The 'how' of data governance: properly documenting data assets

Data governance is as broad a topic as data itself, and as such, there are far too many of these ‘how’s’ to cover in one article. This article is the first part in a series to go over many of the desk level procedures that make up data governance. For more information on this topic, read part two, Implementing data quality initiatives and part three, Data security, privacy and compliance.

Having formalized controls around information management will improve data quality, mitigate security risks, better align business and IT, and enable employees to get more out of data analytics. A tremendous amount of effort has been spent justifying the “why” of data governance. As with any large change effort, explaining the “why” is critical for getting buy-in from stakeholders, as well as from the organization at large. The problem is that most books and presentations on the subject stop there. Some resources walk through the process of kicking off a data governance program, including creating a charter, establishing a data governance committee, and appointing data owners and stewards. A full declaration of the data governance mission and vision is only effective if employees know the “how” of data governance.

Don’t stop at the 'why'

The International Data Corporation has forecasted that “the Global Datasphere will grow from 33 zettabytes (ZB) in 2018 to 175 ZB by 2025” [1].  That is a massive increase. To compete in an environment with this amount of data growth, organizations need to ensure they are effectively tracking where their data assets live and how they relate to each other. Desk level procedures provide a clear understanding of data governance in action on a day-to-day basis. These are tools an organization can choose to implement as part of their data governance program, depending on what it is they’re trying to accomplish.

This article will dive into data asset documentation and the practical artifacts to employ to properly manage the ever-expanding data assets while highlighting some of the most impactful tools to implement at your organization: data dictionaries, business glossaries, source to target maps, and data catalogs. Although there is a lot of value to be gained by comprehensive and robust forms of these tools, even basic versions can provide some quick wins on your data governance journey.