In today’s manufacturing, data is everywhere — but without the right architecture, most of it goes unused. Smart factories need a clear strategy for where data should live, how it should flow, and how it can generate value.
This series breaks down the three critical pillars of modern manufacturing data:
- Unified Namespace (UNS) – the real-time nervous system
- Historian – the machine memory
- Lakehouse – the enterprise brain
Together, they form the backbone of Digital Transformation in manufacturing. In each article, we’ll explore the role, flow, and representation of data across these systems — and how manufacturers can apply them to unlock AI, compliance, and real-time decision-making.
When I First Heard “Data Platform”
When I first started working with AWS, I kept hearing the word “Data Platform.” At that time, my background was deeply rooted in OT systems. To me, a “data platform” meant:
- A database (PostgreSQL, SQL Server) to store structured records
- An MQTT broker for streaming IoT messages
- A Historian to collect high-frequency time-series data from machines
That was my world.
But in the IT world, the term “Data Platform” usually means something very different. They think about the Lakehouse and the ecosystem around it:
- Storage at scale for any kind of data (structured, semi-structured, unstructured)
- Analytics tools like BI dashboards, reporting, self-service query engines
- Machine Learning & Forecasting capabilities on top of the data
This difference in perspective is why OT and IT teams often fail to communicate effectively. For manufacturing, we need both views to be connected — and that’s why understanding UNS, Historian, and Lakehouse together is so important.
Fundamentals of Manufacturing Data: UNS, Historian, and Lakehouse
Gain a deeper understanding of the three core components of a factory data architecture: what data to collect, where to store it, and why each is crucial. This will pave the way for transforming your manufacturing data into a powerful, business-driving asset.