In this episode, we look at the unexpected side of industrial data — the kind you only discover after working with real machines, sensors, and production lines. Some surprises are funny, others a bit frustrating: data that isn’t as “real-time” as promised, sensors that disagree with each other, or systems that store history in ways no one can quite explain. We also talk about what makes this data unique — why context matters, why structure helps, and why patience goes a long way when you’re cleaning it. It’s an honest reflection on the quirks and lessons that make working with industrial data both challenging and strangely satisfying. For more in-depth stories and insights, visit iiotblog.com.