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Episode 27

Descriptive analytics is nothing new, however IoT is applying evolutionary forces to make it adapt to unstructured sensor data and evolve into a mechanism of discovery rather than report generation. Tools that blend traditional business intelligence, analytical modeling and visualization now help data scientists discover the story behind the data which can lead to valuable insights for the enterprise.
Listen to this podcast (or read the transcript) with Dave Rubal about how to apply descriptive analytics to your Internet of Things ...


The future of UX, in certain segments of Consumer and Infrastructure IoT, will be driven by storytelling and emotions. When technology disappear, it’s replaced by magic – resulting in far stronger experiences – an experiences that want to be relived time and time again. Two examples are the Roomba vacuum by iRobot and the Disney theme park magic band. And did you know that many owners of expired Roombas can’t bear to throw them away, even after they’ve been replaced? Talk about product loyalty or is that love?
Watch this video (or read the transcript) to see Matias Rodriguez describe a future of Internet of Things UX for consumer and infrastructure IoT designed to maximize user engagement ...




Episode 26

OK, get ready for it, we’re going to get down and dirty with predictive analytics and when I say dirty, I mean the mathematics of the different forms of predictive models dirty. Geek fest? Yes, but close your eyes and extrapolate how predictive analytics can be applied to your situation. By understanding how it works you will also understand the limits of what it can and cannot do.
Listen to this podcast (or read the transcript) with Anil Gandhi and emerge with a better understanding of predictive analytics and how it really relates to real-time and descriptive analytics ...




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 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 ...


MCU architectures come in so many flavors that there will be a peripheral set to match any sensor you choose. Real decision making at the embedded chipset level is driven by the application. You choose hardware based on its capability to support software. The characteristics of your chipset’s memory, computing power and comms will come from answering a 101 questions, all answered by your IoT application’s requirements.
Watch this video (or read the transcript) to get expert advice from James Stansberry, his best practices and today’s trends in IoT embedded chipsets ...




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 ...


One of the value power sources for an IoT application is external data, that when piped in, can be used to augment its functionality. Of all sources of external data, weather is probably the most ubiquitous and useful. Like many data services, the API is built on a tiered billing system. Come in for free as a developer or hobbyist but once you get over 500 hits per day you start paying.
Watch this video (or read the transcript) to hear Brendan Hayes describe the Weather Company’s API and business model to access it...




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 ...