Data Mesh is a decentralized approach to data management. It treats data as a product and shifts responsibility from central teams to business domains. This approach uses four core principles: domain ownership, data as a product, self-serve data platform, and federated governance.

Why is Data Mesh important for IFS Cloud?

Data Mesh is important for IFS Cloud because it aligns with the platform’s modular, domain-driven design. It enables business domains to own and manage their data products, ensuring better data quality, faster access, and more agile decision-making.

What are the four core principles of Data Mesh?

The four core principles are domain ownership, data as a product, self-serve data platform, and federated governance. These principles work together to create a scalable, decentralized data ecosystem.

How do you implement Data Mesh in IFS Cloud?

Implementation involves several phases: defining project scope, initiating the project, confirming prototypes, establishing the solution, implementing the solution, and going live. Each phase includes specific tasks such as validating product definitions, deploying self-service tools, and training teams.

What is federated governance in Data Mesh?

Federated governance means applying governance standards across domains while allowing each domain to manage its own data products. It ensures consistency, security, and compliance without centralizing control.

What tools does IFS Cloud provide for Data Mesh?

IFS Cloud provides tools like IFS Connect for integration, REST API with OData for data access, Data Migration Manager for processing, and built-in security and access controls for compliance.

How do you measure the success of a Data Mesh implementation?

Success is measured by metrics such as time to release new data products, adoption rate, quality scores, user satisfaction, compliance rate, security incidents, process efficiency, and domain autonomy.

What are the risks of implementing Data Mesh, and how can they be mitigated?

Risks include integration complexity, performance issues, security gaps, resistance to change, lack of resources, and weak governance adoption. Mitigation strategies include phased rollouts, good architecture, regular audits, training, proper staffing, and executive sponsorship.

Data Mesh Implementation Planning for IFS Cloud Projects

IFS-ERP CRIMS customization of IFS Cloud

What Data Mesh brings to IFS Cloud? Why it shifts control from central teams to business domains?

IFS Cloud Data Mesh Implementation Plan

A Data Mesh is a decentralized approach to managing data that treats it as a product, making domains responsible for their own data. Combined with IFS Cloud’s project methodology, it creates a framework for strong governance and scalable data management.

This approach replaces centralized control with a federated model. Business domains own and manage their data products while adhering to shared governance standards.

Core Principles for IFS Cloud

Domain Ownership

Map modules to business domains
Set boundaries (Supply Chain, Finance, etc.)
Align enterprise structure

Data as a Product

Design with clear SLAs
Discoverable in Data Catalog
Expose via REST APIs & OData

Self-serve Platform

Use built-in integration tools
IFS Connect for protocols
Data Migration Manager

Federated Governance

Governance via project org
Enterprise Book of Rules
Use IFS Cloud security

Implementation Phases

Phase 0: Define

Phase 1: Initiate

Phase 2: Prototype

Phase 3: Establish

Implement full specs
Deploy self-service tools
Configure catalog & APIs

Phase 4: Implement

Train teams on ownership
Test end-to-end workflows
Validate compliance

Phase 5: Go Live

Activate production products
Monitor performance
Set up lifecycle management

Data Governance Framework

Includes Executive sponsor (CDO), Domain data product owners, Technical platform team, and Data stewards.

Automated validation dashboards, exception handling, quality reporting, federated access controls, tagging, and audits.

IFS Connect, REST API (OData), Built-in security tools, Data catalog, and pipeline automation.

Roadmap

Months 1 – 3

Build governance structure, define domains, set up initial framework, and train the core team.

Months 4 – 8

Deploy 1 – 2 pilot products, enable self-service, and validate governance architecture.

Months 9 – 12

Expand to all domains, add analytics, optimize governance, and build improvement loops.

Success Measures

Data Products

Time to release
Adoption rate
Quality scores

Governance

Compliance rate
Security incidents
Domain autonomy

Business Value

Faster decisions
Lower costs
Better access

Risks & Mitigation

Technical: Integration complexity & performance gaps.
Fix: Phased rollout & monitoring.

Organizational: Resistance to change & weak governance.
Fix: Executive sponsorship & training.

Frequently Asked Questions

Data Mesh is a decentralized approach to data management. It treats data as a product and shifts responsibility from central teams to business domains using four principles: Domain ownership, data as a product, self-serve data platform, and federated governance.

It aligns with the platform’s modular, domain-driven design, enabling business domains to own their data products for better quality and agility.

Metrics include time to release new data products, adoption rates, quality scores, user satisfaction, compliance rates, and process efficiency.