The Data Governance is the set of rules defining the data: property, storage, protection, and in case of exploitation how it should be shared or rewarded.
This set of rules lets companies create value by enabling a transparent and trustworthy data sharing. Without it, any cross-entities collaboration becomes impossible due to IT ad legal problematic.
Four core elements compose the governance on data:
- Use Case
First, a governance is Use Case specific. It only grants access to a dataset for a specific purpose clearly identified.
For example: a solution may have access to the operating data of a plant to run a predictive maintenance service, but not to estimate the load level of the plant. Yet the dataset to crunch is the same.
Second, governance also defines the Data Storage, or otherwise named Data Stewarship.
This aspect of the governance states the infrastructure whereby data is supposed to be stored, accessible, saved, archived, protected, exploited.
Next, the Data Management is clearly the main piece of the governance. As data only creates value when shared, Data Management describes how data must circulate to serve the business and operations.
From an user side, management rules allocate each one a tailor made access. These access rights vary depending on the reading/writing permissions and the silots of the data lake.
From an organizational side, the management system allows users to work on the same centralized data source, thus making the structure Data Centric.
Last but not least, the governance has to anticipate and evaluate the Data Quality. Because the analysis of a dataset depends on its precision, completeness and veracity, the Data Quality plays a major role in the success of a decision.
Not only the governance needs to assess the quality of data supporting a decision to ensure the validity. But also the governance requires to implement a process of data cleaning.
Of course, the governance raises many problematic such as Intellectual Property or Value redistribution, but frameworks exist.
Frameworks of governance are numerous and cover several well known use cases. Alternatively, some methods can design governance according to project needs.
Once the governance done, the Interoperability of systems can be implemented. This interoperability remains today the main challenge of all sectors to create value together more efficiently.
Our collaborative platform www.industrie4.0smartplatform.com
helps companies to build a governance
according to their project’s data toward interoperability.
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