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I’ve been writing recently about the dimensions of Big Data in the IoT: urgency, importance, frequency, consequences, remedy, cost. You can find my stories on IoT Journal or at my personal website.

The big item missing from this list is, of course, size. How big are individual messages or files? A couple of kilobytes? Many megabytes? And are there still a lot of people who think of Big Data as massive, petabyte-size repositories of epidemiological, meteorological, or particle acceleration data?

I didn’t originally include it, because I saw it as twinned with frequency. In the IoT, most message & file sizes are going to be small. Big Data in the IoT has more to do with sensors and less to do with massive scientific apps.

Frequency might mean a real-time sampling rate of 10 times per second, 100 times per second, or more. Or it may be tethered to a passive device that reports in a timeframe we can call “every once in awhile.” So the frequency dimension might vary by several million times from one application to another. Even if expressed logarithmically, that’s a lot of variance.

Nevertheless, I think I’ll combine the two, and change one of the six categories to size/frequency.

Pay to Play
I go through all this because, in the end, someone has to pay for the dataflow and all tha supports it. Most analyses seem to focus on the amount of data being consumed and stores, ie the size/frequency dimension.

But urgency and importance are mission-critical in setting up proper IoT monitoring, analysis, and the speed of that analysis. Furthermore, the consequences of something gone bad can vary from “there’s a lightbulb out on the bridge” to “a section of the bridge just collapsed.”

The dimensions of consequence and remedy are therefore potentially much more important to cost than the dataflow.

Designing and deploying an IoT project, whether something fun like installing a smart public bench or something grave like monitoring traffic flow, is thus far more than an IT project.

As we get involved in analyzing the cloud computing infrastructures that will no doubt underpin and serve most of the IoT, it’s time to focus not only on cost-per-whateverbyte—the size/frequency dimension–but also the other dimensions, which tell us what this IoT thing is supposed to do and what happens when things go wrong.

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It feels as if we can’t even go a week anymore without hearing about a new breach or outage. For years, IT departments were always on stand-by should the unimaginable happen and were judged by how quickly they could curb a bad situation. These days, however, it’s not good enough to fix a problem – even if it’s taken care of within a few minutes. Questions start to arise the minute something bad happens, and to really show strength IT departments have to stop the problem before it happens. Magic? No, it’s just being proactive and it’s imperative more than ever that IT closely monitor the health of their infrastructure to keep the business running.

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“The Internet of Things is the next wave of cloud. As these distributed devices become more prolific they can really start to gain a lot more insight and gather more date from the environment,” explained Chris Gray, Director of Embedded Intelligence Systems at Red Hat, in this SYS-CON.tv interview at the Internet of @ThingsExpo, held June 10-12, 2014, at the Javits Center in New York City.
Internet of @ThingsExpo 2014 Silicon Valley, November 4-6, at the Santa Clara Convention Center in Santa Clara, CA, will feature technical sessions from a rock star conference faculty and the leading IoT industry players in the world.

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NNIT uses HP Cloud Service Automation to improve their deployment of IT applications and data, and to provide higher overall service delivery speed and efficiency.
As a provider of both application development management and infrastructure outsourcing, Denmark-based NNIT needed a better way to track, manage and govern the more than 10,000 services across its global data centers.
Beginning in 2010, the journey to better overall services automation paved the way to far stronger cloud services delivery, too. NNIT uses HP Cloud Service Automation (CSA) to improve their deployment of IT applications and data, and to provide higher overall service delivery speed and efficiency.
To learn more about how services standardization leads to improved cloud automation, BriefingsDirect spoke with Jesper Bagh, IT Architect and cloud expert at NNIT, based in Copenhagen. The discussion, at the HP Discover conference in Barcelona, is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.

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Over the last few years the healthcare ecosystem has revolved around innovations in Electronic Health Record (HER) based systems. This evolution has helped us achieve much desired interoperability. Now the focus is shifting to other equally important aspects – scalability and performance. While applying cloud computing environments to the EHR systems, a special consideration needs to be given to the cloud enablement of Veterans Health Information Systems and Technology Architecture (VistA), i.e., the largest single medical system in the United States.

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It’s become clear that the impacts and implications of cloud commerce are much broader and much more of a benefit to the business as a whole as an innovation engine, even across whole industries.
Over the past five years, the impetus for cloud adoption has been primarily about advancing the IT infrastructure-as-a-service (IaaS) fabric or utility model, and increasingly seeking both applications and discrete IT workload support services from Internet-based providers.
But as adoption of these models has unfolded, it’s become clear that the impacts and implications of cloud commerce are much broader and much more of a benefit to the business as a whole as an innovation engine, even across whole industries.
Recent research shows us that business leaders are now eager to move beyond cost and efficiency gains from cloud to reap far greater rewards, to in essence rewrite the rules of commerce.

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The agreement between IBM and Apple to collaborate on mobility and Big Data will certainly rank as one of the big stories of the year in global enterprise IT. In addition to Apple’s devices and IBM’s custom apps, an absolute key to this deal will be telecommunications.
As we all know, what we call Information Technology (IT) in the US is generally referred to as Information and Communications Technology (ICT) throughout the world, demonstrating telco’s importance to the whole enchilada.
Thus, we were fortunate to speak about the IBM/Apple deal recently with Robert Fox, IBM’s Global Industry Leader for Telecommunications Media & Entertainment.
Here’s what we asked, and what he had to say:
Big Data Journal: Apple CEO Tim Cook mentioned «Big Data Analytics» as a key reason to do business with IBM. From your point of view and IBM’s point of view, what strengths to you bring in this area?

Bob Fox: The Apple and IBM partnership is all about combining IBM’s Big Data and Analytics capabilities with Apple’s legendary consumer experience, hardware and software integration and developer platform.
IBM is the proven leader in Big Data and Analytics with more than 40,000 data and analytics client engagements that spans research and development, solutions, software and hardware. The analytics portfolio is made up of more than 15,000 analytics consultants, 4,000 analytics patents, 6,000 industry solution business partners, and 400 IBM mathematicians who are helping clients use Big Data to transform their business.
Over the last ten years, we have been applying these resources to solve mission critical challenges in sales, marketing, operations, fraud, security, and many other functions across the 17 industries on which we focus.

BDJ: Big Data is, obviously, nothing without strong telco to deliver it throughout enterprises and the world. What is IBM’s vision and execution in the telco aspect of the IBM/Apple agreement?

Bob: While communications service providers (CSPs) are rethinking how new networks will be provisioned and managed in order to meet new traffic demands, they are also faced with the need to radically change the way networks are maintained and customers are serviced.
Some 76% of CSP enterprise customers report that they are not satisfied and are demanding faster and more efficient service. In the consumer segment, CSPs rank among the lowest in traditional measures of customer satisfaction, including NPS and advocacy.

BDJ: So how do you improve this?
Robert: Customer satisfaction can be drastically improved in this industry by giving mobile workers in the field access to real-time ticket management, service history or parts inventories in the palm of their hand.
To help restore telco’s customer service reputation, IBM and Apple will develop more than 100 enterprise solutions, starting with apps for telecommunications field service personnel. These applications will allow CSPs to deliver the right services the first time, all at lower costs.

BDJ: Do have an estimate/projection on the amounts of Big Data than an individual enterprise may be collecting and analyzing? Do you have a global estimate on the growth of Big Data over the next few years?

Bob: Thanks to a proliferation of devices and the infusion of technology into all things and processes, the world is generating more than 2.5 billion gigabytes of data every day, and 80 percent of it is unstructured—everything from images, video and audio to social media and a blizzard of impulses from embedded sensors and distributed devices.
It is not atypical for a single CSP to collect data on tens of billions of events, yielding a petabyte or more of data to store and analyze–every day!
With the market for data and analytics estimated to reach $187 billion by 2015, organizations spanning many industries have become increasingly dependent on data—for recording their business transactions, managing their production lines and defining their growth strategies.
The emergence of Big Data is the phenomenon of our time; it is a new natural resource. It is fueled by the proliferation of devices, the rise of social media and the infusion of technology into all things and processes.

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Today’s datacenters face a gauntlet of challenges including protection of physical and virtual environments, fast recovery of data, reducing backup times and storage requirements, server consolidation, and disaster recovery. How are savvy CIOs conquering these types of challenges? Find out how in this white paper by expert David Davis.

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Within the world of Big Data & the IoT, there’s a significant sub-culture of what @CloudExpo & @DevOpsSummit faculty member Lori MacVittie has recently termed “passive” data. Her example was a little barcode reader she carries around that scans food items for gluten. The device hooks into databases “out there,” as she puts it—probably in the cloud somewhere out there.

Let’s take a look at how this device interacts among the dimensions of Big Data and the IoT that I outlined the other day. These dimensions are Urgency, Importance, Frequency, Consequences, Remedy & Cost.

The final analysis also includes size, ie, dataflow of course. I leave size out of the group of dimensions as I see it as a function of them, particularly frequency. Also, it seems to be a habit to focus on the size of the problem—eg, how many cloud instances do we need to buy—rather than the data’s real significance to the organization.

In Lori’s use case, the dataflow from even millions of such devices will not be particularly large, but it’s the other dimnsions that matter more. The importance of this information is critical to buying a particular food item. To the merchant and supplier, it’s critical to the sale. The urgency of this information is thus very high as well.

The consequence is a lost sale, the remedy an awareness that people will have this device, and presumably many others checking for all conceivable aspects of what’s in the food they’re buying.

I could see the activity or passivity of data as fitting in nicely with the frequency dimension.

The bottom-line here seems to be that the actual cost of deploying and serving this application and others like it won’t be particularly large per se, but the potential of opportunity cost lost will be very high.

In my particular case, not that anyone wants to know other than for use-case reasons, sugars are the big killer. I’d like my smart watch, smart belt, or smart ring to let me know, when I prompt it, whenever something has less than X milligrams of sugar. I’m sure we can think of at least 100 other things, and perhaps will see the Swiss Army knife approach to such devices in the future.

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