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Asia Pacific Data Mesh Market Size, Share & Trends Analysis Report By Offering (Solution, By Solution Type, By Approach, By Application, By Business Function, By Vertical, By Country and Growth Forecast, 2023 - 2030

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    Report

  • 192 Pages
  • February 2024
  • Region: Asia Pacific
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5945597
Description Jump to:
The Asia Pacific Data Mesh Market would witness market growth of 17.4% CAGR during the forecast period (2023-2030).

Understanding customer behavior is critical in the competitive landscape of E-commerce. From personalized recommendations to targeted marketing campaigns, customer behavior analytics fuel various strategies to enhance the customer experience. Data mesh principles enable teams to take ownership of customer behavior analytics for their respective segments. The versatility of data mesh is exemplified by its applicability across these diverse sectors, highlighting its potential to revolutionize data management practices in organizations of varying sizes and industries.

Moreover, the evolution of data lakes is taking a smart turn within the data mesh context. Smart data lakes are designed to accommodate the decentralized nature of data mesh, allowing for storing and retrieving diverse data products. Additionally, a federated data mesh is gaining traction, where multiple data meshes within an organization can interoperate, enabling seamless collaboration and data exchange. A trend towards decentralized identity and access management (DIAM) is emerging to address security challenges associated with decentralized data ownership. This involves developing robust mechanisms to manage and authenticate identities across different data domains, ensuring secure and controlled access to decentralized data products.

As per the Indian Brand Equity Foundation, by 2025, the Indian fintech sector is anticipated to be worth $150 billion. Globally, India possesses the third most extensive fintech ecosystem. India is among the global fintech sectors with the most rapid expansion. There are more than 2000 DPIIT-recognized Financial Technology (FinTech) businesses in India, which is rapidly increasing. In addition, as per the data released in 2023 by the State Council of China, social logistics rose 3.4 percent yearly to 347.6 trillion yuan (about 50.4 trillion U.S. dollars) last year. The logistics for industrial products increased by 3.6% annually during the specified period. During the specified period, the logistics industry generated a total of 12.7 trillion yuan in annual revenue, an increase of 4.7%. Therefore, expanding BFSI and logistics sectors in the Asia Pacific will help in the growth of the regional data mesh market.

The China market dominated the Asia Pacific Data Mesh Market by Country in 2022, and would continue to be a dominant market till 2030; thereby, achieving a market value of $262.9 million by 2030. The Japan market is registering a CAGR of 16.6% during (2023 - 2030). Additionally, The India market would showcase a CAGR of 18.1% during (2023 - 2030).

Based on Offering, the market is segmented into Solution (Cloud, On-premise), Services. Based on Solution Type, the market is segmented into Data Integration & Delivery, Data Transformation & Orchestration, Data Operations, and Others. Based on Approach, the market is segmented into Coarse-grained, Fine-grained, Hybrid federated mesh, and Value chain-aligned mesh. Based on Application, the market is segmented into Customer Experience Management, Data Privacy Management, Chatbots/ Virtual Assistants, Campaign Management & IoT Monitoring, and Others. Based on Business Function, the market is segmented into Sales & Marketing, Finance & Accounting, Operations & Supply Chain, HR, ITSM, Research & Development, and Others. Based on Vertical, the market is segmented into BFSI, Government & Defense, Energy & Utilities, Healthcare & Lifesciences, Transportation & Logistics, Manufacturing, Retail & eCommerce, IT & Telecom, and Others. Based on countries, the market is segmented into China, Japan, India, South Korea, Singapore, Malaysia, and Rest of Asia Pacific.

List of Key Companies Profiled

  • IBM Corporation
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • SAP SE
  • Oracle Corporation
  • Informatica Inc.
  • Teradata Corporation
  • Microsoft Corporation
  • Monte Carlo Data, Inc.
  • Ataccama group
  • Nexla, Inc.

Market Report Segmentation

By Offering
  • Solution
  • Solution Deployment Type
  • Cloud
  • On-premise
  • Solution Type
  • Data Integration & Delivery
  • Data Transformation & Orchestration
  • Data Operations
  • Others
  • Services
By Approach
  • Coarse-grained
  • Fine-grained
  • Hybrid federated mesh
  • Value chain-aligned mesh
By Application
  • Customer Experience Management
  • Data Privacy Management
  • Chatbots/ Virtual Assistants
  • Campaign Management & IoT Monitoring
  • Others
By Business Function
  • Sales & Marketing
  • Finance & Accounting
  • Operations & Supply Chain
  • HR
  • ITSM
  • Research & Development
  • Others
By Vertical
  • BFSI
  • Government & Defense
  • Energy & Utilities
  • Healthcare & Lifesciences
  • Transportation & Logistics
  • Manufacturing
  • Retail & eCommerce
  • IT & Telecom
  • Others
By Country
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific

Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Asia Pacific Data Mesh Market, by Offering
1.4.2 Asia Pacific Data Mesh Market, by Approach
1.4.3 Asia Pacific Data Mesh Market, by Application
1.4.4 Asia Pacific Data Mesh Market, by Business Function
1.4.5 Asia Pacific Data Mesh Market, by Vertical
1.4.6 Asia Pacific Data Mesh Market, by Country
1.5 Methodology for the research
Chapter 2. Market at a Glance
2.1 Key Highlights
Chapter 3. Market Overview
3.1 Introduction
3.1.1 Overview
3.1.1.1 Market Composition and Scenario
3.2 Key Factors Impacting the Market
3.2.1 Market Drivers
3.2.2 Market Opportunities
3.2.3 Market Restraints
3.2.4 Market Challenges
Chapter 4. Competition Analysis - Global
4.1 Cardinal Matrix
4.2 Recent Industry Wide Strategic Developments
4.2.1 Partnerships, Collaborations and Agreements
4.2.2 Product Launches and Product Expansions
4.2.3 Acquisition and Mergers
4.3 Market Share Analysis, 2022
4.4 Top Winning Strategies
4.4.1 Key Leading Strategies: Percentage Distribution (2019-2023)
4.4.2 Key Strategic Move: (Partnerships, Collaborations & Agreements: 2019, Jun - 2023, Dec) Leading Players
4.5 Porter Five Forces Analysis
Chapter 5. Asia Pacific Data Mesh Market by Offering
5.1 Asia Pacific Solution Market by Country
5.2 Asia Pacific Data Mesh Market by Solution Deployment Type
5.2.1 Asia Pacific Cloud Market by Country
5.2.2 Asia Pacific On-premise Market by Country
5.3 Asia Pacific Data Mesh Market by Solution Type
5.3.1 Asia Pacific Data Integration & Delivery Market by Country
5.3.2 Asia Pacific Data Transformation & Orchestration Market by Country
5.3.3 Asia Pacific Data Operations Market by Country
5.3.4 Asia Pacific Others Market by Country
5.4 Asia Pacific Services Market by Country
Chapter 6. Asia Pacific Data Mesh Market by Approach
6.1 Asia Pacific Coarse-grained Market by Country
6.2 Asia Pacific Fine-grained Market by Country
6.3 Asia Pacific Hybrid federated mesh Market by Country
6.4 Asia Pacific Value chain-aligned mesh Market by Country
Chapter 7. Asia Pacific Data Mesh Market by Application
7.1 Asia Pacific Customer Experience Management Market by Country
7.2 Asia Pacific Data Privacy Management Market by Country
7.3 Asia Pacific Chatbots/ Virtual Assistants Market by Country
7.4 Asia Pacific Campaign Management & IoT Monitoring Market by Country
7.5 Asia Pacific Others Market by Country
Chapter 8. Asia Pacific Data Mesh Market by Business Function
8.1 Asia Pacific Sales & Marketing Market by Country
8.2 Asia Pacific Finance & Accounting Market by Country
8.3 Asia Pacific Operations & Supply Chain Market by Country
8.4 Asia Pacific HR Market by Country
8.5 Asia Pacific ITSM Market by Country
8.6 Asia Pacific Research & Development Market by Country
8.7 Asia Pacific Others Market by Country
Chapter 9. Asia Pacific Data Mesh Market by Vertical
9.1 Asia Pacific BFSI Market by Country
9.2 Asia Pacific Government & Defense Market by Country
9.3 Asia Pacific Energy & Utilities Market by Country
9.4 Asia Pacific Healthcare & Lifesciences Market by Country
9.5 Asia Pacific Transportation & Logistics Market by Country
9.6 Asia Pacific Manufacturing Market by Country
9.7 Asia Pacific Retail & eCommerce Market by Country
9.8 Asia Pacific IT & Telecom Market by Country
9.9 Asia Pacific Others Market by Country
Chapter 10. Asia Pacific Data Mesh Market by Country
10.1 China Data Mesh Market
10.1.1 China Data Mesh Market by Offering
10.1.1.1 China Data Mesh Market by Solution Deployment Type
10.1.1.2 China Data Mesh Market by Solution Type
10.1.2 China Data Mesh Market by Approach
10.1.3 China Data Mesh Market by Application
10.1.4 China Data Mesh Market by Business Function
10.1.5 China Data Mesh Market by Vertical
10.2 Japan Data Mesh Market
10.2.1 Japan Data Mesh Market by Offering
10.2.1.1 Japan Data Mesh Market by Solution Deployment Type
10.2.1.2 Japan Data Mesh Market by Solution Type
10.2.2 Japan Data Mesh Market by Approach
10.2.3 Japan Data Mesh Market by Application
10.2.4 Japan Data Mesh Market by Business Function
10.2.5 Japan Data Mesh Market by Vertical
10.3 India Data Mesh Market
10.3.1 India Data Mesh Market by Offering
10.3.1.1 India Data Mesh Market by Solution Deployment Type
10.3.1.2 India Data Mesh Market by Solution Type
10.3.2 India Data Mesh Market by Approach
10.3.3 India Data Mesh Market by Application
10.3.4 India Data Mesh Market by Business Function
10.3.5 India Data Mesh Market by Vertical
10.4 South Korea Data Mesh Market
10.4.1 South Korea Data Mesh Market by Offering
10.4.1.1 South Korea Data Mesh Market by Solution Deployment Type
10.4.1.2 South Korea Data Mesh Market by Solution Type
10.4.2 South Korea Data Mesh Market by Approach
10.4.3 South Korea Data Mesh Market by Application
10.4.4 South Korea Data Mesh Market by Business Function
10.4.5 South Korea Data Mesh Market by Vertical
10.5 Singapore Data Mesh Market
10.5.1 Singapore Data Mesh Market by Offering
10.5.1.1 Singapore Data Mesh Market by Solution Deployment Type
10.5.1.2 Singapore Data Mesh Market by Solution Type
10.5.2 Singapore Data Mesh Market by Approach
10.5.3 Singapore Data Mesh Market by Application
10.5.4 Singapore Data Mesh Market by Business Function
10.5.5 Singapore Data Mesh Market by Vertical
10.6 Malaysia Data Mesh Market
10.6.1 Malaysia Data Mesh Market by Offering
10.6.1.1 Malaysia Data Mesh Market by Solution Deployment Type
10.6.1.2 Malaysia Data Mesh Market by Solution Type
10.6.2 Malaysia Data Mesh Market by Approach
10.6.3 Malaysia Data Mesh Market by Application
10.6.4 Malaysia Data Mesh Market by Business Function
10.6.5 Malaysia Data Mesh Market by Vertical
10.7 Rest of Asia Pacific Data Mesh Market
10.7.1 Rest of Asia Pacific Data Mesh Market by Offering
10.7.1.1 Rest of Asia Pacific Data Mesh Market by Solution Deployment Type
10.7.1.2 Rest of Asia Pacific Data Mesh Market by Solution Type
10.7.2 Rest of Asia Pacific Data Mesh Market by Approach
10.7.3 Rest of Asia Pacific Data Mesh Market by Application
10.7.4 Rest of Asia Pacific Data Mesh Market by Business Function
10.7.5 Rest of Asia Pacific Data Mesh Market by Vertical
Chapter 11. Company Profiles
11.1 Monte Carlo Data, Inc.
11.1.1 Company Overview
11.1.2 Recent strategies and developments:
11.1.2.1 Partnerships, Collaborations, and Agreements:
11.1.2.2 Product Launches and Product Expansions:
11.2 Ataccama group
11.2.1 Company Overview
11.2.2 Recent strategies and developments:
11.2.2.1 Product Launches and Product Expansions:
11.3 Nexla, Inc.
11.3.1 Company Overview
11.4 IBM Corporation
11.4.1 Company Overview
11.4.2 Financial Analysis
11.4.3 Regional & Segmental Analysis
11.4.4 Research & Development Expenses
11.4.5 Recent strategies and developments:
11.4.5.1 Partnerships, Collaborations, and Agreements:
11.4.5.2 Product Launches and Product Expansions:
11.4.5.3 Acquisition and Mergers:
11.4.6 SWOT Analysis
11.5 Amazon Web Services, Inc. (Amazon.com, Inc.)
11.5.1 Company Overview
11.5.2 Financial Analysis
11.5.3 Segmental Analysis
11.5.4 Recent strategies and developments:
11.5.4.1 Product Launches and Product Expansions:
11.5.5 SWOT Analysis
11.6 SAP SE
11.6.1 Company Overview
11.6.2 Financial Analysis
11.6.3 Segmental and Regional Analysis
11.6.4 Research & Development Expense
11.6.5 SWOT Analysis
11.7 Oracle Corporation
11.7.1 Company Overview
11.7.2 Financial Analysis
11.7.3 Segmental and Regional Analysis
11.7.4 Research & Development Expense
11.7.5 Recent strategies and developments:
11.7.5.1 Partnerships, Collaborations, and Agreements:
11.7.5.2 Product Launches and Product Expansions:
11.7.6 SWOT Analysis
11.8 Informatica Inc.
11.8.1 Company Overview
11.8.2 Financial Analysis
11.8.3 Regional Analysis
11.8.4 Research & Development Expenses
11.8.5 Recent strategies and developments:
11.8.5.1 Partnerships, Collaborations, and Agreements:
11.8.5.2 Acquisition and Mergers:
11.8.6 SWOT Analysis
11.9 Teradata Corporation
11.9.1 Company Overview
11.9.2 Financial Analysis
11.9.3 Segmental & Regional Analysis
11.9.4 Research & Development Expense
11.9.5 Recent strategies and developments:
11.9.5.1 Product Launches and Product Expansions:
11.9.6 SWOT Analysis
11.10. Microsoft Corporation
11.10.1 Company Overview
11.10.2 Financial Analysis
11.10.3 Segmental and Regional Analysis
11.10.4 Research & Development Expenses
11.10.5 Recent strategies and developments:
11.10.5.1 Partnerships, Collaborations, and Agreements:
11.10.6 SWOT Analysis

Companies Mentioned

  • IBM Corporation
  • Amazon Web Services, Inc. (Amazon.com, Inc.)
  • SAP SE
  • Oracle Corporation
  • Informatica Inc.
  • Teradata Corporation
  • Microsoft Corporation
  • Monte Carlo Data, Inc.
  • Ataccama group
  • Nexla, Inc.

Methodology

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About the Market

Data Mesh is a decentralized socio-technical approach to data architecture and organizational design in IT. It emphasizes the importance of creating domain-oriented, self-serve data infrastructure as a product. Within the context of IT Security, Data Mesh prioritizes robust governance, compliance, and security protocols that are embedded into the data platform itself. Unlike traditional centralized data lakes or data warehouses, where security controls can be uniformly applied, Data Mesh involves distributing the responsibility for data stewardship to domain-specific teams. Each team must enforce appropriate access controls, encryption, auditing, and data lineage tracking as part of their domain's data product offerings. The security challenge in a Data Mesh environment is ensuring consistent application of security policies across disparate domains without impeding accessibility and agility. Solutions typically involve a combination of policy-as-code, secure data access patterns, and automated compliance tooling. Continuous monitoring and validation of security practices are also critical in maintaining a strong security posture as the mesh evolves. Several companies provide solutions or contribute to the Data Mesh market with a focus on security. These include: - Zalando (with its Data Mesh implementation) - Thoughtworks (contributing to the concept and methodologies around Data Mesh) - DataStax (offering data management systems that can be adapted to a Data Mesh architecture) - Talend (providing data integration and integrity tools compatible with Data Mesh principles) - Databricks (offering a unified data analytics platform that can support Data Mesh architecture). Show Less Read more

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