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Episode 47


Listen to this analysis episode (or read the transcript) with Bruce Sinclair where he analyses the latest IoT news from a business perspective. In this episode Bruce tees off from the Apple CareKit announcement to discuss why ecosystems are so important and how they differ from IoT platforms ...


In the data science of IoT there’s no one size fits all data model. Each situation needs to be analysed separately by your data scientist. Then the output too, needs to be custom tailored to your customer - internal or external. This output, often in the form of a dashboard, is critical in aiding the identification of value with your data. Therefore, iterate on its design as often as you do on the design of the IoT product.
Watch this video (or read the transcript) to see Christian Mastrodonato discuss standing up an Internet of Things Pilot from a Data Scientist’s perspective ...




Episode 46

Schneider has seen the IoT light and they are following it at scale. Step 1, make all products connected. Step 2, develop a platform, in this case, for the energy management and automation vertical. Step 3, create more customer value by moving from products to products and services to ultimately driving customer results.
Listen to this podcast (or read the transcript) where I speak with Prith Banerjee about the IoT playbook to be followed by all leading edge enterprises, big and small ...


If implementing IoT within your organization it makes sense to target improving operational efficiency; it’s easier for the bean counters to sign off on than some esoteric new IoT business opportunity. This, as I’ve discussed before, is the thin edge of the IoT wedge for getting a pilot started. Next - what OPEX should you go after? Find a metric that everyone in the company or business unit or department, understands and lives by and then apply IoT there first. If people have a stake in it they will be more willing to change, readjust processes and help make the project successful. Rather than making it a top-down edict, power the IoT project from the bottom-up.
Watch this video (or read the transcript) to see Nauman Sheikh share his strategic and hands-on experience on the steps and best way to introduce IoT analytics in any organization ...




Episode 45


Listen to this analysis episode (or read the transcript) with Bruce Sinclair where he analyses the latest IoT news from a business perspective. In this episode Bruce talks about Ericsson quietly slashing IoT device forecasts, the proposed DIGIT bill and the New MQTT ISO Standard ...




Episode 44

If your company is collecting data, and every IoT company collects data, it needs a formal “Information Security Program”. We’ve talked risk assessment in the past, that is the process of assigning liability to each potential security breach, but that’s only part of the program.
Listen to this podcast (or read the transcript) I speak with John Ansbach about the rest of the “Information Security Program”, impending regulation and privacy concerns ...


Visualizing IoT big data is as much an art as it is a science. The palette is underlying algorithms and the exterior is color and texture mapping. Images aren’t static – they are interacted with in 3D or animated as a movie. The result is a science-based art form designed to convey information or present a story where the human mind can discover hidden value invisible to the algorithm. As a subset of descriptive analytics, it is another tool for the data scientist, subject matter expert or executive to extract value form the numbers coming from IoT sensors and data services.
Watch this video (or read the transcript) to see Barend Botha paint a picture of how to use data visualization to uncover hidden value in big Internet of Things data sets ...




Episode 43


Listen to this analysis episode (or read the transcript) with Bruce Sinclair about why he considers LPWA to be an existential threat to the mobile industry in IoT. Mobile World Congress 2016 is the first major public battle ground… the first of many ...




Episode 42

The business counterpart to IoT security is risk, loosely defined as probability times liability. The current narrative around liability is centered on privacy but it turns out that laws, regulations and cyber security in general are some of the other elements in the IoT liability matrix.
Listen to this podcast (or read the transcript) I speak with Mark Radcliffe about the current IoT legal framework and the potential liabilities to address early on in the IoT product development cycle ...


Creating the local intelligence for an Internet of Things product requires special programming skills and knowhow to work within constrained environments. Environments possibly constrained by computing, networking, memory, power or all of the above. The effort to reduce manufacturing costs produces these constraints but sometimes the biggest costs are the ones you didn’t plan for.
Watch this video (or read the transcript) to see Peter Hoddie share his deep experience in programming constrained devices and the (business) issues to consider when planning development ...