AaaS(Analytics as a Service) 시장 : 점유율 분석, 산업 동향, 통계, 성장 예측(2025-2030년)

The Analytics as a Service Market size is estimated at USD 20.56 billion in 2025, and is expected to reach USD 56.49 billion by 2030, at a CAGR of 22.40% during the forecast period (2025-2030).

Demand is rising because cloud-first data-modernization programs allow enterprises to retire on-premises analytics stacks and shift to pay-as-you-go services. The fast spread of vector-native data stores is also enabling real-time processing of unstructured data for generative AI. Public cloud deployments lead today, yet hybrid strategies are advancing as firms balance cost control with data-sovereignty rules. Competitive intensity is mounting as hyperscale platforms deepen AI capabilities while specialist providers focus on vertical solutions and embedded analytics. Talent shortages and data-egress economics, however, continue to influence implementation timelines and ROI calculations.

Global Analytics As A Service Market Trends and Insights

Cloud-First Enterprise Data-Modernization Programmes

Modernization projects are motivating organisations to consolidate siloed data into cloud-native platforms that support AI-ready pipelines. IBM reports that a majority of large enterprises plan to run most workloads in the cloud by 2025, underscoring a pivot away from legacy data warehouses. Vendors position full-stack migration toolkits to simplify workload portability, automate schema conversion, and uphold security controls across multi-region environments. Financial services, healthcare, and retail adopters cite quicker time-to-insight and lower infrastructure overhead as primary benefits. As spending shifts from capital expenditure to operating expenditure, service providers differentiate on transparent pricing, integrated governance, and pre-built AI services to accelerate deployment.

Proliferation of Gen-AI-Ready, Vector-Native Data Stores

Vector databases are helping firms unlock unstructured content for generative AI search, recommendation, and chat experiences. Oracle embedded automated vector stores inside its HeatWave GenAI offering. Salesforce followed by enabling vector capabilities in Data Cloud. These integrations simplify similarity queries at scale without separate indexing layers. Enterprises gain the ability to combine text, audio, and image embeddings with transactional data inside a single platform, reducing latency and operational complexity. Early adopters in retail and media use the approach to personalise experiences, while industrial firms employ vector search to refine quality-inspection models. Market entrants emphasise open-source compatibility and orchestrated pipelines that ease model retraining.

Escalating Hyperscaler Egress-Fee Economics

Data-transfer fees can represent 10%-15% of a typical cloud invoice. These charges deter multi-cloud analytics architectures because shifting terabytes between platforms inflates total cost of ownership. The UK Competition and Markets Authority flagged egress fees as a switching barrier. Although some providers have introduced fee waivers under certain conditions, customers still face contractual hurdles. Service integrators now promote architectures that keep large datasets in neutral storage tiers or employ data-in-motion optimisation, such as Rackspace's Data Freedom offering, claiming up to 85% cost reduction.

Other drivers and restraints analyzed in the detailed report include:

1. Rising Pay-as-You-Go Demand from SMB Cloud Migrations
2. Compliance-Driven Real-Time Audit Analytics
3. Shortage of FinOps and Data-Ops Talent

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Large Enterprises accounted for 64% of 2024 revenue as they leverage deep budgets to deploy enterprise-wide data lakes and advanced modelling tools. Their analytics estates often integrate with long-standing ERP and CRM systems, enabling cross-functional dashboards and AI-driven forecasting. Multi-nationals also prioritise sovereignty controls, leading to region-specific deployments that interconnect via private backbone networks.

SMEs contribute a smaller share today yet will record the highest 24.3% CAGR to 2030. Pay-as-you-go pricing and turnkey templates lower barriers for firms without dedicated data-science teams. No-code interfaces, auto-ML services, and packaged vertical analytics help founders draw insights quickly, supporting inventory optimisation and targeted marketing. As SMB adoption broadens, vendors pilot simplified FinOps consoles that map workload cost to business KPIs, fostering transparent budgeting across finance and operations teams. The influx of SMEs broadens the Analytics as a Service market customer base, encouraging providers to release lightweight service tiers and community-led education.

Public cloud maintained 48.3% of 2024 revenue because its shared infrastructure grants instant elasticity, global reach, and continuous feature upgrades. Start-ups and digital natives rely on fully managed analytics stacks, avoiding data-centre expenditures while accessing the latest AI accelerators. However, firms in regulated industries retain sensitive workloads in private environments to satisfy residency mandates and internal risk policies.

Hybrid architectures are set to expand at a 26.7% CAGR, blending public scalability with private-cloud control. IBM notes that hybrid deployments improve flexibility by letting teams locate data and compute where each performs best. Enterprises commonly stage raw data in private object stores, then burst to public clusters for large-scale model training. This topology mitigates egress fees and supports tiered disaster-recovery postures. As sovereignty requirements rise, providers introduce region-specific sovereign cloud zones and inter-cloud networking services, further reinforcing hybrid appeal within the Analytics as a Service market.

Analytics As A Service Market is Segmented by Enterprise Size (Small and Medium Enterprises and Large Enterprises), Deployment Model (Public Cloud, Private Cloud, and Hybrid Cloud), Analytics Type (Descriptive Analytics, Diagnostic Analytics, and More), End-User Industry (IT and Telecommunication, BFSI, Healthcare and Life-Sciences, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Geography Analysis

North America held 42.8% of 2024 revenue, anchored by widespread cloud adoption, mature AI talent pools, and constant product innovation from dominant hyperscalers. United States enterprises in healthcare, retail, and media apply large-scale analytics to personalise experiences, optimise logistics, and drive precision medicine. Government agencies also expand data-sharing initiatives that fuel analytic workloads. Canadian organisations follow with fast uptake of sovereign cloud zones that fulfil public-sector data-residency laws. Mexico's manufacturing corridors integrate cloud analytics into export-oriented supply chains, closing operational insight gaps.

Asia-Pacific is projected to produce the highest 25.4% CAGR, driven by aggressive digital-economic agendas in China, Japan, India, and Southeast Asia. Rapidly scaling e-commerce platforms ingest terabytes of behavioural data daily, while fintechs roll out credit models targeting underserved populations. Local cloud providers partner with multinational hyperscalers to build regionally compliant infrastructure, lowering latency and enabling sovereign-ready Analytics as a Service market offerings. Government stimulus programmes for smart-factory rollouts further stimulate demand, and SMEs leverage low-cost service bundles to leapfrog legacy systems.

Europe occupies a significant share shaped by privacy and AI governance frameworks. Strict GDPR enforcement and forthcoming EU AI Act rules push firms to deploy explainable models, audit layers, and sovereign cloud controls. AWS announced a Germany-based corporate entity to operate an independent European Sovereign Cloud with launch targeted for late 2025. Financial institutions implement multi-region redundancy to maintain operational resilience, while manufacturers connect IoT data into analytics pipelines that support energy-efficiency targets. The Analytics as a Service market in Europe thus balances innovation with compliance, promoting hybrid patterns that satisfy both business and regulatory imperatives.

1. Amazon Web Services
2. Microsoft Corporation
3. Google Cloud (Alphabet Inc.)
4. IBM Corporation
5. SAP SE
6. Oracle Corporation
7. Hewlett Packard Enterprise
8. SAS Institute
9. Accenture PLC
10. Teradata Corporation
11. Snowflake Inc.
12. Databricks, Inc.
13. Salesforce, Inc.
14. Tableau Software, LLC
15. QlikTech International AB
16. MicroStrategy Incorporated
17. TIBCO Software, Inc.
18. Alteryx, Inc.
19. Splunk Inc.
20. Domo, Inc.
21. Sisense Ltd.
22. ThoughtSpot, Inc.
23. Looker Studio (Google)
24. GoodData, Inc.
25. Zoho Analytics (Zoho Corporation)

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

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 LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Cloud-first enterprise data-modernization programmes
  • 4.2.2 Proliferation of Gen-AI-ready, vector-native data stores
  • 4.2.3 Rising pay-as-you-go demand from SMB cloud migrations
  • 4.2.4 Compliance-driven real-time audit analytics (e.g., DORA, SEC)
  • 4.2.5 Embedded analytics in vertical SaaS 'mini-clouds'
  • 4.2.6 Sovereign-cloud mandates spurring regional AaaS build-outs
• 4.3 Market Restraints
  • 4.3.1 Escalating hyperscaler egress-fee economics
  • 4.3.2 Shortage of FinOps and data-ops talent
  • 4.3.3 Model-explainability regulations delaying roll-outs
  • 4.3.4 Carbon-intensity quotas limiting non-green data-centre use
• 4.4 Industry Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Key Performance Indicators (KPIs)
• 4.8 Industry Attractiveness - Porter's Five Forces Analysis
  • 4.8.1 Threat of New Entrants
  • 4.8.2 Bargaining Power of Buyers
  • 4.8.3 Bargaining Power of Suppliers
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Intensity of Competitive Rivalry
• 4.9 Impact of Macroeconomic Factors on the Market

5 MARKET SIZE AND GROWTH FORECASTS (VALUES)

• 5.1 By Enterprise Size
  • 5.1.1 Small and Medium Enterprises (SME)
  • 5.1.2 Large Enterprises
• 5.2 By Deployment Model
  • 5.2.1 Public Cloud
  • 5.2.2 Private Cloud
  • 5.2.3 Hybrid Cloud
• 5.3 By Analytics Type
  • 5.3.1 Descriptive Analytics
  • 5.3.2 Diagnostic Analytics
  • 5.3.3 Predictive Analytics
  • 5.3.4 Prescriptive Analytics
• 5.4 By End-user Industry
  • 5.4.1 IT and Telecommunication
  • 5.4.2 BFSI
  • 5.4.3 Healthcare and Life-Sciences
  • 5.4.4 Retail and E-Commerce
  • 5.4.5 Manufacturing
  • 5.4.6 Energy and Utilities
  • 5.4.7 Government and Public Sector
  • 5.4.8 Other End-user Industries
• 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 Chile
    • 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 Italy
    • 5.5.3.5 Spain
    • 5.5.3.6 Russia
    • 5.5.3.7 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 Singapore
    • 5.5.4.7 Malaysia
    • 5.5.4.8 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 Egypt
    • 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 Amazon Web Services
  • 6.4.2 Microsoft Corporation
  • 6.4.3 Google Cloud (Alphabet Inc.)
  • 6.4.4 IBM Corporation
  • 6.4.5 SAP SE
  • 6.4.6 Oracle Corporation
  • 6.4.7 Hewlett Packard Enterprise
  • 6.4.8 SAS Institute
  • 6.4.9 Accenture PLC
  • 6.4.10 Teradata Corporation
  • 6.4.11 Snowflake Inc.
  • 6.4.12 Databricks, Inc.
  • 6.4.13 Salesforce, Inc.
  • 6.4.14 Tableau Software, LLC
  • 6.4.15 QlikTech International AB
  • 6.4.16 MicroStrategy Incorporated
  • 6.4.17 TIBCO Software, Inc.
  • 6.4.18 Alteryx, Inc.
  • 6.4.19 Splunk Inc.
  • 6.4.20 Domo, Inc.
  • 6.4.21 Sisense Ltd.
  • 6.4.22 ThoughtSpot, Inc.
  • 6.4.23 Looker Studio (Google)
  • 6.4.24 GoodData, Inc.
  • 6.4.25 Zoho Analytics (Zoho Corporation)

7 MARKET OPPORTUNITIES AND FUTURE TRENDS

• 7.1 White-Space and Unmet-Need Assessment