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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 ...




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 ...




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 ...




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 ...




Episode 21

On the surface, building your own IoT cloud seems pretty straightforward, but brush away some of the fluff and you’ll find the non-trivial issues of data velocity, message processing, scalability, redundancy and robustness.
Listen to this podcast (or read the transcript) with Dan Collins, its differences with the IT cloud and the issues to consider when building or buying ...




Episode 20

To go beyond connectivity, the IoT Platform must abstract all components of the Internet of Things product or environment into a form that can be computed and interfaced with the app, model and analytics. I call this the software-defined product, or in the case of home automation, the software-defined home.
Listen to this podcast (or read the transcript) with Jim Hunter and the importance of abstraction – from the metal to the cloud ...




Episode 19

The “IoT Platform” is such an overloaded term that its meaning has been lost. Chipset manufacturers, sensor manufacturers, software vendors, consortia and system integrators all have their own definitions. But if you come at it from enough angles eventually a form takes shape and you realize it means what you want it to mean and what is important is not its definition but the context in which it’s used.
Listen to this podcast (or read the transcript) with Dr. Sean Lorenz and I as we go through the elusive IoT platform and why the business problem is always the place to start ...




Episode 18

It’s a heck of a lot easier than it used to be but most IoT projects still involve custom system integration – the question now is how much. Although the definition of an IoT platform, or AEP, is not always clear, what is clear is that using a platform saves a lot of time and a lot of system integration work. There may be legitimate reasons to develop your own platform in house but by definition, this means you become a software company – big time.
Listen to this podcast (or read the transcript) with Bryan Kester to get his take on what an IoT platform is, the technologies involved and a candid view on the strengths and weaknesses of IoT platforms today ...