If you're still designing your stack with a separate transactional layer, an analytical warehouse, and a real-time tier stitched together by pipelines — H1 2026 just made that architecture harder to justify. Every major platform shipped something this half that chips away at the need for that middle layer. This week's issue breaks down exactly what ➡️ Snowflake, ➡️ Databricks, ➡️ BigQuery, ➡️ Redshift, and ➡️ MS Fabric each did — and what the pattern means for the rest of the year. Video version of this weeks www.datapro.news below 👇

Most enterprise AI projects don't fail at the model. They fail at the foundation. The pattern is familiar: a promising proof of concept, then the initiative stalls. The cause usually isn't the AI. It's a data foundation without stable entity identity, complete history, or auditable lineage, the conditions that turn confident-sounding output into output you can actually trust. We're joining Scalefree International for a live panel on how to fix the architecture underneath. Data Vault: The Foundation for Trusted AI 📅 Tuesday, 30 June 2026 ⏰ 09:00 CEST On the panel: 🎙️ Julien Redmond, CEO of Ignition and IRiS 🎙️ Alexander Lai, IRiS Product Lead 🎙️ Ole Bause, Senior Consultant, Scalefree We'll get into why the data foundation, not the model, is the real bottleneck for enterprise-grade AI, and how the right architecture delivers the semantic meaning, history, and lineage that reliable AI depends on. Register via the link here: https://us02web.zoom.us/webinar/register/WN_u1dUBz0xSUKSGbF_cftHoA#/registration

Here is what you can get done in under 15 minutes if the silver layer of your Lakehouse is automated.

Most of the work in building a Data Vault isn't the code. It's the design. Reading metadata, profiling samples, identifying business keys, capturing definitions nobody updates later. We filmed a walkthrough of the IRiS Assistant doing exactly that work. One source table, start to finish: profiled, modelled, definitions captured, production-ready metadata pushed to the repository, in a single conversation. If you've ever sat through the design phase of a Data Vault build, this is worth eleven minutes. The IRiS Assistant is live in beta: https://ignition-data.com/iris-assistant

We said watch this space. Here it is. The IRiS Assistant is live. It connects to your source data, profiles it, and walks you through the integration model design one source at a time. Each table lands where it belongs, extending the model where new territory is needed and integrating cleanly where structures already exist. Which relationships need history and what terms need definitions. All captured as you go, all landed in your repository as a versioned, auditable record. The design phase used to be the expensive part. The part that needed weeks of senior architect time before a line of code got written. Not anymore. Learn more about the IRiS Assistant here: https://ignition-data.com/iris-assistant