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Okay, so my vacations don’t necessary seem like other folks’ vacations. Yes, we relax. Yes, we spend too much money. Yes, we eat too much food. But for some reason, unusual learning opportunities pop up during our vacations, and this year’s vacation was no different. This year’s vacation theme was… logistics. Our logistics foray started by watching the artsy-fartsy movie “The Lunchbox.” I hate artsy-fartsy movies, but my wife insists on watching them on vacation. The movie was excellent. However, I was totally mesmerized by the lunchbox delivery system that was a featured part of the movie. The lunchbox delivery system, called dabbawalas, delivers hot lunches from homes and restaurants to people at work in Mumbai, India. The lunchboxes are picked up mid morning, delivered to husbands at noon using bicycles and railway trains, and returned to the originating source ... (more)

It’s About Economics! Data Is the New Sun | @ThingsExpo #AI #DX #BigData

I’ve always felt that bringing an economics perspective to our Big Data and digital transformation discussions is more important than a traditional accounting or even information technology (IT) perspective. Heck, I believe that a Chief Data Officer’s background should be more along the lines of economics than IT. Economics brings a forward-looking perspective on creating value (wealth). In fact, economics is defined as “the branch of knowledge concerned with the production, consumption, and transfer (capture) of wealth.” It is this forward-looking perspective on the “production, consumption, and transfer (capture) of wealth” that should drive an organization’s digital transformation initiatives. And as an example of how digital transformation is exploiting economics, we need to look no further than what is happening in the automobile industry. Economics of an Elec... (more)

Isaac Asimov: The 4th Law of Robotics | @ThingsExpo #AI #ML #DX #DigitalTransformation

Like me, I’m sure that many of you nerds have read the book “I, Robot.” “I, Robot” is the seminal book written by Isaac Asimov (actually it was a series of books, but I only read the one) that explores the moral and ethical challenges posed by a world dominated by robots. But I read that book like 50 years ago, so the movie “I, Robot” with Will Smith is actually more relevant to me today. The movie does a nice job of discussing the ethical and moral challenges associated with a society where robots play such a dominant and crucial role in everyday life. Both the book and the movie revolve around the “Three Laws of Robotics,” which are: A robot may not injure a human being or, through inaction, allow a human being to come to harm. A robot must obey the orders given to it by human beings except where such orders would conflict with the First Law. A robot must protect ... (more)

“Unlearn” to Unleash Your Data Lake | @ThingsExpo #IoT #M2M #DataLake #Analytics

It takes years – sometimes a lifetime – to perfect certain skills in life: hitting a jump shot off the dribble, nailing that double high C on the trumpet, parallel parking a Ford Expedition. Malcolm Gladwell wrote a book, “Outliers,” discussing the amount of work – 10,000 hours – required to perfect a skill (while the exactness of 10,000 hours has come under debate, it is still a useful point that people need to invest considerable time and effort to master a skill). But once we get comfortable with something that we feel that we have mastered, we become reluctant to change. We are reluctant to unlearn what we’ve taken so long to master. Changing your point of release on a jump shot or your embouchure for playing lead trumpet is dang hard! Why? Because it is harder to unlearn that it is to learn. It is harder to un-wire all those synoptic nerve endings and deep mem... (more)

Difference Between #BigData and Internet of Things | @ThingsExpo #IoT #M2M

A recent argument with folks whose intelligence I hold in high regard (like Tom, Brandon, Wei, Anil, etc.) got me thinking about the following question: What does it mean, as a vendor, to say that you support the Internet of Things (IoT) from an analytics perspective? I think the heart of that question really boils down to this: What are the differences between big data (which is analyzing large amounts of mostly human-generated data to support longer-duration use cases such as predictive maintenance, capacity planning, customer 360 and revenue protection) and IoT (which is aggregating and compressing massive amounts of low latency / low duration / high volume machine-generated data coming from a wide variety of sensors to support real-time use cases such as operational optimization, real-time ad bidding, fraud detection, and security breach detection)? I don’t beli... (more)

Quantum Computing, #AI and Solving the Impossible | @ThingsExpo #DX #SmartCities

Quantum Computing, Artificial Intelligence (AI) and Solving the Impossible In the blog “From Autonomous to Smart:  Importance of Artificial Intelligence,” we discussed the two critical artificial intelligence (AI) challenges in creating “smart” edge devices: Artificial Intelligence Challenge #1: How do the Artificial Intelligence algorithms handle the unexpected, such as flash flooding, terrorist attacks, earthquakes, tornadoes, police car chases, emergency vehicles, blown tires, a child chasing a ball into the street, etc.? Artificial Intelligence Challenge #2: The more complex the problem state, the more data storage (to retain known state history) and CPU processing power (to find the optimal or best solution) is required in the edge devices in order to create “smart”. In the blog “Reinforcement Learning to the Rescue,” we talked about how Moore’s Law isn’t going... (more)

The Four Laws of #DigitalTransformation | @CloudExpo @Schmarzo #AI #DX #IoT #SmartCities

My discussions with organizations looking to “digitally transform” themselves is yielding some interesting observations. I expect that when these discussions move into the execution phase, we will start to create some “Laws of Digital Transformation” that will guide organizations digital transformation journey. So with that in mind, let me start by proposing these “4 Laws of Digital Transformation”. Law #1: It’s About Business Models, Not Just The Business Digital Transformation is about innovating business models, not just optimizing business processes Organizations are looking to leverage these digital assets to create new “economic moats.” Warren Buffett, the investor extraordinaire, popularized the term “economic moat.” “Economic moat” refers to a business’s ability to maintain competitive advantages over its competitors (through process and technology innovatio... (more)

How to Power #DigitalTransformation | @CloudExpo #DX #IoT #SmartCities

“You can’t stop the incessant march of economics” – Bill Schmarzo Okay, so it’s probably not cool to quote oneself, but hey, this is my blog and I get to do what I want.  And for anyone who follows me knows, I love to “riff” on the game-changing power of economics.  The “economics of big data” – where the cost to store, manage and analyze data is 20x to 100x cheaper than traditional analytics – started this big data and data science craze.  But ultimately it is the economics of value, or to be specific, “value in use” where the economics really become a game changer. I recent article titled “The Simple Economics of Machine Intelligence” from the Harvard Business Review highlights very well the role that economics (maybe even more than data science) is going to play in separating the winners from the losers in digital transformation.  To quote the article: Machine int... (more)

Me, Myself and Digital Twins | @ThingsExpo #AI #IoT #BigData #DX #DigitalTransformation

It’s hard to get into the world of the Internet of Things (IoT) without eventually talking about Digital Twins. I was first exposed to the concept of Digital Twins when working with GE. Great concept. But are Digital Twins only relevant to physical machines such as wind turbines, jet engines, and locomotives? What can we learn about the concept of digital twins that we can apply more broadly – to other physical entities (like contracts and agreements) and even humans? What Is a Digital Twin? A Digital Twin is a digital representation of an industrial asset that enables companies to better understand and predict the performance of their machines, find new revenue streams, and change the way their business operates[1]. GE uses the concept of Digital Twins to create a digital replica of their physical product (e.g., wind turbine, jet engine, locomotive) that captures ... (more)

Azure Stack Hybrid Cloud From @DellEMC | @CloudExpo @Azure #AI #ML #DX

Dell EMC Announce Azure Stack Hybrid Cloud Solution Dell EMC have announced their Microsoft Azure Stack hybrid cloud platform solutions. This announcement builds upon earlier statements of support and intention by Dell EMC to be part of the Microsoft Azure Stack community. For those of you who are not familiar, Azure Stack is an on premise extension of Microsoft Azure public cloud. What this means is that essentially you can have the Microsoft Azure experience (or a subset of it) in your own data center or data infrastructure, enabling cloud experiences and abilities at your own pace, your own way with control. Learn more about Microsoft Azure Stack including my experiences with and installing Technique Preview 3 (TP3) here. What Is Azure Stack Microsoft Azure Stack is an on-premise (e.g., in your own data center) private (or hybrid when connected to Azure) cloud pl... (more)

Key to Data Monetization | @CloudExpo #IoT #BigData #Analytics #AI #DX #DigitalTransformation

Many organizations are associating data monetization with selling their data. But selling data is not a trivial task, especially for organizations whose primary business relies on its data. Organizations new to selling data need to be concerned with privacy and Personally Identifiable Information (PII), data quality and accuracy, data transmission reliability, pricing, packaging, marketing, sales, support, etc. Companies such as Nielsen, Experian and Acxiom are experts at selling data because that’s their business; they have built a business around gathering, aggregating, cleansing, aligning, packaging, selling and supporting data. So instead of focusing on trying to sell your data, you should focus on monetizing the customer, product and operational insights that are gleaned from the data; insights that can be used to optimize key business and operational processe... (more)