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Getting your arms around the IoT platform is still a challenge, mostly because the definition is still evolving. However if you squint your eyes a platform is either used for managing devices, managing backhaul communications or developing applications. And it lives in the cloud or on-prem or in both places at the same time. Using scope and topology is the first step in narrowing down the field while shopping for your platform.
Watch this video (or read the transcript) to see Ken Forster expertly classify IoT platforms in terms of scope and topology and describe what he considers most important when making a buying decision ...




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 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 ...


To quote Mark Andreessen, “Software is eating the world” in industry after industry and it’s no different in ours. Old school SCADA (Supervisory Control and Data Acquisition) hardware is being consumed by Internet of Things software. Often people ask, “What’s the difference between M2M and IoT?” Besides the scope of the networks – M2M lives on a local area network or no network while IoT lives on a wide area network – the other major difference is SCADA consists of proprietary hardware like programmable logic controllers whereas the heart of IoT is software.
Watch this video (or read the transcript) to see Ron DeSerrano compare and contrast his company’s SCADA system with its new Internet of Things platform including the business models ...


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 ...