Hi! I’m Denis Gontcharov

In this episode of the Industrial Data Quality Podcast, I talk with with John Walmsley of Aluminate Technologies, about what AI actually does in heavy industry today, cutting through the hype to explore real applications and challenges. John brings experience from semiconductors to medical devices to AI in heavy industry. The conversation covers three levels of industrial AI: continuous monitoring, multi-sensor analysis, and autonomous optimization. Using aluminum industry examples, we explore why AI projects get stuck in pilot phase and what it takes to scale solutions enterprise-wide. ...

In this new video I share how to overcome Azure CPU quota limits with Databricks Asset Bundles, a common roadblock many Databricks practitioners face when deploying Databricks Asset Bundles on Azure for the first time. Problem If you’re playing around with Databricks projects, Azure’s default CPU quota limits often fall short of what Databricks Asset Bundle Python template jobs and pipelines actually need to run. ...

I’m a big fan of text expanders, espanso being my favorite one. As Xorg is no longer maintained, I recently switched to Wayland and the Gnome desktop environment. Unfortunately, I found out that Wayland support is experimental. This means espanso has to be installed from source. I browsed some forums and saw that installing espanso on Wayland is tricky. After some tinkering, I managed to get espanso running on my system: Void Linux x86_64 6.12.30_1 Gnome 47.4 on Wayland Install rustup Install rust via rustup. ...

I’m excited to share the latest episode of the Industrial Data Podcast featuring Lonnie Bowling, founder of Diemus Consulting. We explore the fascinating evolution of OT data integration, from basic SCADA trend-viewing to today’s cloud-based AI analytics. Lonnie shares how historians like OSIsoft PI transformed from simple tools to enterprise-wide platforms, while discussing the ongoing industry consolidation (AVEVA acquisition of OSIsoft) reshaping the landscape. Despite technological advances, we’re wrestling with old problems: the challenges of proprietary formats, inconsistent naming conventions, and questionable data quality persist as companies migrate to platforms like Databricks for advanced analytics. ...

Data good enough for operations is not necessarily analytics-ready. Exactly one month ago I published the first episode of my Industrial Data Quality Podcast. In my opinion, a topic of critical importance that is all too often overlooked, especially with all the buzz around AI. In the most recent episode, I had the pleasure of inviting guest speaker Thomas Dhollander, co-founder of Timeseer.AI. Together we explored critical challenges in industrial time series data reliability and observability. ...