DM200: Data Governance & Data Asset Management in Practice NEW

Agenda:

• Refresh DM100 Data Management & Data Governance Fundamentals
  • Governance Fundamentals
  • Target Architecture & Guardrails
    
    
• Data Asset Management
  • Asset Definition
  • Classification
  • Criticality

• Role Model & Organization
  • Data Owner/Steward/Domain Lead
  • RACI
  • Delegation Logic
    
    
• Policies & Standards in Practice
  • Structure
  • Approval
  • Exceptions
  • Evidence Management
    
    
• Metadata Operations
  • Glossary/Catalog Processes
  • Data Asset Onboarding
  • Metadata Maintenance & Quality

• Lineage & Impact
  • purpose, granularity level, pragmatic implementation approach

• Data Quality as Organization
  • DQ Rules
  • DQ KPIs
  • Data Issue Management (Triage, Ownership, SLAs)
    
    
• Operating Models
  • centralized, federated, hub and spoke
  • Data Mesh compatible governance
    
    
• Adoption & Change
  • Communication and Enablement Plan
  • Governance Backlog
  • Quick Wins

Objectives:

• Design and justify a practical role and accountability model
• Formulate policies/standards so that they are implementable, auditable, and integrable
• Define catalog/glossary operating processes (onboarding, maintenance, approvals, quality criteria)
• Define a lineage/impact approach (scope, granularity, value, initial MVP)
• Set up a data quality organization: rules, KPI set, issue workflow, ownership/SLAs
• Design a governance operating model including bodies, decision paths, and escalation
• Create a concrete implementation roadmap (pilot, scaling, metrics, change measures)
• Structured preparation for CDMP/governance certifications

Target audience:

• Data Asset Manager
• Data Manager
• Data Steward

Prerequisites:

To be able to follow the course content and learning pace in the training DM200 Data Governance & Data Asset Management in Practice effectively, we recommend prior attendance of the course:

• DM100 Fundamentals Data Management & Data Governance or equivalent foundational knowledge
• Practically helpful: Knowledge of own data domains, stakeholders and typical problem cases

Description:

The DM200 Data Governance & Data Asset Management in Practice course is the practice-oriented deep dive for everyone who must not only “understand” governance, but implement and operate it. Building on the workshop DM100 Fundamentals of Data Management & Data Governance, the foundational framework is turned into an implementable operating model: participants develop a role model with clear accountability logic (including RACI thinking), define governance artifacts (policies, standards, decision records), design catalog and metadata processes (onboarding, maintenance, approvals), and connect these with lineage/impact analyses, data quality organization, and pragmatic issue management.

A central element is translation into day-to-day work: How is stewardship embedded organizationally? Which body makes which decisions? How are conflicts resolved? How do you prioritize data assets (e.g., critical data elements), and how do you establish a “definition of done” for data (e.g., catalog entry, quality rules, access control, accountable owners, lineage evidence)? The workshop provides concrete blueprints and templates that teams can use directly as a starting point (policy templates, stewardship backlog, operating model canvas, DQ KPI set, catalog onboarding checklist).