| Data Governance requires a careful balance | | | | 1 - Not in data model, no analysis, and/or no |
| between the soft skills of managing people, | | | | metadata |
| committees, upper management and the | | | | 2 - Added to data model with metadata |
| workforce while still being able to 'get in the | | | | 3 - Valid values established, issues identified |
| weeds' and provide strong analytical skills to your | | | | 4 - Issue analysis performed, resolution pending |
| data model, data processes, and metadata. | | | | 5 - Fully governed, full analysis and issue resolution |
| Whilst so many things are going on, don't forget | | | | performed |
| about metrics. You'll need to show what you've | | | | 6 - Data quality in place to find anomalies and |
| done, why your program is valuable, and where | | | | violations (possibly in real-time depending on your |
| you are going. In my blog, I always stress taking | | | | tool) |
| notes and tracking what you do. One very | | | | The reason that this model will help you is |
| tangible way to do this is with a data maturity | | | | because, as you begin to work through your |
| model. | | | | in-scope data, you'll be able to show the progress |
| A data governance scope generally revolves | | | | of the domains your review. As time goes by, |
| around a specific set of data. What you'll do is | | | | you'll see how the maturity of your data is |
| first create a maturity model for the data. It | | | | progressing, and where you still have room for |
| doesn't have to be particularly complex, just | | | | improvement. For more practical information on |
| something that shows the natural progress of a | | | | data governance, please visit my website at |
| field from 'no governance' to 'fully governed'. Here | | | | DataGovernanceBlog. |
| is an example: | | | | |