In a Nutshell Concept Map

There is lots of talk about DAMA-DMBOK2 and DCAM and this can be confusing for people who are new to data governance and data management. There are many definitions describing what data governance is. For example Wikipedia states

'Data governance is a term used on both a macro and a micro level. The former is a political concept and forms part of international relations and Internet governance; the latter is a data management concept and forms part of corporate data governance.'

I came across this article  Data Management and Data Governance in a Nutshell which has a useful concept map of data management and data governance definitions. DAMA and  DCAM are fairly well aligned now.

DAMA-DMBOK2, DCAM and TOGAF methodologies

 

I came across this article giving a comparison between what is included in DAMA-DMBOK2, DCAM and TOGAF methodologies. I mentioned the core framework elements here. The most used data models by the industry are DAMA-DMBOK2 by the DAMA International and DCAM® 2.2 by the EDM Council.

No one model covers all areas and no one company is the same and it is very common that different bits are used as and when required. It is worth reading the discussion in the blog. 

Different data models and frameworks

 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 Classification 

Data Ownership 

Data Security 

Data Sovereignty and Cross-Border Data Sharing 

Data Quality

Data Lifecycle Management 

Data Entitlements and Access Tracking  

Data Lineage  

Data Privacy 

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. 

Capability Maturity Model Integration  (CMMI) Six themes  The CMMI models are described as collections of effective practices and process improvement goals that organisations can use to evaluate and improve their processes.