[MarTech Platform] Consolidate data, rules engines, and customer profiles

Two ideas from my research project with Databricks that we released yesterday fundamentally rewired how I think about martech. 🧠 Mind-bending idea #1: Everything. Is. Data. Not just customer data. Not just campaign data. Company operations data, content, code, governance controls — all of it living on a common data plane, underpinning everything in the business. This isn't just a universal data layer for classic martech records. It's a universal data layer for everything. The wildest part? Code as data. When you realize that AI models, prompts, agent skills, and governance rules can all be managed and manipulated as data — queried, updated, versioned, orchestrated — something clicks. Functionality becomes as fluid as any other kind of data. I think of this as the Grand Unified Theory of Martech: The martech stack doesn't just use data. It is data. ⚡ Mind-bending idea #2: The new math of integration. I've spent my career wrestling with martech integrations — as a developer, as a platform leader, as an analyst. Integration has been the bane of martech since the moment there were more than two tools on the landscape. We've made great progress, but there was still a long way to go. When everything lives on a shared native data substrate, the complexity curve changes fundamentally. Hub-and-spoke integration models are O(n) — every new connection adds proportional overhead, technical debt, and failure points. On a common data plane, you're approaching O(log n). Each new integration adds only a minuscule fraction of incremental complexity because everything is already adjacent and accessible. It's not just faster and easier. Going back to idea #1: when everything is already data on that plane, the integrations themselves become richer and more powerful — no longer bottlenecked through narrow APIs with partial coverage and perpetual version drift. This one felt personal. In the best possible way. There's a lot more in my latest newsletter issue and the report itself — including the composable canvas architecture framework, the semantic layer, context graphs, and more. The link to the web version of the newsletter issue is below. You can grab a free copy of the full Databricks report from there too. Massive thanks to Tasso Argyros, Katy Yuan, and the entire Databricks team for being such incredible partners on this project. 🙏 #marketing #martech #AI