Microsoft Fabric has only been in preview for a week, and I’ve already written one post that covers data governance – do we really need another one already?
I think we do.
Over the weekend I got this reply via Mastodon.
Dave’s excellent question and comment[1] got me thinking about why OneLake feels so important to him (and to me) even though Fabric is so much more than any one part – even a part as central as OneLake. The more I thought about it, the more the pieces fell into place in my mind, and the more I found myself thinking about one of my favorite quotes[2]:
A complex system that works is invariably found to have evolved from a simple system that works. The inverse proposition also appears to be true: A complex system designed from scratch never works and cannot be made to work.
Please take a minute to reflect on this quote. Ask yourself if Fabric is a complex system that works, what is the simple system that works? We’ll come back to that.
One of the most underappreciated benefits of Power BI as a managed SaaS data platform has been the “managed” part. When you create a report, dataset, dataflow, or other item in Power BI, the Power BI service knows everything about it. Power BI is the authoritative system for all items it contains, which means that Power BI can answer questions related to lineage (where does the data used by this report come from?) and impact analysis (where is the data in this dataset used?) and compliance (who has permissions to access this report?) and more.
If you’ve ever tried to authoritatively answer questions like these for a system of any non-trivial scope, you know how hard it is. Power BI has made this information increasingly available to administrators, through logs and APIs, and the community has built a wide range of free and paid solutions to help admins turn this information into insights and action. Even more excitingly, Power BI keeps getting better and better even as the newer parts of Fabric seem to be getting all of the attention.
What what does all this have to do with Fabric and OneLake and simple systems?
For data governance and enablement, Power BI is the simple system that works. OneLake is the mechanism through which the additional complexity of Fabric builds on the success of Power BI. Before the introduction of Fabric, the scope of Power BI was typically limited to the “final mile” of the data supply chain. There is a universe of upstream complexity that includes transactional systems, ETL/ELT/data preparation systems, data warehouses, lakes, and lakehouses, and any number of related building blocks. Having accessible insights into the Power BI tenant is great, but its value is constrained by the scope of the tenant and its contents.
With Fabric, that scope of value is significantly increased. Fabric includes tools and capabilities for significantly more parts of the data supply chain, and whatever you do in Fabric is part of the same tenant, which means these insights are more readily available. In addition to what you know and love in Power BI, Fabric also includes a growing set of governance-focused capabilities that make it easier than ever to monitor and audit artifacts and activities, and to implement guardrails to help everyone achieve their business goals in ways that align with the organization’s governance strategy.
All Fabric workloads use OneLake as their default data location. OneLake represents the biggest single step forward in moving from simpler to more complex, because it is the big expansion in the SaaS foundation shared by all Fabric workloads new and old. Because of Fabric, and because OneLake is the heart of Fabric, governance teams can now get more of the things they love about Power BI for more parts of the data estate.
Why should your governance team be excited about Microsoft Fabric? They should be excited because Fabric has the potential of making their lives much easier. Just as Fabric can help eliminate the complexity of integration, it can also help reduce the complexity of governance.
[1] Yes, we have Dave to thank and/or blame for this post.
[2] This massive pearl of wisdom is from The Systems Bible by John Gall. I first encountered it in the early 90s in the introduction to an OOP textbook, and have been inspired by it ever since. This quote should be familiar to anyone who has ever heard me talk about systems and/or data culture.