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1856957

全球資料網格架構市場：預測至 2032 年—按解決方案、部署方式、應用程式、最終用戶和區域進行分析

Data Mesh Architecture Market Forecasts to 2032 - Global Analysis By Solution, Deployment Mode, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2025 年，全球資料網格架構市場規模將達到 14 億美元，到 2032 年將達到 49 億美元，預測期內複合年成長率為 19.5%。

資料網格架構是一種去中心化的資料管理方法，它將資料視為一種產品，並將所有權分配給特定領域的團隊。與依賴集中式資料湖或資料倉儲不同，將資料責任分散到不同的業務領域可以實現擴充性、更快的存取速度和更高的資料品質。每個領域的團隊都使用標準化的互通性原則來管理、共用和治理自己的資料。這種架構促進了自主性、跨職能協作和自助式資料基礎設施，使組織能夠有效率地處理大型、複雜且不斷演進的資料生態系統。

數據民主化和可近性

企業正從集中式資料湖轉向面向領域的模型，使每個團隊都能擁有並維護資料。業務部門正在利用網格化原則來減少瓶頸並縮短洞察獲取時間。與自助式分析和協作管治的整合提高了易用性和合規性。資料網格支援產品、營運和分析團隊之間可擴展的協作。這些能力正在推動資料基礎設施的去中心化和敏捷性。

文化和組織方面的挑戰

許多公司在將所有權從集中式 IT 團隊過渡到分散式領域團隊的過程中舉步維艱。資料素養不足和跨職能協作不良會延緩新方法的採用和管治成熟度的提升。對變革的抵觸情緒和不明確的責任制機制會阻礙執行。遺留的層級結構和孤立的工作流程會降低網狀架構原則的有效性。這些障礙持續限制企業級轉型和營運一致性。

採用雲端原生技術

雲端平台提供模組化服務，用於資料整合、管治和資料可觀測性，並遵循網格原則。無伺服器運算、容器編配和 API 驅動的設計正在推動可擴展的資料產品開發。供應商正在推出支援網域所有權和互通性的網格解決方案。與資料目錄、血緣工具和策略引擎的整合正在提升信任度和可發現性。這些創新正在加速企業為分散式資料架構做好準備。

平台和技術複雜性

組織必須整合多種工具來實現跨域資料攝取、轉換、管治和存取控制。元資料缺乏標準化、模式演化以及服務等級協定的缺失，使得互通性變得複雜。監控和調試分散式管道需要高度的可觀測性和DevOps成熟度。供應商碎片化和架構蔓延增加了營運成本和風險。這些挑戰持續阻礙網狀環境中的一致性和可擴展性。

新冠疫情的影響：

疫情加速了人們對分散式資料策略的關注，遠距辦公和數位化營運成為常態。企業面臨跨地域、跨團隊即時洞察的更高需求。資料網格原則在動盪時期為敏捷決策和本地化所有權提供了支援。各行各業的雲端遷移和數位轉型工作都取得了顯著進展。疫情後的策略開始將網格架構納入長期彈性和可擴展性計畫。這種轉變正在加速對領域主導資料基礎設施的投資。

預計在預測期內，資料整合和分發板塊將成為最大的板塊。

預計在預測期內，資料整合和分發領域將佔據最大的市場佔有率，因為它在實現領域級資料產品和互通性發揮基礎性作用。該領域涵蓋 ETL 管道、資料映射、轉換引擎、串流平台等。企業正在投資支援跨領域即時和批量處理的模組化整合工具。供應商提供低程式碼和 API 優先的解決方案，簡化了上線流程並提高了可擴充性。與管治和可觀測性層的整合正在提升信任度和合規性。這些能力正在鞏固該領域在網狀資料基礎設施中的主導地位。

預計在預測期內，人工智慧/機器學習模型訓練和特徵儲存領域將實現最高的複合年成長率。

預計在預測期內，人工智慧/機器學習模型訓練和特徵儲存領域將呈現最高的成長率。特徵儲存為模型開發和部署提供標準化、可重複使用的資料資產。領域團隊正在使用基於網格的管道來管理訓練資料、元資料和血緣關係。與 MLOps 平台和模型註冊的整合正在提高可追溯性和效能。各行業對分散式實驗和即時推理的需求正在不斷成長。

佔比最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於其先進的雲端基礎設施、成熟的企業資料水準和完善的供應商生態系統。美國企業正在金融、醫療保健、零售和科技等行業採用資料網格，以提高敏捷性和管治。對雲端原生平台和資料產品工具的投資正在推動資料網格的普及。主要軟體供應商和開放原始碼社群的存在促進了創新和標準化。法律規範和資料隱私法規正在加強領域層面的責任制。這些因素共同推動了北美在資料網格架構領域的領先地位。

複合年成長率最高的地區：

預計亞太地區在預測期內將實現最高的複合年成長率，這主要得益於數位轉型、雲端運算應用和分散式資料策略的整合。印度、中國、新加坡和澳洲等國家正在銀行、通訊和公共服務等領域推廣網狀聯邦平台。政府支持的雲端舉措和資料管治計畫正在協助企業做好充分準備。本地企業正在推出符合區域合規性和基礎設施需求的網狀原生解決方案。行動優先和分散式組織正在推動可擴展即時分析的需求。

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    • 基於產品系列、地域覆蓋和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 引言

  • 概述
  • 相關利益者
  • 分析範圍
  • 分析方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 分析方法
  • 分析材料
    • 原始研究資料
    • 二手研究資訊來源
    • 先決條件

第3章 市場趨勢分析

  • 介紹
  • 促進要素
  • 抑制因素
  • 市場機遇
  • 威脅
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的感染疾病

第4章 波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代產品的威脅
  • 新參與企業的威脅
  • 公司間的競爭

5. 全球資料網格架構市場（按解決方案分類）

  • 資料整合與分發
  • ETL 工具
  • 數據管道
  • 資料映射和轉換
  • 協作式資料管治
  • 元資料管理
  • 數據品質與安全
  • 資料處理
  • 數據可觀測性和監測
  • 資料沿襲及編目

6. 全球資料網格架構市場以部署方式分類

  • 本地部署
  • 雲端基礎的

7. 全球資料網格架構市場（按應用分類）

  • 顧客體驗與互動
  • 資料隱私合規管理
  • 物聯網監控與分析
  • 即時決策
  • AI/ML模型訓練和特徵存儲
  • 其他用途

8. 全球資料網格架構市場（依最終用戶分類）

  • 銀行、金融服務和保險（BFSI）
  • 零售與電子商務
  • 資訊科技/通訊
  • 醫學與生命科​​學
  • 政府/公共部門
  • 製造業/工業
  • 能源與公用事業
  • 其他最終用戶

9. 全球資料網格架構市場（按地區分類）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第10章：主要趨勢

  • 合約、商業夥伴關係和合資企業
  • 企業合併（M&A）
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第11章 公司簡介

  • IBM Corporation
  • Oracle Corporation
  • Informatica Inc.
  • SAP SE
  • Cinchy Inc.
  • Intenda（Pty）Ltd.
  • NextData, Inc.
  • K2View Ltd.
  • Accenture plc
  • ThoughtWorks, Inc.
  • Starburst Data, Inc.
  • Denodo Technologies, Inc.
  • Zaloni, Inc.
  • DataKitchen, Inc.
  • Tata Consultancy Services Ltd.
Product Code: SMRC31821

According to Stratistics MRC, the Global Data Mesh Architecture Market is accounted for $1.4 billion in 2025 and is expected to reach $4.9 billion by 2032 growing at a CAGR of 19.5% during the forecast period. Data Mesh Architecture is a decentralized data management approach that treats data as a product and assigns ownership to domain-specific teams. Instead of relying on a centralized data lake or warehouse, it distributes data responsibilities across different business domains, enabling scalability, faster access, and better quality. Each domain team manages, shares, and governs its own data using standardized interoperability principles. This architecture promotes autonomy, cross-functional collaboration, and self-serve data infrastructure, helping organizations efficiently handle large-scale, complex, and evolving data ecosystems.

Market Dynamics:

Driver:

Data democratization and accessibility

Organizations are shifting from centralized data lakes to domain-oriented models that empower teams to own and serve their data. Business units are using mesh principles to reduce bottlenecks and improve time-to-insight. Integration with self-service analytics and federated governance is enhancing usability and compliance. Data mesh is enabling scalable collaboration across product, operations, and analytics teams. These capabilities are propelling decentralization and agility in data infrastructure.

Restraint:

Cultural and organizational challenges

Many firms struggle to shift ownership from centralized IT to distributed domain teams. Lack of data literacy and cross-functional alignment slows adoption and governance maturity. Resistance to change and unclear accountability models create friction in execution. Legacy hierarchies and siloed workflows degrade the effectiveness of mesh principles. These barriers continue to constrain enterprise-wide transformation and operational consistency.

Opportunity:

Adoption of cloud-native technologies

Cloud platforms offer modular services for data integration, governance, and observability that align with mesh principles. Serverless computing, container orchestration, and API-driven design are enabling scalable data product development. Vendors are launching mesh-ready solutions that support domain ownership and interoperability. Integration with data catalogs, lineage tools, and policy engines is improving trust and discoverability. These innovations are fostering enterprise readiness for distributed data architecture.

Threat:

Platform and technology complexity

Organizations must integrate multiple tools for ingestion, transformation, governance, and access control across domains. Lack of standardization in metadata, schema evolution, and service-level agreements complicates interoperability. Monitoring and debugging distributed pipelines require advanced observability and DevOps maturity. Vendor fragmentation and architectural sprawl increase operational overhead and risk. These challenges continue to hamper consistency and scalability in mesh environments.

Covid-19 Impact:

The pandemic accelerated interest in decentralized data strategies as remote work and digital operations became the norm. Enterprises faced rising demand for real-time insights across distributed teams and geographies. Data mesh principles supported agile decision-making and localized ownership during disruption. Cloud migration and digital transformation initiatives gained momentum across sectors. Post-pandemic strategies now include mesh architecture as part of long-term resilience and scalability planning. These shifts are accelerating investment in domain-driven data infrastructure.

The data integration & delivery segment is expected to be the largest during the forecast period

The data integration & delivery segment is expected to account for the largest market share during the forecast period due to its foundational role in enabling domain-level data products and interoperability. This segment includes ETL pipelines, data mapping, transformation engines, and streaming platforms. Enterprises are investing in modular integration tools that support real-time and batch processing across domains. Vendors are offering low-code and API-first solutions that simplify onboarding and scalability. Integration with governance and observability layers is improving reliability and compliance. These capabilities are boosting segment dominance across mesh-aligned data infrastructure.

The AI/ML model training & feature stores segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the AI/ML model training & feature stores segment is predicted to witness the highest growth rate as organizations adopt mesh principles to scale machine learning across domains. Feature stores are enabling standardized, reusable data assets for model development and deployment. Domain teams are using mesh-aligned pipelines to manage training data, metadata, and lineage. Integration with MLOps platforms and model registries is improving traceability and performance. Demand for decentralized experimentation and real-time inference is rising across industries.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to its advanced cloud infrastructure, enterprise data maturity, and vendor ecosystem. U.S. firms are deploying data mesh across finance, healthcare, retail, and technology sectors to improve agility and governance. Investment in cloud-native platforms and data product tooling is supporting mesh adoption. Presence of leading software vendors and open-source communities is driving innovation and standardization. Regulatory frameworks and data privacy mandates are reinforcing domain-level accountability. These factors are boosting North America's leadership in data mesh architecture.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR as digital transformation, cloud adoption, and decentralized data strategies converge. Countries like India, China, Singapore, and Australia are scaling mesh-aligned platforms across banking, telecom, and public services. Government-backed cloud initiatives and data governance programs are supporting enterprise readiness. Local firms are launching mesh-native solutions tailored to regional compliance and infrastructure needs. Demand for scalable, real-time analytics is rising across mobile-first and distributed organizations.

Key players in the market

Some of the key players in Data Mesh Architecture Market include IBM Corporation, Oracle Corporation, Informatica Inc., SAP SE, Cinchy Inc., Intenda (Pty) Ltd., NextData, Inc., K2View Ltd., Accenture plc, ThoughtWorks, Inc., Starburst Data, Inc., Denodo Technologies, Inc., Zaloni, Inc., DataKitchen, Inc. and Tata Consultancy Services Ltd.

Key Developments:

In March 2025, IBM partnered with Cloudera and Red Hat to integrate open data lakehouse capabilities into its Watsonx.data platform. This collaboration supports decentralized data ownership and federated governance-core principles of data mesh. It enables enterprises to manage domain-specific data products across hybrid cloud environments with enhanced lineage, access control, and AI readiness.

In January 2025, Oracle expanded its partnership with Microsoft Azure to support multi-cloud data mesh deployments. This integration enables federated data governance and decentralized access across Oracle Autonomous Database and Azure Synapse. It supports hybrid analytics and AI workloads, aligning with enterprise demand for interoperable, domain-oriented data infrastructure.

Solutions Covered:

  • Data Integration & Delivery
  • ETL Tools
  • Data Pipelines
  • Data Mapping & Transformation
  • Federated Data Governance
  • Metadata Management
  • Data Quality & Security
  • Data Operations
  • Observability & Monitoring
  • Data Lineage & Cataloging

Deployment Modes Covered:

  • On-Premise
  • Cloud-Based

Applications Covered:

  • Customer Experience & Engagement
  • Data Privacy & Compliance Management
  • IoT Monitoring & Analytics
  • Real-Time Decisioning
  • AI/ML Model Training & Feature Stores
  • Other Applications

End Users Covered:

  • Banking, Financial Services & Insurance (BFSI)
  • Retail & E-Commerce
  • IT & Telecom
  • Healthcare & Life Sciences
  • Government & Public Sector
  • Manufacturing & Industrial
  • Energy & Utilities
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Data Mesh Architecture Market, By Solution

  • 5.1 Introduction
  • 5.2 Data Integration & Delivery
  • 5.3 ETL Tools
  • 5.4 Data Pipelines
  • 5.5 Data Mapping & Transformation
  • 5.6 Federated Data Governance
  • 5.7 Metadata Management
  • 5.8 Data Quality & Security
  • 5.9 Data Operations
  • 5.10 Observability & Monitoring
  • 5.11 Data Lineage & Cataloging

6 Global Data Mesh Architecture Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 On-Premise
  • 6.3 Cloud-Based

7 Global Data Mesh Architecture Market, By Application

  • 7.1 Introduction
  • 7.2 Customer Experience & Engagement
  • 7.3 Data Privacy & Compliance Management
  • 7.4 IoT Monitoring & Analytics
  • 7.5 Real-Time Decisioning
  • 7.6 AI/ML Model Training & Feature Stores
  • 7.7 Other Applications

8 Global Data Mesh Architecture Market, By End User

  • 8.1 Introduction
  • 8.2 Banking, Financial Services & Insurance (BFSI)
  • 8.3 Retail & E-Commerce
  • 8.4 IT & Telecom
  • 8.5 Healthcare & Life Sciences
  • 8.6 Government & Public Sector
  • 8.7 Manufacturing & Industrial
  • 8.8 Energy & Utilities
  • 8.9 Other End Users

9 Global Data Mesh Architecture Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 IBM Corporation
  • 11.2 Oracle Corporation
  • 11.3 Informatica Inc.
  • 11.4 SAP SE
  • 11.5 Cinchy Inc.
  • 11.6 Intenda (Pty) Ltd.
  • 11.7 NextData, Inc.
  • 11.8 K2View Ltd.
  • 11.9 Accenture plc
  • 11.10 ThoughtWorks, Inc.
  • 11.11 Starburst Data, Inc.
  • 11.12 Denodo Technologies, Inc.
  • 11.13 Zaloni, Inc.
  • 11.14 DataKitchen, Inc.
  • 11.15 Tata Consultancy Services Ltd.

List of Tables

  • Table 1 Global Data Mesh Architecture Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Data Mesh Architecture Market Outlook, By Solution (2024-2032) ($MN)
  • Table 3 Global Data Mesh Architecture Market Outlook, By Data Integration & Delivery (2024-2032) ($MN)
  • Table 4 Global Data Mesh Architecture Market Outlook, By ETL Tools (2024-2032) ($MN)
  • Table 5 Global Data Mesh Architecture Market Outlook, By Data Pipelines (2024-2032) ($MN)
  • Table 6 Global Data Mesh Architecture Market Outlook, By Data Mapping & Transformation (2024-2032) ($MN)
  • Table 7 Global Data Mesh Architecture Market Outlook, By Federated Data Governance (2024-2032) ($MN)
  • Table 8 Global Data Mesh Architecture Market Outlook, By Metadata Management (2024-2032) ($MN)
  • Table 9 Global Data Mesh Architecture Market Outlook, By Data Quality & Security (2024-2032) ($MN)
  • Table 10 Global Data Mesh Architecture Market Outlook, By Data Operations (2024-2032) ($MN)
  • Table 11 Global Data Mesh Architecture Market Outlook, By Observability & Monitoring (2024-2032) ($MN)
  • Table 12 Global Data Mesh Architecture Market Outlook, By Data Lineage & Cataloging (2024-2032) ($MN)
  • Table 13 Global Data Mesh Architecture Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 14 Global Data Mesh Architecture Market Outlook, By On-Premise (2024-2032) ($MN)
  • Table 15 Global Data Mesh Architecture Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 16 Global Data Mesh Architecture Market Outlook, By Application (2024-2032) ($MN)
  • Table 17 Global Data Mesh Architecture Market Outlook, By Customer Experience & Engagement (2024-2032) ($MN)
  • Table 18 Global Data Mesh Architecture Market Outlook, By Data Privacy & Compliance Management (2024-2032) ($MN)
  • Table 19 Global Data Mesh Architecture Market Outlook, By IoT Monitoring & Analytics (2024-2032) ($MN)
  • Table 20 Global Data Mesh Architecture Market Outlook, By Real-Time Decisioning (2024-2032) ($MN)
  • Table 21 Global Data Mesh Architecture Market Outlook, By AI/ML Model Training & Feature Stores (2024-2032) ($MN)
  • Table 22 Global Data Mesh Architecture Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 23 Global Data Mesh Architecture Market Outlook, By End User (2024-2032) ($MN)
  • Table 24 Global Data Mesh Architecture Market Outlook, By Banking, Financial Services & Insurance (BFSI) (2024-2032) ($MN)
  • Table 25 Global Data Mesh Architecture Market Outlook, By Retail & E-Commerce (2024-2032) ($MN)
  • Table 26 Global Data Mesh Architecture Market Outlook, By IT & Telecom (2024-2032) ($MN)
  • Table 27 Global Data Mesh Architecture Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
  • Table 28 Global Data Mesh Architecture Market Outlook, By Government & Public Sector (2024-2032) ($MN)
  • Table 29 Global Data Mesh Architecture Market Outlook, By Manufacturing & Industrial (2024-2032) ($MN)
  • Table 30 Global Data Mesh Architecture Market Outlook, By Energy & Utilities (2024-2032) ($MN)
  • Table 31 Global Data Mesh Architecture Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.