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市场调查报告书
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1856957

全球资料网格架构市场：预测至 2032 年—按解决方案、部署方式、应用程式、最终用户和区域进行分析

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个工作天内

价格

根据 Stratistics MRC 的数据，预计到 2025 年，全球资料网格架构市场规模将达到 14 亿美元，到 2032 年将达到 49 亿美元，预测期内复合年增长率为 19.5%。

资料网格架构是一种去中心化的资料管理方法，它将资料视为一种产品，并将所有权分配给特定领域的团队。与依赖集中式资料湖或资料仓储不同，将资料责任分散到不同的业务领域可以实现扩充性、更快的存取速度和更高的资料品质。每个领域的团队都使用标准化的互通性原则来管理、共用和治理自己的资料。这种架构促进了自主性、跨职能协作和自助式资料基础设施，使组织能够有效率地处理大型、复杂且不断演进的资料生态系统。

数据民主化和可近性

企业正从集中式资料湖转向面向领域的模型，使每个团队都能拥有并维护资料。业务部门正在利用网格化原则来减少瓶颈并缩短洞察获取时间。与自助式分析和协作管治的整合提高了易用性和合规性。资料网格支援产品、营运和分析团队之间可扩展的协作。这些能力正在推动资料基础设施的去中心化和敏捷性。

文化和组织方面的挑战

许多公司在将所有权从集中式 IT 团队过渡到分散式领域团队的过程中举步维艰。资料素养不足和跨职能协作不良会延缓新方法的采用和管治成熟度的提升。对变革的抵触情绪和不明确的责任制机制会阻碍执行。遗留的层级结构和孤立的工作流程会降低网状架构原则的有效性。这些障碍持续限制企业级转型和营运一致性。

采用云端原生技术

云端平台提供模组化服务，用于资料整合、管治和资料可观测性，并遵循网格原则。无伺服器运算、容器编配和 API 驱动的设计正在推动可扩展的资料产品开发。供应商正在推出支援网域所有权和互通性的网格解决方案。与资料目录、血缘工具和策略引擎的整合正在提升信任度和可发现性。这些创新正在加速企业为分散式资料架构做好准备。

平台和技术复杂性

组织必须整合多种工具来实现跨域资料摄取、转换、管治和存取控制。元资料缺乏标准化、模式演化以及服务等级协定的缺失，使得互通性变得复杂。监控和调试分散式管道需要高度的可观测性和DevOps成熟度。供应商碎片化和架构蔓延增加了营运成本和风险。这些挑战持续阻碍网状环境中的一致性和可扩展性。

新冠疫情的影响：

疫情加速了人们对分散式资料策略的关注，远距办公和数位化营运成为常态。企业面临跨地域、跨团队即时洞察的更高需求。资料网格原则在动盪时期为敏捷决策和本地化所有权提供了支援。各行各业的云端迁移和数位转型工作都取得了显着进展。疫情后的策略开始将网格架构纳入长期弹性和可扩展性计画。这种转变正在加速对领域主导资料基础设施的投资。

预计在预测期内，资料整合和分发板块将成为最大的板块。

预计在预测期内，资料整合和分发领域将占据最大的市场份额，因为它在实现领域级资料产品和互通性发挥基础性作用。该领域涵盖 ETL 管道、资料映射、转换引擎、串流平台等。企业正在投资支援跨领域即时和批量处理的模组化整合工具。供应商提供低程式码和 API 优先的解决方案，简化了上线流程并提高了可扩充性。与管治和可观测性层的整合正在提升信任度和合规性。这些能力正在巩固该领域在网状资料基础设施中的主导地位。

预计在预测期内，人工智慧/机器学习模型训练和特征储存领域将实现最高的复合年增长率。

预计在预测期内，人工智慧/机器学习模型训练和特征储存领域将呈现最高的成长率。特征储存为模型开发和部署提供标准化、可重复使用的资料资产。领域团队正在使用基于网格的管道来管理训练资料、元资料和血缘关係。与 MLOps 平台和模型註册的整合正在提高可追溯性和效能。各行业对分散式实验和即时推理的需求正在不断增长。

占比最大的地区：

在预测期内，北美预计将占据最大的市场份额，这主要得益于其先进的云端基础设施、成熟的企业资料水准和完善的供应商生态系统。美国企业正在金融、医疗保健、零售和科技等行业采用资料网格，以提高敏捷性和管治。对云端原生平台和资料产品工具的投资正在推动资料网格的普及。主要软体供应商和开放原始码社群的存在促进了创新和标准化。法律规范和资料隐私法规正在加强领域层面的责任制。这些因素共同推动了北美在资料网格架构领域的领先地位。

复合年增长率最高的地区：

预计亚太地区在预测期内将实现最高的复合年增长率，这主要得益于数位转型、云端运算应用和分散式资料策略的整合。印度、中国、新加坡和澳洲等国家正在银行、通讯和公共服务等领域推广网状联邦平台。政府支持的云端倡议和资料管治计画正在协助企业做好充分准备。本地企业正在推出符合区域合规性和基础设施需求的网状原生解决方案。行动优先和分散式组织正在推动可扩展即时分析的需求。

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  • 公司简介
    • 对最多三家其他公司进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域分类
    • 根据客户兴趣对主要国家进行市场估算、预测和复合年增长率分析（註：基于可行性检查）
  • 竞争基准化分析
    • 基于产品系列、地域覆盖和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 引言

  • 概述
  • 相关利益者
  • 分析范围
  • 分析方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 分析方法
  • 分析材料
    • 原始研究资料
    • 二手研究资讯来源
    • 先决条件

第三章 市场趋势分析

  • 介绍
  • 司机
  • 抑制因素
  • 市场机会
  • 威胁
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的感染疾病

第四章 波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代产品的威胁
  • 新参与企业的威胁
  • 公司间的竞争

5. 全球资料网格架构市场（按解决方案划分）

  • 资料整合与分发
  • ETL 工具
  • 数据管道
  • 资料映射和转换
  • 协作式资料管治
  • 元资料管理
  • 数据品质与安全
  • 资料处理
  • 数据可观测性和监测
  • 资料沿袭及编目

6. 全球资料网格架构市场以部署方式划分

  • 本地部署
  • 云端基础的

7. 全球资料网格架构市场（按应用划分）

  • 顾客体验与互动
  • 资料隐私合规管理
  • 物联网监控与分析
  • 即时决策
  • AI/ML模型训练和特征存储
  • 其他用途

8. 全球资料网格架构市场（依最终用户划分）

  • 银行、金融服务和保险（BFSI）
  • 零售与电子商务
  • 资讯科技/通讯
  • 医学与生命科​​学
  • 政府/公共部门
  • 製造业/工业
  • 能源与公用事业
  • 其他最终用户

9. 全球资料网格架构市场（按地区划分）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十章：主要趋势

  • 合约、商业伙伴关係和合资企业
  • 企业合併（M&A）
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十一章 公司简介

  • 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.