Enterprise Data Management Market Size, Growth & Share Analysis

Name: Enterprise Data Management Market Size, Growth & Share Analysis | 2030
Creator: Mordor Intelligence
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Enterprise Data Management Market Size and Share

Market Overview

Study Period	2019 - 2030
Market Size (2025)	USD 122.84 Billion
Market Size (2030)	USD 205.98 Billion
Growth Rate (2025 - 2030)	10.89% CAGR
Fastest Growing Market	Asia Pacific
Largest Market	North America
Market Concentration	Medium
Major Players *Disclaimer: Major Players sorted in no particular order Image © Mordor Intelligence. Reuse requires attribution under CC BY 4.0.

Enterprise Data Management Market (2025 - 2030) — Image © Mordor Intelligence. Reuse requires attribution under CC BY 4.0.

Enterprise Data Management Market Analysis by Mordor Intelligence

The enterprise data management market is valued at USD 122.84 billion in 2025 and is projected to advance at a 10.89% CAGR, reaching USD 205.98 billion by 2030. Expansion is propelled by the convergence of AI-enabled data-fabric architectures, the rapid scale-up of cloud-native platforms, and global data-privacy mandates that elevate compliance spending. Explosive IoT and edge deployments are creating unprecedented unstructured-data volumes, forcing enterprises to prioritize modern data fabrics that automate classification, lineage, and governance. Growth also reflects a strategic pivot from reactive governance to data-as-a-product models, where sovereign-cloud requirements fragment traditional hyperscale roll-outs yet reinforce the need for unified control planes. Demand accelerates as enterprises seek to reconcile ESG audit obligations with real-time analytics, while a persistent skills shortage intensifies outsourcing toward managed service providers.

Key Report Takeaways

By component, software retained 62.78% of 2024 revenue, yet services are forecast to expand at a 12.40% CAGR through 2030.
By deployment model, on-premises installations held 55.43% of 2024 revenue, whereas cloud implementations are projected to rise at a 14.80% CAGR to 2030.
By enterprise size, large enterprises controlled 59.55% of 2024 revenue; small and midsize firms are poised to grow at a 13.60% CAGR through 2030.
By end-use industry, BFSI led with 28.92% of 2024 revenue, while healthcare is set to expand at a 14.00% CAGR through 2030.
By geography, North America commanded 33.77% of 2024 revenue; the Asia-Pacific region is projected to pace the market with a 13.90% CAGR through 2030.

Global Enterprise Data Management Market Trends and Insights

Drivers Impact Analysis

Driver	(~) % Impact on CAGR Forecast	Geographic Relevance	Impact Timeline
Explosive data growth from IoT / edge devices	+2.8%	Global, led by Asia-Pacific	Medium term (2-4 years)
Tightening global data-privacy regulations	+2.1%	North America and EU; expanding to Asia-Pacific	Long term (≥ 4 years)
Cloud-native EDM platforms accelerate time-to-value	+1.9%	Global, strongest in cloud-first regions	Short term (≤ 2 years)
AI-enabled data-fabric architectures cut integration cost	+1.7%	North America and EU core markets	Medium term (2-4 years)
ESG audit and reporting mandates boost master-data accuracy	+1.2%	EU leading; North America following	Long term (≥ 4 years)
Low-code platforms democratize EDM adoption for SMEs	+1.0%	Global, pronounced in emerging digital economies	Short term (≤ 2 years)
Explosive data growth from IoT / edge devices	+2.8%	Global, led by Asia-Pacific	Medium term (2-4 years)

Source: Mordor Intelligence

Explosive data growth from IoT / edge devices

Enterprises will manage 180 zettabytes of unstructured data in 2025, with 60% of Asia-Pacific manufacturers already relying on AI models to govern edge data flows.^{[1]Expereo, “Digital Silk Road Drives Asia-Pacific Edge Adoption,” expereo.com} Real-time sensor data elevates the need for low-latency processing, prompting a 23% year-over-year rise in cloud-infrastructure spend to USD 94 billion during Q1 2025. Organizations must harmonize edge streams with core systems, accelerating adoption of AI-driven data fabrics that auto-classify and route data in compliance with sector-specific mandates.

Tightening global data-privacy regulations

The EU Corporate Sustainability Reporting Directive compels nearly 50,000 firms to disclose 800 data points beginning 2025, driving large-scale adoption of automated lineage and compliance tools. Simultaneously, SEC climate rules require third-party assurance of emissions data, extending governance complexity. Sovereign-cloud strategies have gained traction, with 37% of European enterprises already investing to maintain jurisdictional control, a figure expected to rise within two years.^{[2]Accenture, “Sovereign Cloud: Catalyzing the Next Digital Wave,” accenture.com}Enterprises therefore pivot to multi-cloud frameworks combined with granular policy engines that manage disparate residency laws while upholding user-privacy commitments.

Cloud-native EDM platforms accelerate time-to-value

API-first and serverless designs enable enterprises to cut integration cycles by 50%, eliminating most manual migration bottlenecks. Separation of compute and storage lets organizations scale resources on demand, while unified dataspaces such as VAST Data’s model permit real-time analytics without traditional ETL. Oracle’s cloud-infrastructure revenue rose 52% in Q4 2025 as organizations moved mission-critical workloads from on-premises to cloud-native stacks.^{[3]Oracle, “Q4 2025 Earnings Press Release,” oracle.com} Faster deployment is increasingly essential for AI roll-outs that depend on immediate, high-quality data streams.

AI-enabled data-fabric architectures cut integration cost

As 93% of enterprise data remains unstructured, AI-driven fabrics create a virtualized layer that grants unified access without physically relocating data ibm.com. Automated discovery and quality enforcement can reduce infrastructure cost by 30% while boosting data-quality scores by 98%. IBM’s acquisition of DataStax highlights the strategic priority of aligning unstructured and structured assets within one fabric to support emerging agentic AI workflows. This approach mitigates silo proliferation and improves ROI on multi-cloud deployments.

Restraints Impact Analysis

Restraint	(~) % Impact on CAGR Forecast	Geographic Relevance	Impact Timeline
Shortage of data-governance talent inflates service costs	-1.8%	Global; acute in North America and EU	Short term (≤ 2 years)
Complex legacy integration raises migration risk	-1.4%	North America and EU legacy-heavy markets	Medium term (2-4 years)
Rising sovereign-cloud demands fragment global roll-outs	-1.1%	EU leading; Asia-Pacific following	Long term (≥ 4 years)
Vendor lock-in fears on hyperscaler ecosystems	-0.9%	Global enterprise markets	Medium term (2-4 years)

Source: Mordor Intelligence

Shortage of data-governance talent inflates service costs

Sixty percent of data professionals cite skills gaps as the chief barrier to AI initiatives, and 42% report that talent scarcity degrades data quality targets. Premium salaries for AI governance, data ethics, and sovereign-cloud roles elevate consulting fees, extending project timelines. As 67% of mature organizations introduce new generative-AI roles, internal teams must upskill rapidly or cede ground to specialized providers, concentrating successful deployments within well-resourced firms.

Complex legacy integration raises migration risk

Seventy-three percent of enterprises blame incompatible formats for two-thirds of integration failures, while hidden dependencies can inflate project budgets by 40%. Regulated sectors must perform extensive validation, lengthening timelines beyond acceptable thresholds. Cultural resistance also emerges when decades-old business logic embedded in mainframes needs reinterpretation, complicating change-management programs and elevating the probability of disruption.

Segment Analysis

By Component: Services outpace software as outsourcing accelerates

Software contributed 62.78% of 2024 revenue, underlining its foundational role in data integration, master-data, and security platforms that anchor the enterprise data management market. Yet services will post a 12.40% CAGR through 2030 as enterprises confront rising complexity and use managed expertise to mitigate internal skills gaps. The shift reflects a preference for outcome-based engagements that guarantee regulatory compliance and uptime. Professional services targeting AI integration and sovereign-cloud configuration are in greatest demand, while managed offerings for real-time data quality monitoring gain traction. This pivot from ownership to consumption dovetails with the finding that 60% of data leaders identify skills shortages as a primary obstacle, a gap that service partners readily fill.

Providers now deliver bundled platforms that unite advisory, implementation, and run-time support, reinforcing retention and expanding wallet share. Within software, security and master-data modules show resilient growth as privacy laws tighten, whereas traditional ETL tools morph into AI-enabled constructs that auto-generate integration pipelines. The component mix suggests continued movement toward cloud-delivered, micro-service architectures that can be orchestrated by external specialists, further fueling outsourced-services momentum.

By Deployment Model: Hybrid sovereignty reshapes cloud strategy

On-premises estates still accounted for 55.43% of the enterprise data management market share in 2024, yet the cloud track will grow 14.80% annually to 2030 as organizations seek elasticity and lower time-to-value. Data sovereignty weighs heavily: 88% of large companies rate jurisdictional control as business-critical, spurring interest in sovereign clouds that blend local control with hyperscale economics. As a result, workload placement is becoming dynamic; sensitive records remain on-premises or within sovereign zones, while analytical sandboxes migrate to low-latency public-cloud regions. Hybrid orchestration platforms that enforce common governance policies across locations have become a core purchase criterion.

Vendor lock-in fears further encourage multi-cloud architectures. Eighty-three percent of enterprises planned workload repatriation from public clouds in 2024, up sharply from 43% in 2020. This necessitates flexible data fabrics that span diverse environments without disrupting lineage or security controls, explaining the surge in fabric-centric roadmaps among leading vendors.

By End-user Enterprise Size: Low-code tools unlock SME participation

Large enterprises held 59.55% of 2024 revenue thanks to scale, dedicated data teams, and sizable compliance budgets. However, small and midsize enterprises (SMEs) will outpace with a 13.60% CAGR through 2030. Low-code and no-code platforms abstract data pipelines behind intuitive interfaces, allowing non-specialists to build governance routines. Subscription pricing further eases adoption, eliminating capital barriers that once restricted SME entry. Vendors are packaging simplified editions that preserve core lineage, catalog, and quality functions while reducing configuration overhead, fostering rapid deployment cycles measured in weeks rather than months.

Meanwhile, large enterprises shift focus to optimization, consolidating disparate tools into unified control planes and embedding AI to automate quality checks. They also pilot sovereign-cloud blueprints to satisfy cross-border compliance. The divergent priorities of SMEs and large firms ensure sustained demand across the value chain—from streamlined SaaS suites to bespoke advisory engagements.

By End-Use Industry: Healthcare climbs fastest under privacy pressure

Financial services retained 28.92% of 2024 revenue, supported by trade surveillance, risk analytics, and stringent capital-market reporting mandates. Healthcare will chart the highest growth at 14.00% CAGR to 2030, propelled by HIPAA, GDPR, and state-level privacy laws that require auditable lineage for patient data. Telehealth expansion since the pandemic multiplied data volumes, adding impetus for modern master-data systems that unify clinical, operational, and research datasets. Manufacturing maintains steady investment to enable predictive maintenance and quality analytics across Industry 4.0 lines, while retail prioritizes personalization and supply-chain resilience.

Healthcare providers increasingly demand zero-trust architectures that encrypt data in motion and at rest while enabling real-time clinician access. Vendors able to demonstrate certified compliance, automated anonymization, and AI-ready data fabrics stand to capture outsized share of new deployments.

Geography Analysis

North America led with 33.77% of 2024 revenue, leveraging advanced regulatory frameworks and early cloud-native adoption across finance and technology. Enterprises allocate significant budgets to comply with SEC climate disclosures and state privacy laws, spurring demand for integrated governance suites. Europe follows closely, its growth anchored in GDPR enforcement and a rapid pivot to sovereign-cloud constructs; 37% of regional enterprises already run sovereign instances, with more to come as the EU embeds digital-sovereignty objectives in policy planning. Asia-Pacific, however, will exhibit the strongest expansion at 13.90% CAGR through 2030, underpinned by massive investments in data centers and the Digital Silk Road program that broadens regional connectivity. Manufacturing and telecom spending dominate, striving to harness edge-generated data for AI-enabled applications.

The Middle East and Africa show steady but smaller growth, reflecting nascent regulatory regimes and ongoing infrastructure development. Latin America’s momentum is tied to open-banking regulations and e-commerce growth that escalate real-time data-management requirements. Collectively, these patterns underscore a multipolar landscape where localized regulations, data-residency rules, and infrastructure maturity shape deployment decisions, driving the need for globally consistent yet regionally adaptable platforms.

Competitive Landscape

The market remains moderately concentrated. Oracle, IBM, SAP, and Microsoft continue to leverage end-to-end platforms and active acquisition pipelines. Oracle’s cloud revenue climbed 27% year-on-year to USD 6.7 billion in fiscal 2025, reflecting demand for integrated database-to-application stacks. Salesforce reinforced its positioning through an USD 8 billion Informatica acquisition that folds advanced data-integration and governance functions into its CRM ecosystem. IBM’s USD 6.4 billion purchase of HashiCorp highlights the strategic priority of automating multi-cloud configuration at scale.

Challengers such as Snowflake, Collibra, Alation, and Confluent concentrate on high-growth niches—data lakehouses, data catalogs, and streaming platforms—offering open architectures that minimize lock-in. Interoperability has become a decisive factor; enterprises routinely evaluate whether a vendor’s AI-governance roadmap aligns with existing security postures and sovereign-cloud requirements. Competitive differentiation thus hinges on embedding generative-AI assistants that reduce manual stewardship, ecosystem partnerships that certify plug-and-play integrations, and flexible consumption models that adjust to unpredictable data volumes.

Enterprise Data Management Industry Leaders

Oracle Corporation
Amazon Web Services Inc.
Informatica Inc.
SAP SE
IBM Corporation
*Disclaimer: Major Players sorted in no particular order

Enterprise Data Management Market Concentration — Image © Mordor Intelligence. Reuse requires attribution under CC BY 4.0.

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Recent Industry Developments

March 2025: IBM introduced the Transformation Suite for SAP Applications, automating technical assessment and data migration to shorten S/4HANA projects.
June 2025: Sema4.ai secured USD 25 million in Series A-extension funding to scale its AI-agent platform integrated with Snowflake Marketplace.
April 2025: Huawei unveiled its AI Data Lake Solution, uniting storage, governance, and AI toolchains to accelerate analytics workloads.
January 2025: Prophecy raised USD 47 million in Series B1 to enhance AI-driven data-integration software for cloud migrations.

Table of Contents for Enterprise Data Management Industry Report

1. INTRODUCTION

1.1 Study Assumptions and Market Definition
1.2 Scope of the Study

2. RESEARCH METHODOLOGY

3. EXECUTIVE SUMMARY

4. MARKET LANDSCAPE

4.1 Market Overview
4.2 Market Drivers
- 4.2.1 Explosive Data Growth from IoT/Edge Devices
- 4.2.2 Tightening Global Data-Privacy Regulations (GDPR, CCPA, etc.)
- 4.2.3 Cloud-Native EDM Platforms Accelerate Time-to-Value
- 4.2.4 AI-Enabled Data-Fabric Architectures Cut Integration Cost
- 4.2.5 ESG Audit and Reporting Mandates Boost Master-Data Accuracy Needs
4.3 Market Restraints
- 4.3.1 Shortage of Data-Governance Talent Inflates Service Costs
- 4.3.2 Complex Legacy Integration Raises Migration Risk
- 4.3.3 Rising Sovereign-Cloud Demands Fragment Global Roll-Outs
- 4.3.4 Vendor Lock-In Fears on Hyperscaler Ecosystems
4.4 Value Chain Analysis
4.5 Regulatory Landscape
4.6 Technological Outlook
4.7 Porter's Five Forces Analysis
- 4.7.1 Bargaining Power of Suppliers
- 4.7.2 Bargaining Power of Buyers
- 4.7.3 Threat of New Entrants
- 4.7.4 Threat of Substitutes
- 4.7.5 Intensity of Competitive Rivalry
4.8 Pricing and Cost Analysis

5. MARKET SIZE AND GROWTH FORECASTS (VALUE)

5.1 By Component
- 5.1.1 Software
- 5.1.1.1 Data Security
- 5.1.1.2 Master Data Management
- 5.1.1.3 Data Integration and ETL
- 5.1.1.4 Data Warehousing
- 5.1.1.5 Data Migration
- 5.1.1.6 Metadata Management
- 5.1.1.7 Data Quality and Stewardship
- 5.1.2 Services
- 5.1.2.1 Professional Services
- 5.1.2.2 Managed Services
5.2 By Deployment Model
- 5.2.1 On-Premises
- 5.2.2 Cloud
5.3 By End-user Enterprise Size
- 5.3.1 Large Enterprises
- 5.3.2 Small and Medium Enterprises
5.4 By End-Use Industry
- 5.4.1 IT and Telecommunication
- 5.4.2 Healthcare and Life Sciences
- 5.4.3 Retail and E-commerce
- 5.4.4 Manufacturing
- 5.4.5 Government and Public Sector
- 5.4.6 Energy and Utilities
- 5.4.7 Education
- 5.4.8 Others
5.5 By Geography
- 5.5.1 North America
- 5.5.1.1 United States
- 5.5.1.2 Canada
- 5.5.1.3 Mexico
- 5.5.2 South America
- 5.5.2.1 Brazil
- 5.5.2.2 Argentina
- 5.5.2.3 Colombia
- 5.5.2.4 Rest of South America
- 5.5.3 Europe
- 5.5.3.1 Germany
- 5.5.3.2 United Kingdom
- 5.5.3.3 France
- 5.5.3.4 Spain
- 5.5.3.5 Russia
- 5.5.3.6 Rest of Europe
- 5.5.4 Asia-Pacific
- 5.5.4.1 China
- 5.5.4.2 Japan
- 5.5.4.3 India
- 5.5.4.4 South Korea
- 5.5.4.5 Australia
- 5.5.4.6 Rest of Asia-Pacific
- 5.5.5 Middle East and Africa
- 5.5.5.1 Middle East
- 5.5.5.1.1 Saudi Arabia
- 5.5.5.1.2 United Arab Emirates
- 5.5.5.1.3 Turkey
- 5.5.5.1.4 Rest of Middle East
- 5.5.5.2 Africa
- 5.5.5.2.1 South Africa
- 5.5.5.2.2 Nigeria
- 5.5.5.2.3 Kenya
- 5.5.5.2.4 Rest of Africa

6. COMPETITIVE LANDSCAPE

6.1 Market Concentration
6.2 Strategic Moves
6.3 Market Share Analysis
6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, and Recent Developments)
- 6.4.1 Oracle Corporation
- 6.4.2 International Business Machines (IBM) Corporation
- 6.4.3 SAP SE
- 6.4.4 Amazon Web Services Inc.
- 6.4.5 Microsoft Corporation
- 6.4.6 Informatica Inc.
- 6.4.7 Cloud Software Group Inc. (TIBCO)
- 6.4.8 Teradata Corporation
- 6.4.9 Cloudera Inc.
- 6.4.10 Semarchy SAS
- 6.4.11 Ataccama Corporation
- 6.4.12 Collibra NV
- 6.4.13 Talend SA
- 6.4.14 SAS Institute Inc.
- 6.4.15 Alation Inc.
- 6.4.16 Reltio Inc.
- 6.4.17 Denodo Technologies
- 6.4.18 Dell Boomi Inc.
- 6.4.19 Profisee Group Inc.
- 6.4.20 Snowflake Inc.
- 6.4.21 Qlik Technologies Inc.

7. MARKET OPPORTUNITIES AND FUTURE OUTLOOK

7.1 White-space and Unmet-Need Assessment

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Global Enterprise Data Management Market Report Scope

Enterprise Data Management (EDM) encompasses the processes, tools, and strategies that organizations employ to manage, integrate, and govern their data assets. By ensuring data accuracy, accessibility, and security, EDM empowers organizations to make informed decisions and operate efficiently. As data volumes surge from sources like IoT, cloud platforms, and varied systems, EDM becomes paramount for compliance, analytics, and business agility. Key sectors, including BFSI, manufacturing, and healthcare, are driving the market, all aiming to harness data as a strategic asset.

The Enterprise Data Management Market is Segmented by component (software (data security, master data management, data warehousing, data migration, metadata management, and other software), services (professional services, managed services)), deployment (on-premise, cloud), enterprise size (large enterprise, small and medium enterprise), end-use Industry (IT and telecommunication, BFSI, healthcare, retail, manufacturing, education, and other end-use industries) 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.

By Component	Software	Data Security
		Master Data Management
		Data Integration and ETL
		Data Warehousing
		Data Migration
		Metadata Management
		Data Quality and Stewardship

	Services	Professional Services
		Managed Services
By Deployment Model	On-Premises
	Cloud
By End-user Enterprise Size	Large Enterprises
	Small and Medium Enterprises
By End-Use Industry	IT and Telecommunication
	Healthcare and Life Sciences
	Retail and E-commerce
	Manufacturing
	Government and Public Sector
	Energy and Utilities
	Education
	Others

By Geography	North America	United States
		Canada
		Mexico

	South America	Brazil
		Argentina
		Colombia
		Rest of South America

	Europe	Germany
		United Kingdom
		France
		Spain
		Russia
		Rest of Europe

	Asia-Pacific	China
		Japan
		India
		South Korea
		Australia
		Rest of Asia-Pacific

	Middle East and Africa	Middle East	Saudi Arabia
			United Arab Emirates
			Turkey
			Rest of Middle East

		Africa	South Africa
			Nigeria
			Kenya
			Rest of Africa

By Component

Software	Data Security
	Master Data Management
	Data Integration and ETL
	Data Warehousing
	Data Migration
	Metadata Management
	Data Quality and Stewardship
Services	Professional Services
	Managed Services

By Deployment Model

On-Premises

Cloud

By End-user Enterprise Size

Large Enterprises

Small and Medium Enterprises

By End-Use Industry

IT and Telecommunication

Healthcare and Life Sciences

Retail and E-commerce

Manufacturing

Government and Public Sector

Energy and Utilities

Education

Others

By Geography

North America	United States
	Canada
	Mexico
South America	Brazil
	Argentina
	Colombia
	Rest of South America
Europe	Germany
	United Kingdom
	France
	Spain
	Russia
	Rest of Europe
Asia-Pacific	China
	Japan
	India
	South Korea
	Australia
	Rest of Asia-Pacific

Middle East and Africa	Middle East	Saudi Arabia
		United Arab Emirates
		Turkey
		Rest of Middle East

	Africa	South Africa
		Nigeria
		Kenya
		Rest of Africa

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Key Questions Answered in the Report

How big is the Enterprise Data Management Market?

The Enterprise Data Management Market size is expected to reach USD 122.84 billion in 2025 and grow at a CAGR of 10.89% to reach USD 205.98 billion by 2030.

What is the current size of the enterprise data management market?

The enterprise data management market is valued at USD 122.84 billion in 2025 and is forecast to reach USD 205.98 billion by 2030.

Which segment is growing fastest within the enterprise data management market?

Services are expanding at a 12.40% CAGR as organizations outsource expertise to manage rising governance complexity.

Why is healthcare adopting enterprise data management platforms rapidly?

Healthcare faces stringent patient-privacy regulations and growing telehealth data volumes, driving a 14.00% CAGR for EDM solutions in the sector. is estimated to grow at the highest CAGR over the forecast period (2025-2030).

How do data-privacy regulations affect deployment models?

Tightening laws encourage hybrid and sovereign-cloud strategies so that sensitive data remains within jurisdictional boundaries while still leveraging cloud scalability.

What technologies most reduce data-integration costs?

AI-enabled data fabrics virtualize access to disparate sources, lowering integration costs by connecting data without physical movement and automating quality checks.