Azure Data Factory had become the go-to tool for data pipelines across industries for over a decade. Microsoft built Fabric as its newer all-in-one platform, but the challenge was building a migration that didn't break while getting everyone internally aligned. I partnered with my team, brought stakeholders together across two large orgs, and led the end-to-end design to make migration something teams could actually trust.
Azure Data Factory is mature and trusted by enterprises to run production pipelines at scale. But the data landscape was evolving and ADF was falling behind. Microsoft made the call to build Fabric, an entirely new all-in-one SaaS platform, and made it publicly available in 2023.
Both platforms have run in parallel since. But "move everyone to Fabric" was a mandate, not a plan. There was no agreed approach, no internal confidence, and no fundable project to make it happen.
I ran a foundational study with 10 enterprise architects and BI leads running data factories in ADF. Three archetypes emerged, and their differences shaped the entire strategy.
Inherited tangled no-code pipelines. Wants tooling to extract the hidden logic so her team can rebuild cleanly in code.
Juggling many disparate sources. Sees migration as a chance to simplify but needs a clear picture of what moves and what doesn't before making any decisions.
Runs production at scale. Not moving until Fabric reaches parity. Refuses to ship a step backward.
The insight that unlocked alignment: don't make customers choose between staying and leaving. Bring their Azure Data Factory into Fabric as a live, mounted item, let them assess what's ready, then migrate incrementally on their own terms.
This approach gave both orgs a direction they could finally agree on.
Bring the factory into a Fabric workspace as a native item. See and manage pipelines side-by-side. Nothing breaks.
An assessment-first report categorizes every pipeline and activity and surfaces the hidden logic underneath.
Select pipelines, auto-map connections, and migrate in waves, keeping anything unsupported running in place.
Why it aligned the org: mounting gave Azure customers a low-risk path in, and gave Fabric a clear growth strategy. Both sides could finally say yes to the same plan, because nobody had to lose to make it work.
From a single banner inside Azure Data Factory to a guided migration inside Fabric. Here are the moments that mattered most.
Every state of the migration flow was annotated for engineering: focus order, roles, names, and screen reader notifications, so the experience met the accessibility bar enterprise tools require.
The slide-in migration panel, explorer, and assessment views were specified across breakpoints so the experience held up wherever data teams work.
No deadline communicated. Soft messaging guides users to explore Fabric and migrate when ready, with a dismissible banner.
The tone gets more direct, actively pushing users toward migration. The banner persists and the migrate action is always present in the toolbar.
ADF support is ending and the deadline is clear. Users must move to Fabric. The banner is unmissable and the action is required.
Getting the org to commit meant designing the right messaging, not just the experience. The tone had to reassure users, and the timeline had to give both orgs something they could stand behind.
The approach was funded and reached internal dogfood and private preview.
Mount-first, assessment-first is now the migration path Microsoft publishes, with clear states showing what's ready to migrate and what needs a closer look.
Consensus across Azure, Fabric, and exec leadership, with patterns that fed into Microsoft's broader migration guidelines.
The hardest design problem here wasn't a screen. It was getting a large, divided organization to agree on a direction. Research gave me neutral ground to make that happen. Good design strategy is often just making the right path the obvious one.