The analysis of Internet of Things (IoT) data is quickly becoming a mainstream activity. I’ve written about the Analytics of Things (AoT) before (some examples here, here, and here). For this blog, I’m going to focus on a few unique challenges that you’ll most likely encounter as you move to take IoT data into the AoT realm.
Challenge 1: The Deceptive Simplicity of IoT Data
With many historical data sources, such as transactional data, it was often quite an effort to gather the source data required for analysis. It was necessary to identify what information was available, how it was formatted, and also to reconcile data from different sources that often contained similar information, but had inconsistencies in how it was provided. Ironically, this is one area where IoT sensor data can seem deceptively simple compared to many other sources.
Most sensors spit out data in a simple format. There is a timestamp, a measure identifier (temperature, pressure, etc.), and then a value. For example, at 4:59 pm the temperature is 95 degrees. The good news is that this makes ingesting raw sensor data fairly straight forward in terms of the coding logic required. So, you can fairly quickly go from a raw feed to a dataset …