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Episode 89

The digital twin can be hierarchical – representing environments, systems, products and even parts. When digitizing supply networks with digital twins, the network can be a digital twin of its systems, which can be digital twins of their assets, which can be digital twins of their parts which themselves can be digital twins. Sound complicated? It doesn’t need to be. Start at the level of the hierarchy that returns the most value and proceed from there.
Listen to this podcast (or read the transcript), where I speak with Dr. Lane Warshaw and Aaron Parrott about the digital twin and its profound use in digital supply networks ...




Episode 88

We’ve discussed the digital twin at length but what is the cognitive digital twin? Is it possible to develop cognitive computing models with our data to endow our digital twin with artificial intelligence? The answer is yes.
Listen to this podcast (or read the transcript), where I speak with Dr. Ahmed El Adl about how this is done and the situations where an AI approach to reaching insights may be better than an analytics approach ...




Episode 79

There are two types of manufacturing: discrete manufacturing where the output is physical, countable things, and process manufacturing, where the output is chemistry – think oil & gas. Process manufacturing has been consistently instrumented for over two decades so it is not surprising that they’re a little ahead of their discrete counterparts on their path to IoT.
Listen to this podcast (or read the transcript) with Peter Zornio about IoT analytics in process manufacturing, and his advice is applicable to all industries ...


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 28

Big Data is big! It’s another entire industry that’s subsumed by the Internet of Things. There’s a lot to consider but it all starts with your business information requirements – what you get by transforming the raw sensor data you collect into business value you can use.
Listen to this podcast (or read the transcript) with Big Data expert Mark van Rijmenam to conclude our seven-part miniseries on analytics by covering the entire array of what’s available ...




Episode 25

First it was Big Data and now it’s the Internet of Things; the science of data is becoming increasingly sexy, maybe not Victoria’s Secret sexy but it certainly get the juices flowing for business leaders in the know. Hot or not? Definitely hot.
Listen to this podcast (or read the transcript) with Ajit Jaokar about his passion, data science, and the application of machine learning, deep learning and predictive analytics in IoT ...




Episode 23

Column-based versus row-based, SQL versus NoSQL and streaming versus batch are three of the most important dimensions to consider choosing your IoT database. But let’s get something clear, databases are two levels of indirection beyond what’s truly important: the IoT information you require. Databases support analytics support information. Having said that, the informed business manager on databases will ask the right questions and set the right priorities during ideation of the IoT product.
Listen to this podcast (or read the transcript) with Nik Rouda who breaks down the data environments used in IoT today ...