About this course
All there is to know about Data Governance Maturity Models.
What is a maturity model.
A look into the foremost maturity model, the Capability Maturity Model (CMM).
The concept of maturity models is applied across different industries and subjects. Here are some examples.
The set of characteristics shared across maturity models
The benefits and reasons to leverage data governance maturity models.
Answering the questions "are these models compatible?" and "are these comparable?"
An overview of the Oracle Data Governance Maturity Model and its three phase approach in governance activity.
An overview of the 2016 Gartner Enterprise Information Management Maturity Model
An overview of Dataflux Data Governance Maturity Model and its four stages, each with its characteristics, risks and benefits.
An overview of Kalido Data Governance Maturity Model, its four stages and characteristics.
An overview of the TDWI Data Governance Maturity Model
An overview of the IBM Data Governance Maturity Model
An overview of the Stanford Data Governance Maturity Model
An overview of the CMMI Data Management Maturity Model
Introduction to the 6 step workflow to follow in order to best use a Data Governance Maturity Model.
The selection considerations and things to watch out for when selecting a Data Governance Maturity Model.
The three parts of the assessment step, a quick demo, and recommendations.
The analysis step and things to look for and draw out, such as the SWOT analysis, resources capability, and benchmarking activity.
The deliverables and actions of the improvement step in order to achieve a higher level in the Data Governance Maturity Model.
The time expectations and things to be mindful of in order to have valuable re-assessment results.
An overview of a key, but forgotten aspect of data governance in general and a critical step in using the maturity model.
Gaining and awareness of the downside and shortcomings of the Data Governance Maturity Models in order to find ways to navigate around them.
Lessons learned from organizations and data governance professionals that successfully or not so successfully used Data Governance Maturity Models.
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