Deployment and Monitoring Flow
Deployment and Monitoring#
Key Ideas
- The Deployment Phase focuses on transitioning the solution from QA/UAT into the Production environment. This phase ensures that the system is stable, secure, and aligned with the organization’s go-live requirements and readiness expectations.
- Smoke Testing- Conduct initial quick checks in production environments to confirm basic functionality after deployment.
- Proivide comprehensive training to data stewards, administrators and other stakeholders who interact with the MDM Solution.
- Continously track system performace to ensure uptime and responsiveness.
- Establish recurring data governance council and audit checks to oversee compliance and policy adherence.
- Create clear channel for reporting system issues or enhancement requests.
- Build a robust backup and recovery plan to safeguard the master data and ensure business continuity.
- Define and track KPI's to measure success of the MDM solution.
- Create Operations Manual Templates - O&M Manual templates
Roles#
1. Input#
What you need to launch the MDM solution into production.
| Category | Input |
|---|---|
| Validated Solution | - Fully tested MDM Hub configuration (Base Objects, Match Rules, Workflows) - Cleaned, validated master data |
| Deployment Plan | - Step-by-step deployment checklist - Rollback and contingency plans |
| Approved Sign-Offs | - UAT sign-off - Business and IT approvals for go-live |
| Security and Access Matrix | - Final role-based access model - Admin and user permissions |
| Infrastructure Setup | - Production environment readiness - Connectivity, storage, backup, monitoring |
| Automation Scripts | - CI/CD deployment scripts, configuration migration packages |
| Documentation | - SOPs, release notes, configuration guides |
2. Process#
The execution of the go-live activities.
| Step | Description |
|---|---|
| Production Deployment | - Migrate configurations, workflows, APIs, match/merge rules from QA to Production |
| User Provisioning | - Assign roles and permissions to users, stewards, and admins |
| Initial Data Load | - Ingest master data from source systems into the Production MDM environment |
| Smoke Testing | - Run quick tests to validate core MDM functionality in production |
| Enable Monitoring | - Configure alerts, dashboards (e.g., job status, data quality checks) |
| Communication and Training | - Notify end users of the go-live - Provide training and usage guides |
| Go-Live | - System officially launched for operational use |
| Post-Go-Live Support | - Hypercare Period: Address immediate post-deployment issues, actively monitor system usage and performance, and ensure stability during the initial go-live phase. |
3. Output#
Results and assets after a successful deployment.
| Output | Description |
|---|---|
| Live MDM Solution | - MDM system is fully operational in the Production environment with live data and active integrations |
| User Access Enabled | - Users and stewards accessing the system as per role definitions |
| Monitoring Dashboard | - Integration job tracking, data quality KPI evaluation, and match rule performance assessment to ensure system reliability and accuracy |
| Log Monitoring | - MDM Solution integrated with Splunk |
| Go-Live Report | - Summary of deployment steps, issues encountered, fixes applied |
| Training and Support Materials | - User manuals, SOPs, quick reference guides |
| Backup and Recovery Setup | - Regular backup routines, recovery plan in place |
| Hypercare Logs | - Log of post-go-live support tickets and actions taken |
What happens next?#
After launch the solution solution moves from being delivered to being embraced and sustained by the business.
Adoption & Support Phase Begins!
Business Adoption Ramps Up: End users, data stewards, and analysts start using the MDM system in their daily workflows — looking up golden records, submitting change requests, and validating data with confidence.
Training & Enablement Continues: Targeted sessions, how-to videos, and hands-on demos help users become power users. Ongoing office hours or coaching builds long-term confidence.
Support & Hypercare Kick In: A dedicated O&M team resolves early issues, monitors pipelines, and fine-tunes workflows. Data stewards collaborate closely with the technical team during this "stabilization" window.
Usage and Value are Tracked:
KPIs like data quality , match rates, and turnaround time for requests are monitored to measure success — and justify the ROI to stakeholders.
Feedback Loops Drive Evolution:
Feedback from users flows into backlog grooming — enhancements, new attributes, and improved rules. MDM begins to evolve as the business grows.