There are 3 different models that can help when thinking about data governance and data management.
The revised DAMA Wheel has data governance at the top
The core components to think about for data governance and data management are: Policy; Stewardship & Ownership; Culture Change; Strategy; Principles and Ethics; Data Valuation; Data Maturity Assessment; Data Classification.
When getting started I look at the fundamentals as a starting place.
1. Data Governance
2. Meta Data Management
3. Data Quality
4. Reference/Master Data
DAMA-DMBOK | Data Management Body of Knowledge
DCAM (Data Management Capability Assessment Model) was first published in 2014 following the Socratic method of question and debate. . CDMC (Cloud Data Management Capabilities Framework) is a playbook of best practice for managing data in the cloud. Version 1.1.1 was released in September 2021 , created by a cross industry workgroup of 100+ firms. It is a framework for best data management practices to accelerate trusted cloud adoption. It can be downloaded here. The holistic list of capabilities highlighted in the CDMC from the EDM Council is:
Data Cataloguing and Discovery
Data Sovereignty and Cross-Border Data Sharing
Data Lifecycle Management
Data Entitlements and Access Tracking
Trusted Source Management and Data Contracts
Ethical Use and Purpose
Master Data Management
Data Management Capabilities Model Framework | Playbook of best practice
The Data Management Maturity (DMM) program from the CMMI Institute has best practices for providing support for the implementation of process for these five categories: strategy; governance; data quality; operations; and platform and architecture.
Best practice for ensuring broad participation in the practice and senior oversight of the effectiveness of data management.