Data Knowledge Democratisation

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Data Governance initiatives often struggle to gain real business traction and bring about noticeable change. A lack of executive sponsorship is often cited as the main reason why the data governance effort was not able to drive through a change in corporate culture. However there are other factors at play.

By: Patrick Dewald, [email protected] , Diaku Ltd, www.diaku.com 

Doing better work around data on an enterprise scale requires the engagement of staff across multiple disciplines and functions. Most large organisations are faced with a highly complex data landscape; reducing that complexity requires the knowledge and collaboration of local and central staff across a number of areas. If we could achieve a leaner and meaner data landscape by just involving data and IT people we would be there already.

enterprise-data-management-post-1To date the knowledge about data often remains locked away in specialist modelling and architecture tools as well as an eclectic mix of Visio and Excel artifacts. This inhibits any broad collaboration as not only specialist knowledge is required to interact with those tools, the views captured within do not easily connect up to form an integrated and meaningful whole.

The knowledge about the firm’s data desperately needs to be shared to empower anyone and everyone in the firm to be a well informed data citizen and enable collaboration across disciplines and functional silos. It needs to be democratised both in terms of providing an accessible view irrespective of the user’s skillset and in providing an interconnected view across the different perspectives each of the disciplines or functions have. Knowledge Democratisation is a terrific driver for Data Governance adoption across the organisation.

enterprise-data-management-post-2Data definitions are a good starting point, but in order for the IT practitioners to be able to contribute, those definitions should be linked up to the technical metadata. Similarly if one wants to understand data usage the process viewpoint needs to be linked in as well. The compliance and regulatory viewpoints are equally important as are the more conventional data quality and data lineage viewpoints. How about providing visibility of what items are about to be affected by which change project?

With each new facet being connected into the knowledge base a new community of experts and stakeholders is brought into the governance model while growing the understanding of data and broadening the context of its use.

It also makes the conversation around data more objective and meaningful to the community, as they see things together, from the perspective of the business outcomes that data supports.

Data governance is the people component within enterprise data management. As such it should first and foremost focus on collaboration by connecting people and knowledge. When it does this it can transcend any single group’s capacity to imagine, understand and unleash a new way of working around data where being aligned is not the exception, but the norm.

About the Author

Patrick Dewald is a knowledge management expert and a Director of Diaku, makers of Axon – the world’s first graph database driven collaborative data governance software.

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