latency-sensitive control with enterprise-wide analytics.
Explosion of Unstructured IoT and Video Data Requiring Scalable Feature Stores
IoT devices are on track to generate 79.4 zettabytes of data by 2025, and 95% of firms cite difficulty wrangling unstructured formats. Advanced platforms integrate computer-vision pipelines, automated labeling, and versioned feature stores that handle both streaming and batch workloads, enabling retailers, manufacturers, and security agencies to operationalize video analytics while meeting retention and audit mandates.
Restraints Impact Analysis
Restraint | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
---|---|---|---|
Data-Residency Barriers Hampering Multi-Region Roll-outs in Public Sector EU | -1.8% | EU core, with regulatory spill-over effects | Short term (≤ 2 years) |
Shortage of ML-Ops Engineers Undermining Complex Deployments | -2.4% | Global, particularly acute in North America and EU | Medium term (2-4 years) |
Escalating Cloud Bills Creating Budget Pushback for Real-Time Training Workloads | -1.9% | Global, with highest impact in North America and EU | Short term (≤ 2 years) |
Legacy Data Silos in Energy and Utilities Delaying Platform ROI | -1.6% | Global, particularly acute in North America and Europe | Medium term (2-4 years) |
Source: Mordor Intelligence
Data-Residency Barriers Hampering Multi-Region Roll-outs in EU Public Sector
GDPR and sovereignty rules force public entities to confine processing within national borders, complicating multinational deployments. The EU trails the US by USD 1.36 trillion in ICT investment, and 43% of cross-border SMEs struggle with location mandates that narrow vendor options to providers offering in-region hosting. [4]European Centre for International Political Economy, “The EU's Trillion Dollar Gap in ICT and Cloud Computing Capacities,” ecipe.org
Shortage of MLOps Engineers Undermining Complex Deployments
Only 13% of ML projects make it to production, largely because firms lack professionals skilled in automated testing, CI/CD for models, and lineage tracking. The talent deficit nudges enterprises toward managed services or simplified feature sets, raising implementation costs and slowing innovation.
Segment Analysis
By Offering: Services Surge Despite Platform Dominance
Platforms contributed 72% of the data science platform market in 2024, reflecting enterprise appetite for integrated toolchains that cover ingestion to model monitoring. Yet services are expanding at a 24.3% CAGR as firms purchase advisory, customization, and managed capabilities to operationalize complex workloads. Vendor revenue models increasingly blend licenses with professional engagements to curb customer churn and assure compliance readiness.
Service momentum traces back to the MLOps skills gap: enterprises lacking deployment expertise outsource design, automation, and monitoring. As a result, the services slice of the data science platform market size is projected to widen steadily through 2030, reinforcing the ecosystem’s shift from pure software sales to outcome-based partnerships.
By Deployment: Cloud Supremacy Reinforced by AI Workloads
Cloud deployments accounted for 78% of the data science platform market share in 2024, underpinned by the need for elastic GPU clusters and AI-optimized storage. Providers report that half of incremental infrastructure revenue since 2023 stems directly from generative AI workloads.
With a 21.9% CAGR ahead, cloud remains the primary engine of the data science platform market. On-premise and hybrid implementations persist in heavily regulated verticals, but even those users increasingly offload dev-test stages to the cloud while keeping production pipelines within sovereign zones. Edge nodes now form an adjunct layer, enabling latency-critical inference yet remaining orchestrated from centralized consoles.
By Enterprise Size: SME Acceleration Challenges Large-Enterprise Dominance
Large enterprises held 65% of 2024 revenue thanks to entrenched data estates and compliance budgets. However, SME uptake is racing ahead at 22.4% CAGR as vendors introduce browser-based notebooks, automated feature engineering, and pay-as-you-go pricing. Cloud-first delivery eliminates server procurement and shifts expenditures to operating budgets, lowering barriers for finance, retail, and healthcare challengers.
The democratization reshapes vendor go-to-market motions: lightweight bundles, marketplace channels, and guided wizards target non-specialist users. As a result, SME penetration is poised to shrink the dominance gap, though large enterprises will still account for the majority of absolute spend in the data science platform market size.
By End-User Industry: BFSI Leadership Faces Retail Disruption
BFSI institutions commanded 24% of 2024 revenue, leveraging platforms for fraud detection, credit scoring, and algorithmic trading. Cloud adoption in banking surged from 37% in 2020 to 91% by late 2023, accelerating demand for audit-ready, policy-enforced tooling.
Retail and e-commerce record the steepest trajectory at 22.1% CAGR as personalization, inventory optimization, and omnichannel analytics demand real-time insights. Industry roll-outs of computer-vision shelf monitoring and dynamic pricing engines illustrate how data science platforms underpin consumer-facing agility. Manufacturing, healthcare, and public sector follow, focusing on predictive maintenance, drug discovery, and smart-city governance respectively.
Geography Analysis
North America retains 40% of the data science platform market share in 2024, bolstered by USD 68.4 billion in Q1 2025 cloud-service revenue from the top three hyperscalers. Venture funding, patent leadership, and a dense partner ecosystem nurture advanced deployments, though rising infrastructure costs push providers to bankroll record capital budgets exceeding USD 100 billion for additional capacity.
Asia-Pacific is the fastest expanding arena, growing at 25.7% CAGR on the back of China’s generative-AI outlays and India’s doubling data-center footprint. Regional data-center power surpassed 12 GW operational, providing the backbone for sustained expansion. Government programs such as Australia’s Digital Economy Strategy and China’s Three-Year Data Factor Action Plan create policy pull that underwrites platform adoption.
Europe sits at a regulatory crossroads: the EU AI Act fuels platform demand, yet a USD 1.36 trillion ICT investment gap plus sovereignty imperatives compel providers to build local hosting and encryption. Fragmented markets raise costs, but initiatives such as Germany’s Industry 4.0 and France’s AI stimulus (EUR 30 billion / USD 33 billion) incentivize compliant, sovereign-cloud solutions. Global sovereign-cloud spending is forecast to cross USD 250 billion by 2027.

Competitive Landscape
Competition in the data science platform market pivots on infrastructure depth, ecosystem breadth, and industry specificity. AWS, Microsoft Azure, and Google Cloud collectively captured 63% of global cloud services in early 2025, giving them scale advantages in GPU fleets and integrated governance tooling. AWS posted USD 29.3 billion in Q1 2025 revenue, while Microsoft’s AI business exceeded a USD 13 billion run rate, underlining hyperscaler resource depth.
Specialist vendors pursue differentiation through open data formats, multi-cloud orchestration, and domain accelerators. Databricks crossed USD 3 billion ARR in 2024 and targets a USD 62 billion IPO valuation, signaling investor confidence in lakehouse convergence. Snowflake delivered USD 3.626 billion 2025 revenue and lifted guidance after early-2026 product-revenue topped USD 1 billion. Midsize players add value via auto-ML, low-code interfaces, and embedded model governance.
Strategic moves illustrate intensifying rivalry. Hyperscalers integrate foundation-model services to lock in data gravity; platform pure-plays partner with BI and MLOps specialists to broaden reach; and vertical apps vendors embed analytics engines to cultivate stickiness. Patent output in AI/ML infrastructure continues to grow at roughly 45% yearly, underscoring sustained technological arms races that will shape future data science platform market dynamics.
Data Science Platform Industry 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 Institute Inc.
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Alteryx Inc.
- *Disclaimer: Major Players sorted in no particular order

Recent Industry Developments
- June 2025: Dataiku named Snowflake AI Data Cloud Product Partner of the Year, extending joint go-to-market programs and integrating automated ML with Snowflake’s native governance. The collaboration tightens both firms’ position in regulated BFSI and manufacturing segments.
- June 2025: SandP Global closed the TeraHelix acquisition to bolster data-linking and graph-analytics capabilities, aligning its risk-analytics suite with advanced feature engineering that accelerates compliance modeling.
- May 2025: Snowflake raised its fiscal-2026 revenue outlook above USD 1 billion after Q1 over-performance, signaling sustained enterprise migration to cloud-native lakehouse architectures.
- March 2025: Adobe launched its AI Platform at Adobe Summit, unifying creative and marketing workflows; Adobe Experience Platform revenue climbed 50% YoY, showing cross-portfolio synergy in content-driven analytics.
Global Data Science Platform Market Report Scope
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 Enterprise Size | Small and Medium Enterprises | ||||
Large Enterprises | |||||
By End-user Industry | IT and Telecom | ||||
BFSI | |||||
Retail and E-commerce | |||||
Manufacturing | |||||
Energy and Utilities | |||||
Healthcare and Life Sciences | |||||
Government and Defense | |||||
Other End-user Industries | |||||
By Geography | North America | United States | |||
Canada | |||||
Mexico | |||||
Europe | United Kingdom | ||||
Germany | |||||
France | |||||
Italy | |||||
Spain | |||||
Rest of Europe | |||||
Asia-Pacific | China | ||||
India | |||||
Japan | |||||
South Korea | |||||
Australia and New Zealand | |||||
Rest of Asia-Pacific | |||||
South America | Brazil | ||||
Argentina | |||||
Rest of South America | |||||
Middle East and Africa | Middle East | GCC | United Arab Emirates | ||
Saudi Arabia | |||||
Qatar | |||||
Rest of GCC | |||||
Turkey | |||||
Rest of Middle East | |||||
Africa | South Africa | ||||
Nigeria | |||||
Rest of Africa |
Platform |
Services |
On-Premise |
Cloud |
Small and Medium Enterprises |
Large Enterprises |
IT and Telecom |
BFSI |
Retail and E-commerce |
Manufacturing |
Energy and Utilities |
Healthcare and Life Sciences |
Government and Defense |
Other End-user Industries |
North America | United States | |||
Canada | ||||
Mexico | ||||
Europe | United Kingdom | |||
Germany | ||||
France | ||||
Italy | ||||
Spain | ||||
Rest of Europe | ||||
Asia-Pacific | China | |||
India | ||||
Japan | ||||
South Korea | ||||
Australia and New Zealand | ||||
Rest of Asia-Pacific | ||||
South America | Brazil | |||
Argentina | ||||
Rest of South America | ||||
Middle East and Africa | Middle East | GCC | United Arab Emirates | |
Saudi Arabia | ||||
Qatar | ||||
Rest of GCC | ||||
Turkey | ||||
Rest of Middle East | ||||
Africa | South Africa | |||
Nigeria | ||||
Rest of Africa |
Key Questions Answered in the Report
What is the current size of the data science platform market?
The market is valued at USD 111.23 billion in 2025 and is projected to reach USD 275.67 billion by 2030.
Which region is growing fastest in the data science platform market?
Asia-Pacific is forecast to expand at a 25.70% CAGR, buoyed by large-scale AI investments in China, India, and Japan.
Why are services growing faster than platforms?
Enterprises face talent shortages in MLOps and regulatory complexity, prompting them to buy consulting and managed services that ensure successful deployment.
How big is cloud’s share of the data science platform market?
Cloud deployments account for 78% of 2024 revenue and are expected to grow at a 21.90% CAGR through 2030.
Which industries lead adoption?
BFSI holds 24% market share due to fraud and compliance use cases, while retail and e-commerce is the fastest climber at a 22.1% CAGR.
What impact does the EU AI Act have on platform demand?
The Act’s stringent governance rules favor managed platforms with built-in compliance, adding an estimated 2.8 percentage points to forecast CAGR growth in affected regions.