IoT and Analytics Weekly (9/26/2016)

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Big Data Analytics (BDA) and the Internet of Things (IoT) are some of the most exciting and rapidly-changing phenomena in the world. These two fields are closely connected, since IoT devices generate (and stream) lots of data which typically requires BDA to create actionable insights and, in many cases, control these devices. Let’s take a look at what interesting happened in these two areas last week.

Making Money on Big Data

Microsoft commissioned Keystone Strategy to take a look at investments in big data and found that “companies who dig into their data assets have higher gross and operating margins.”  On average, companies who use data effectively end up with gross margins that are 18% higher and operating margins that are 4% higher. The study sampled 344 large companies from around the world with a median of 6,000 employees and $3.4 billion in revenue.

Not a big surprise here, but it’s good to see some numbers confirming our general expectations.

Are We Overpaying on Amazon.com?

“Unseen and almost wholly unregulated, algorithms play an increasingly important role in broad swaths of American life”−this is a good way to describe our interaction with algorithms nowadays.

This interesting and somewhat provocative article takes a look at the way Amazon recommends the items you want. The authors spent several weeks watching 250 items and noting how the recommendation engine places items on the page and which of them gets “the most prominent placement”. The article claims that “About three-quarters of the time, Amazon placed its own products and those of companies that pay for its services in that position even when there were substantially cheaper offers available from others.”

This reminded me of my own LinkedIn article published in August 2014.  That article discussed how we extensively trust algorithms powering our car navigation systems and how much we depend on them and their decisions.

Already, we have a difficult time figuring out how most algorithms work. The future, controlled by many more complex algorithms, will be even more “interesting”. One day, we might feel like we don’t have any control at all.

Big Data Misconceptions

The authors of this publication spent some time selecting and debunking “five misconceptions” about big data. I could easily agree with four of them but one of them made me a bit uncomfortable. The article addresses the misconception that “Big data is hard to come by” and uses this argumentation to debunk it:

“There are tools that pull information from your accounting software, customer relationship management system (CRM), email, website analytics and much more. Many of these tools will allow you to export your data into Excel for easy manipulation so you can create custom reports and present it in an easy to understand format – It doesn’t have to be difficult or expensive.”

I don’t want to argue with this opinion but I think it simply describes a lot of data rather than “big data”. Big data requires machine learning, neural networks, Hadoops and Sparks, parallel processing, and highly-trained people (with the average annual salary of $119,000, as I wrote last week). This cannot be too easy or too cheap.

IoT Security

This article points to an interesting consequence of IoT device hacking−something that wasn’t obvious to me at all. The danger is not to you or your home. The danger is to the others: “Devices such as web servers, routers, modems, network attached storage (NAS) devices, CCTV systems, and industrial control systems are all being recruited into botnets for the purpose of carrying out DDoS attacks”. Considering how fast the IoT market growth is, this scenario is pretty scary.

IoT + Big Data Analytics = The Future

This Forbes article stated that, “the World Economic Forum estimates that the number of connected devices will grow at a compound annual growth rate (CAGR) of 21.6% over the next four years from 22.9 billion in 2016 to a headline-grabbing 50.1 billion by 2020 – equivalent to almost five connected devices for every person on the planet. But that’s just the beginning.”

I think we all agree with this optimistic outlook on the future even if the exact numbers change from one source to another. In my opinion, however, the exact numbers are not important. Their order of magnitude is. So, from this point of view, the above-mentioned article added nothing to my notion of the future. In fact, a 21.6% CAGR isn’t an outrageous number at all − I recall that Hadoop market is projected to grow at a CAGR of around 60% over the same period of time.

But what I particularly liked about this article is the way they are  (and this is why I combined IoT and Analytics into one blog):

“IoT [data] and other data is the rocket fuel of the digital economy.”

Agreed completely. It is the actionable insights provided by data analytics that will make the IoT industry work for all of us, not just the data acquisition, transmission, or storage. And most of the devices themselves will be powerless without complex algorithms ingesting this data and returning decisions and commands back to them.

IDC has just released the “3rd annual survey of IoT decision-makers,” in which it concludes that data management is fast becoming the overarching theme. Analytics and the IoT Platform are emerging as the main requirements of the 31.4% of organizations surveyed that have already launched IoT solutions, and an additional 43% are looking to deploy in the next 12 months.

Also, IDC believes that “IBM and Microsoft have taken a leading role in almost all IoT segments, especially the ones ascending in importance—analytics, software, systems integration and providing an IoT platform. ” What about Amazon? Or GE?

Does the Government Support  Self-Driving Cars?

Great news: self-driving cars on our roads are now a bit closer to the reality. On September 19th, the US Government released the first guidelines, which outlined safety expectations for the nascent self-driving technology.  The guidelines weren’t as specific as the safety requirements imposed on standard human-driven vehicles today. But this is just the beginning. We all know that Google, Tesla, and others are working on this subject. Meanwhile, Uber has started some life trials of self-driving cars in Pittsburgh.  It feels like, in just a few years from now, we will have some free time as our car drives us to work, which we can usefully spend on something else. Most likely, to work even more.

Nothing but numbers

  • The recent study found that ” 81 percent of business executives believe that successful adoption of industrial IoT is critical to their company’s future success. Only 25% of them, however, have a clear industrial IoT strategy.”

  • Cisco predicts the global IoT market will be $14.4 trillion by 2022, with the majority invested in improving customer experiences.

  • 31.4% of organizations claim they have already launched IoT solutions.

  • Per IDC, of 4,500 industry decision-makers surveyed by them, 55% say IoT is strategic to their business as a means to compete more effectively. 21% regard it as “transformative”—they know it holds promise and are looking for the right investment.

  • Top IoT challenges include security (26%), privacy (21%), upfront cost (22%), on-going cost (19%), IT infrastructure (16%) and IoT skills (14%).

  • Where is the IoT data being processed?

  • 54% collect data at the edge of corporate networks and transmit it to the enterprise;

  • 29% collect and process data at the point of creation (on-site analytics);

  • 14% collect and process some data at the point of creation and transmit the rest to the enterprise.

This entry was posted in Analytics, data analytics, big data, big data analytics, data on the internet, data analytics meaning, IoT, Internet of things, smart connected devices, IoT analytics and tagged , , , , . Bookmark the permalink.

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