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Yeah, data analytics can be complicated, but its application doesn’t need to be. Take discrete manufacturing for example. There’s lots of hype around more advanced analytic applications like predictive maintenance but that’s running before you even know how to walk. I know it doesn’t sound as sexy, but let’s start with operational efficiency.
Watch this video (or read this transcript) to see William Sobel discuss data analytics in manufacturing and why to start easy before tackling sexy predictive maintenance ...




Episode 24

In the Internet of Things there are generally three classes of analytics performed: real-time analytics done of the fly alerting you to anomalies; predictive analytics performed as a post process yielding a prediction and confidence level and descriptive analytics that reports on past, present or future data with visualizations that often result in the biggest insights.
Listen to this podcast (or read the transcript) with Shepherd Shi, as well as the steps that are taken before and after ...




Episode 22

How much IoT data should you keep? It’s not clear. The more data you keep, the more data transmission and storage costs you’ll incur. However thinning out your data store means throwing away potential future insights, potential answers to future questions and potential new information products to expand your business – all value generators unique to IoT products.
Listen to this podcast (or read the transcript) with Steve Stover about balancing the costs and the technology approaches to maximize your Internet of Things data value ...