This is Part Four of a four-part series about Agile Data Governance. In Part One, we covered lessons learned from software development history and how they should guide us in today’s data challenges. Part Two profiles stakeholder types and explains the process at a high level. Part Three explores how Agile Data Governance removes five key barriers to data-driven culture.
No two Agile Data Governance programs are exactly alike, nor should they be. The histories of Agile and Open Source have taught us that the people who change the status quo can distill their vision down to a set of ideas. On this foundation, they build and adapt practices, technologies, and skills to make it real. In that spirit, we offer these 10 principles.
- Governance should increase transparency, trust, understanding, and speed—not obscurity, doubt, confusion, and delay.
- Start with the business problems and analytics questions you have today.
- Iterate quickly to build better habits and get to value faster.
- One person’s work should help everyone else’s.
- Give all stakeholders ways to add knowledge and improve data assets.
- Keep people, data, docs, and analysis connected and accessible from the beginning.
- Make documentation easy and iterative or it won’t happen.
- Promote good statistical and scientific methods.
- Analytics is valuable while it’s happening, not just when it’s “done.”
- Make the user experience twice as good as the products and practices it competes with to earn adoption.
What do you think? Anything missing? How could they be better?
We hope that this exploration of Agile Data Governance gives you the knowledge, focus, and determination to take your first small steps on a faster path to a data-driven culture. If you have feedback, questions, ideas, or want to learn how data.world makes Agile Data Governance possible, please ping me: firstname.lastname@example.org & @jonloyens.