Establishing a Data Management Framework & Function

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This training program is designed for CDOs, data governance leaders, and program managers who are responsible for building or strengthening a data management function. It provides a practical roadmap for developing an enterprise-wide governance framework, including the operating model, governing bodies, and a clear data roles architecture. The program also guides participants in designing capability-specific governance for business architecture, data modeling, data and application architecture, metadata management, and data quality—covering the required policies, processes, roles, key artifacts, and tool specifications. In addition, the program explains how to assess maturity for both the overall data management capability and its individual components, and how to establish a performance management system that supports meaningful oversight, continuous improvement, and demonstrable business value.

Select a fit-for-purpose data management framework aligned with organizational goals.
Define a feasible, value-driven scope for data initiatives that support business priorities.
Formulate strategic directions and objectives that guide the entire data management function.
Design enterprise-wide governance, including a DM operating model, roles' hierarchy, and governing bodies.
Develop business architecture governance that links business structure with data and AI practices and defines corresponding policies, processes, roles, and IT tool requirements.
Establish governance for data modeling that defines modeling standards, processes, roles, key artifacts, and requirements for supporting tools.
Design governance for data and application architecture that aligns systems and integrations with business needs and specifies required policies, processes, roles, and architectural artifacts.
Define governance for metadata and data lineage that covers metadata categories, required artifacts, processes, roles, and tool specifications.
Develop data quality governance that includes quality rules, processes, controls, roles, required artifacts, and tool requirements.
Create a performance measurement system for capabilities and the overall data management function.
Assess maturity levels for the data management capability and its components to guide improvement.