Last week I chatted about the importance of context and governance to create meaning from definitions.
By coincidence, I came across this related piece from Forbes. In The heartbeat of a data driven culture, Forbes contributor, Dan Woods, takes a practical look at the problem of creating context and giving metadata meaning.
Dan takes a practical look at the work that needs to be done in order to truly benefit from exciting new technologies, such as Hadoop, or Tableau.
The challenge: This work is not exciting. It is the grunt work of identifying and documenting data sources, validating data quality, defining terms and ensuring that they have the correct business context and deliver a common understanding. In short: Data Governance
To use a sporting analogy – for many viewers soccer is all about goals being scored. Defence is boring. Yet, a winning strategy depends on a sound defense. The defense (and midfield) grind the opposition team down and create opportunities for the strikers. This work may not be exciting but it is critical.
How do you deliver data governance in an organisation that may have tens of thousands of data assets – systems, processes, attributes, reports, terms, calculations, and many more? We may need to engage with hundreds of people – users, subject matter experts, managers, IT and auditors in order to ensure that we have correctly captured the business context for each term and that the wisdom is shared across the business.
In the Forbes article, Dan looks at how our partner, data governance vendor, Collibra, makes data governance practical.
Collibra lets you start small – solving tactical problems – yet continually build on each success to build a complete enterprise view. Collibra enables all knowledge users to participate, at the appropriate level, through predefined workflows and views, without overwhelming any one user with unnecessary information. It may not be exciting but it delivers the critical foundation for the data driven enterprise
His conclusion:
“The crucial challenge facing companies today with respect to data is not how they will address the fun parts. The fancy toys will be bought because they are exciting. The companies that make the most of the data they spend so much to collect will be the ones that have enthusiasm for the overall-clad work of data governance, that is, turning raw and messy data into something genuine and meaningful like poetry. When that occurs, changes in data lead to changes in action, not to confusion.”
