The weak maturity of data governance projects necessitate the implementation of good practices and feedback loops to constantly monitor and verify the validity of management rules on your data asset.
The following articles explain the characteristics of a data governance labeled as agile in order to:
1. Be as close as possible to your enterprise’s operational reality.
2. Adapt to your enterprise’s context and not the other way around.
3. Accurately reflect your data assets.
4. Unify and involve your collaborators.
5. Respond to changes quickly.
The implementation of data governance must avoid pitfalls, all too often seen in the past via a top-down approach. This type of descending approach wants for objectives and instructions be set by management and then implemented.
This project leadership, like software development in recent years, has proven to be too hierarchical and bureaucratic, uncorrelated to the realities on the ground and therefore, data held by the company.
We recommend a bottom-up approach of the field, in the operational sense, to progressively consolidate a synthesis and to maintain a data governance management that corresponds to the real context of your enterprise.
We define a bottom-up data governance by: