Showing posts with label big data. Show all posts
Showing posts with label big data. Show all posts

Tuesday, May 3, 2016

Is the Internet of Things Really Happening?

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Over the last few years there has been much speculation about the inevitable growth of the Internet of Things (or Internet of Everything). Forecasts have suggested anywhere from 30 to 50 billion devices will be connected by 2020. Cisco has estimated that the global IoT ecosystem will have a value of $14.4 trillion by 2022, and IDC has projected yearly IoT market revenue to increase to $1.7 trillion by 2020. 

Here we are now in 2016, a few years into the future they were talking about back then, and it may be a good time to take a look the current state of the IoT and see how it measures up to all of these lofty expectations. Are people really embracing IoT technology at this rate? Is this money really being invested? 

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Connected Devices
First, let’s take a look at the number of connected devices. If we flash back to 2013, we find that Gartner released a report entitled “Forecast: The Internet of Things, Worldwide, 2013”. In this report, they predicted that the IoT will include 26 billion connected devices by 2020. Two years later, Gartner reported a total of 4.9 billion connected devices at the end of 2015, up from 3.8 billion in 2014. Gartner also revised their 2020 estimate, anticipating 20.7 billion connected devices by 2020, a decrease of 5.3 billion (20.4%) from their 2013 estimate. (It should be noted here that Cisco continues to anticipate as many as 50 billion by 2020).

So, according to Gartner, IoT adoption has not proceeded at the rate they had anticipated at the end of 2013.
One reason for the slower-than-expected growth is the difficulty faced when trying to implement IoT technology. In fact, Gartner anticipates that through 2018, 75% of IoT projects will take up to twice as long as planned. 


Value of the IoT
Now, let’s consider the monetary value of the IoT and how that number has progressed. Cisco initially projected a value of $14.4 trillion by 2022. Within two years Cisco had increased this number to $19 trillion.
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This highlights an interesting fact. Even though fewer connected devices are expected by this date, the total value of these devices and the underlying network is expected to be greater than it was when more devices were expected. Based on this, I think it’s safe to suggest that implementing IoT technology is turning out to be more expensive than originally thought. 

This may be due in part to the fact that some enterprises are rushing headlong into IoT projects without the proper foresight and planning. Often it is a reaction to competitive pressure, based on a perception that a competitor is already moving forward with their IoT strategy, or simply in an effort to be the first and gain a competitive edge.

“I think it’s safe to suggest that implementing IoT technology is turning out to be more expensive than originally thought.”


Another answer may come from Gartner’s 2015 report: “Predicts 2015: The Internet of Things”, in which Gartner predicts that through 2018, there will be “no dominant IoT ecosystem platform”. They cite a lack of IoT standards and anticipate that IT leaders will be forced to compose solutions from multiple providers.

Read our White Paper on Choosing the Right IoT Software Platform


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Even when faced with these realities, however, enterprises are still moving forward with their IoT projects. The extra expense – though unanticipated – is not nearly enough to outweigh the potential benefits. The IoT is most certainly transforming the way businesses operate, and no one wants to be the last one to this dance.


IoT Investment
This is an important category as it will largely determine how quickly the industry moves to develop standards, and how motivated IoT solution providers will be to develop more powerful and more cost-effective solutions.

Recall IDC’s projection of annual market revenue reaching $1.7 trillion by 2020. It would stand to reason that if we are learning that IoT projects are coming in over budget and late, there is probably some distaste in the marketplace, and maybe IDC’s projection was a bit ambitious.
At the same time, though, if people are spending more on IoT initiatives than they had originally planned, perhaps IDC’s projection was a bit conservative. Let’s examine how things are taking shape.
In 2015, IDC reported that worldwide IoT spending reached $655.8 billion in 2014 and calculated a 16.9% CAGR (Compound Annual Growth Rate).
Well, 2015 is now in the books and we can see how IDC’s projections seem to be holding up. Their latest report indicates that spending in 2015 reached $698.6 billion, a CAGR over 2014 of only 6.53%. Had IDC’s anticipated CAGR proven accurate, 2015 revenue should have been closer to $766 billion.
Notwithstanding this fact, however, IDC continues to project a CAGR of 17% and an increase in spending to $1.3 billion by 2019, which would equal approximately $1.5 billion in 2020. It looks like IDC sees the IoT market cooling off a bit, though not much.
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So, while the earlier projection has proven to be overly optimistic, it is clear that investments in IoT initiatives are continuing to increase with no end in sight.

If there is any kind of meaningful takeaway from all of this, I think it’s safe to surmise that IoT projects may be coming in late and over budget, but that doesn’t seem to have had much of an impact on continued investments. It is clear that business owners and executives see the value and have no interest in letting their competitor’s gain an edge. 
So, was the IoT hyped a bit excessively over the last couple of years? Maybe a bit. But, it is also very real and happening right now.

Tuesday, March 8, 2016

3 Keys to Effective Real-Time Data Visualization

manyFacesEverybody appreciates the value of a good picture. Each one says a thousand words, after all, or so the saying goes. If we really dig in to this metaphor, we’d probably admit that some pictures say substantially more than that – while others probably come in well under a dozen (just look at a random Facebook wall for some examples).
Ours has become a very visual culture, and one occupying a place in time defined by an overwhelming abundance of information all around us. Considering these two facts, it is not at all surprising that we see such an increased interest in data visualization – that is to say the process of placing a particular, specific set of data points in a highly visual context that allows it to be quickly consumed and analyzed.
It’s not a new concept; data has been visualized in pictures for centuries. A map is a type of data visualization, for instance, as are the many charts and graphs that have been used since the end of the 18th Century. What is new is the massive quantity of data available to nearly everyone, and the wide array of tools that can be used to create compelling visualizations. Think about the cool infographic you saw the other day. Was it created painstakingly over several days of carefully reviewing ethnographic data compiled by a dogged scientist over the course of his career? Maybe, but probably not. It was more likely created by some marketing department somewhere (not that there’s anything wrong with that) using somebody else’s data and somebody else’s visualization tools.
The purpose of this post, though, is not to discuss the merits of data visualization in general, but rather the specific subset of data visualization that deals with real-time data. This is a completely separate species of data visualization and should be treated as such.
Real-time data visualization refers to visualization of data that is continuously updated as new data is generated by connected devices or people. This is the type of data that is used to make real-time decisions and, when done correctly, can truly transform business processes.
There are a number of important factors to consider when attempting to visualize data in real time, but we will focus on three simple and obvious keys: clarity, consistency, and feedback.

Clarity
Real-Time graphics should emphasize pertinent information and use design principles that promote ease-of-use and accessibility above aesthetics. Things like size, color and brightness can be used to distinguish primary details from secondary and tertiary details. Special graphics can be created to emphasize different information under different conditions (i.e. a special set of graphics to be used when a certain alarm is triggered).

Hierarchical Data
Hierarchical Data Makes its Relevance Obvious

Clear visualizations provide actionable information at a glance, and clearly show the current process state and conditions. Alarms and indicators of abnormal conditions are prominent and impossible to ignore.
Clarity encompasses both content and context.
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Contextual Controls Allow You to Assess Current Conditions at a Glance


Consistency
Consistent visualizations are standardized and consistently formatted. Interaction requires a minimum of keystrokes or pointer manipulations.
Shapes, colors, and layouts should be used consistently through all screens. If the color red is used in one place to designate an abnormally high value on one screen, that same color red should be used to indicate all abnormally high values of the same type on all screens. If navigation buttons are on the left side of one screen, they should be on the left side of all screens. A consistent visualization system is arranged in a logical, hierarchical manner, allowing operators to visualize both a general overview of the system as well as more detailed information on different components as needed. Navigation and interaction of any type should be as easy and intuitive as possible.
Consistency is closely related to clarity.
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Color is a Great Way to Distinguish One Property from Another, As Long As it Is Consistently Applied.


Feedback
An operator should be fully confident that the choices they make are having the desired effect. Screens should be designed in a way that provides information, putting relevant data in the proper context. Also, important actions that carry significant consequences should have confirmation mechanisms to ensure that they are not activated inadvertently.
Controls will function consistently in all situations. If something is not working as it should, that fact should be immediately obvious and undeniable. In a well-designed system, design principles are employed to reduce user fatigue.
There are obviously many other important factors to consider when real developing a real-time visualization system. Anyone who wants to dig deeper is encouraged to read this free whitepaper on the subject: