By nature, industrial facilities consist of physical assets and processes that evolve through time. Therefore, each data point generated by such systems is essentially a snapshot of events at that particular point in time. By extension, this data wants to be stored in a way that reflects the sequential order of events, so that it can be rapidly queried and analysed, among many other reasons. But yet, this isn't a capability that is inherently baked into the more common Relational and NoSQL databases. Hence the rise in popularity of Time-Series Databases for industrial Telemetry Data storage over the past few years. At the forefront of this revolution is InfluxDB, an Open-Source Time-Series Database platform developed by InfluxData. To understand how Time-Series Databases work, and InfluxDB in particular, I had a chat with Brian Gilmore who is the Product Manager for IoT at InfluxData. Check out our full conversation in the video linked below. Outline: ✔️ Characteristics of IIoT Data ✔️ Why Time-Series Databases Matter for IIoT ✔️ Common IIoT Use Cases for Time Series Database ✔️ How to Plan an IIoT Data Architecture ✔️ InfluxDB Time-Series DB Platform ✔️ InfluxDB - Open Source vs Cloud vs Enterprise ✔️ InfluxDB Time-Series DB Migration ✔️ InfluxDB Deployment Options ✔️ Acquiring Industrial Telemetry Data into InfluxDB ✔️ Industrial Telemetry Data Enrichment in InfluxDB ✔️ InfluxDB Integration with Analytics & Visualisation Platforms ✔️ Factory-Floor to InfluxDB Data Pipeline