Building you Data Governance Toolbox
Approaching data governance from your existing organizational structures and processes.
New Post: Building you Data Governance Toolbox
This post describes an approach to data governance that I’ve found a bit more manageable than trying to untangle the tightly interconnected ideas that make up most data governance frameworks.
The quick-read version:
Data Governance is the process of deciding who’s accountable for each of the activities that enable your organization to derive value from data.
Most individuals will only recognize the subset of these activities that impact their daily work.
To identify all of them, consider six categories defined by two axes: Strategic/Tactical/Operational and Defensive/Offensive.
Once you’ve identified all the required activities, you can apply or extend your organization’s existing governance processes before looking to data governance frameworks for whatever remains.
For Further Consideration
What activities in each of the six categories does your organization rely on?
Is someone formally accountable for each of them? If not, which are missing?
What existing organizational structures facilitate these activities? Which ones could be adjusted or extended to fill in the gaps?
Further Reading
The defensive/offensive dimension in this post came from “What’s your data strategy?”
TechTarget has a good overview of common data governance approaches: What is data governance and why does it matter?
Filling out a RACI matrix may be more structure than you necessarily need, but it’s interesting to read about the different versions in Wikipedia’s article on RACI matrices.
Up Next
Upcoming blog posts will include:
A series of case studies exploring design decisions for examples of each of the use case categories.
A series of posts about how thinking of all your organization’s software as a single platform can enable all users to more effectively leverage data.
More posts about the nuts and bolts of designing an integrated data platform.
I like this article critiquing ins and out of "Data Governance" Accountability, decision making and execution make it more lively than organizational “governance”, which is somewhat static in comparison. Moreover, the definition of data seems to expand and morph almost weekly, so Data Governance must include the continual discovery of what "Data" is.
The title "Scaling Biotech" begs the question: How is data in biotech scaled? If a square has its dimensions doubled the area quadruples. If the radius of a sphere doubles it's a factor of eight. When biotech scales up, what is the consequence for the amount of data (not cost, or square footage, etc.) ? I suspect that new forms of data also come into existence.