Ron Kimchi on Eon at Google Cloud Next

Why does u‑OS Data Hub matter? The u‑OS Data Hub cuts through data silos and makes automation integration fast and code‑free. With centralized data access, multiple API options, and an open, secure architecture, it helps teams connect machines, apps, and cloud services with far less effort. A smarter, faster path to modern industrial automation. https://lnkd.in/dX2J7TCE

One of the standout sessions at Data Center World: Julianne Carroll from Microsoft and Shen Jackson from Google walking through how hyperscalers actually plan, scale, and adapt when workloads span continents and evolve by the hour. The framing around GPU-intensive workloads reshaping rack density, cooling requirements, and facility design was particularly grounded. This is the operational reality that drives the decisions about where capacity gets built and how fast it needs to come online. The gap between how hyperscalers think about capacity planning and how the broader market still approaches it is one of the most important dynamics in this industry right now. Sessions like this help close it. Great conversation. Exactly why Data Center World is worth being at this week!

4.15.26 - In today's data center news: HYPERSCALE 🖊️ Microsoft takes over Stargate Norway data center from OpenAI 📢 Microsoft buys an additional 3,200 acres in Cheyenne, WY ⚖️ xAI is being sued by the NAACP over Memphis data center air pollution COLOCATION & OTHER DEVELOPMENTS 📢 Pure Data Centres Group buys land in Seinajoki, Finland, for data center campus 📢 Two-building data center campus proposed in northeast Pennsylvania 📢 Two-building campus eyed just outside of Leesburg, Virginia 🤝 Solaria in talks to join a state-backed consortium seeking to develop a €4 billion ($4.7 billion) data center hub in Spain LEGISLATIVE ✅ Maine passes first-in-nation freeze on data centers over 20MW OTHER 💲 Aon expands data center lifecycle insurance program capacity to $3.5B in support of digital infrastructure clients Click the link below to learn more - read, enjoy, share, and subscribe!

Shortcut vs Delta Table in Microsoft Fabric Lakehouse – When to use what? One of the most common questions while working with Fabric Lakehouse is: Should I use a Shortcut or create a Delta Table? Here’s a simple way to think about it: Use Shortcut When you want quick access without copying data Best for real-time, zero-copy access Ideal for shared datasets across teams Use Delta Table When you need transformations, performance, and governance Supports ACID transactions, time travel, optimization Best for production-grade pipelines Rule of Thumb: Shortcut = Reuse Delta Table = Control + Performance Recommended Approach (Medallion Architecture): Bronze → Shortcut (raw ingestion) Silver → Delta (cleaned data) Gold → Delta (business-ready insights) Bottom line: Start fast with Shortcuts, scale smart with Delta Tables. #MicrosoftFabric #DataEngineering #Databricks #Lakehouse #BigData #Azure #DataArchitecture

Lakehouse or Warehouse as gold layer data store? The results from 10 MVPs were quite interesting, but surely everyone knows there's just one right answer 👀

Here is a look inside the Equinix Silicon Valley data center: https://lnkd.in/gJkcUqEJ These days the first thing that comes to mind is of course AI. But a data center is used for a wide mix of workloads including web hosting, cloud connectivity, storage, enterprise IT, and increasingly AI. These facilities are designed to let all of the customers to connect directly to each other with very low latency. They existed long before the AI boom and are still mostly used for general internet + enterprise infrastructure. AI is just one workload among many, but it’s growing fast. It's interesting to observe how we are no longer talking about cooling the servers by putting them in the ocean, like Microsoft did with project Natick. Instead of ocean water, these data centers rely on engineered HVAC systems + water loops. Modern cooling systems handle heat effectively, while keeping everything accessible, upgradeable, and scalable - things you could not easily do by dropping them in the ocean. #datacenter #webhosting #CloudComputing #EnterpriseIT #EnterpriseAI

🧵 Microsoft Fabric - Day 11/100 Did you know many organizations struggle to ingest and process high-volume streaming data without complex, multi-service architectures? • Microsoft Fabric's Eventstream simplifies real-time data ingestion by offering a unified, no-code/low-code experience for capturing events from various sources. • It supports direct integration with Azure Event Hubs and Kafka, enabling seamless data flow into Fabric for immediate processing. • Eventstream allows you to define multiple destinations, including Lakehouses and KQL Databases, ensuring data is routed appropriately for analytical needs. • You can apply basic transformations and filtering directly within Eventstream, reducing the need for downstream processing for simple use cases. 💡 Pro Tip: Leverage Eventstream's "Add destination" feature to simultaneously send data to both a Lakehouse for historical analysis and a KQL Database for near real-time dashboards, without duplicating ingestion efforts. 📖 Full guide: https://lnkd.in/dNvi3zeK --- #MicrosoftFabric #DataEngineering #Azure #Analytics #100DaysChallenge #RealTimeAnalytics #Eventstream 👉 What's the most challenging real-time data source you've had to integrate, and how do you think Eventstream could simplify it?

FabCon & SQLCon 2026 just wrapped, and Microsoft didn't hold back. From unified data security to AI-powered planning built directly into Fabric, the announcements signal a real shift in how data platforms are designed. Our data experts, Margerita Sołtysiak and Adrian Kukiełka, break down what shipped, what it actually means for your architecture, and which tools it might be time to retire. 👉 Read the full breakdown here: https://lnkd.in/dDTuW-R9 #MicrosoftFabric #FabCon2026 #SQLCon #DataEngineering #DataPlatform

🧵 Microsoft Fabric - Day 21/100 🛠️ Want to optimize your advanced data factory patterns workflows? Advanced Data Factory Patterns in Microsoft Fabric provides: • Scalable data processing capabilities • Delta Lake ACID transactions • Automated data quality checks • Real-time streaming support • Optimized performance patterns Master advanced data factory patterns to build production-ready data pipelines. 💡 Pro Tip: Implement advanced data factory patterns patterns to scale your data workflows efficiently. 📖 Read the complete technical guide with step-by-step implementation examples, best practices, and expert insights: https://lnkd.in/dNgtVNeJ --- #MicrosoftFabric #DataEngineering #Azure #Analytics #100DaysChallenge #DataEngineering 👉 What's your experience with advanced data factory patterns? Share your thoughts and questions below!

There’s a lot of talk about Bronze, Silver, and Gold in Microsoft Fabric. What’s usually missing is how it actually works in production. If you missed our session last week, you can now you can see it! 🎥 This on-demand session walks through how Solina Foundation implemented a Fabric-based data platform with WhereScape and IT-Logix — from source integration to model-driven pipelines and scalable architecture. You’ll see how: • multiple sources were unified into a consistent model • pipelines were generated from metadata instead of hand-coded • patterns like historization and delete detection were applied in practice It’s a real-world look at moving from fragmented data to something structured, repeatable, and built to scale. If you’re evaluating Fabric or trying to move past theory, this is a solid reference point. ▶️ Watch on demand: https://ow.ly/IAyO50YIf95 #MicrosoftFabric #DataEngineering #DataArchitecture #DataModeling #WhereScape