Category: Internet of Things

Big Data Indescribably Large

Lost for words

I have been the first to be overly critical of those that define big data solely by size and (absence of) structure. That being said, it is inescapable that data volumes have reached an inflection point. In an article for the Wall Street Journal, Andrew McAfee makes a pretty startling observation. Data has gone from being measured in terabytes to petabytes and exabytes. He explains that in 2012 Cisco announced that its equipment was recording a zettabyte of data. Not startling so far and, in any case, outside of the circle of data geeks, few will have heard of a zettabyte.  The more jarring fact is that the next metric for measuring data is the final one. After the zettabyte is a yottabyte (10 to the power of 24  as you asked ) and then that’s it. We have literally run out of words to describe how big, big data is.

Big v Different

Commentators such as Jeff Jonas and Kenneth Culkier make the point that big is not just big. Big can be different.  David Weinberger, one of the authors of the CluetrainManifesto, makes a similar point in his book Too Big to Know. He proposes that knowledge has been shaped, perhaps even limited by its medium. Only the most important, meticulously researched facts were  committed to paper until the invention of the printing press. Even then, the printed medium carried figurative and literal weight.

In describing Big Data in Decision Sourcing, we  contrast transactional data with ambient data. Transactional data was limited by traditional data processing originally in the form of the punch card and more latterly the relational database. Ambient data, however, exists all around us. It’s size meant that it went unobserved or at least uncaptured. This is what has changed. Affordable and available technology means that signals generated through the internet of things and human social interaction can be captured in digital form providing new (and different) sources of insight. The relational database limited us to recording invoice lines and account details whilst new forms of data management allow us to capture every human gesture, comment and click. Meanwhile  the machines are logging everything they do.

Whats’s next?

Metric prefixes were last updated in 1991 at the 19th General Conference on Weights and Measures and beyond yotta, we got nothin’. Big Data means disruptive, transformational change in a way that we don’t completely understand today. In fact we don’t even have a name for what comes next. Yet.

Smart Watch naysayers and the inevitable rise of Wearable Tech

A diversion into the world of wearable tech for my first post after a Summer recess.

The naysayers are already lining up to herald the failure of smart watches including a couple of post from ZDNet with The problems with the smart watch even Apple can’t solve and Wearable computing: Why there’s no room for watches like Galaxy Gear. There is also a much more direct post from Medium with Why Smart watches will fail.

The sum of these and other similar criticisms are that the screens are too small and that there is no practical way of data input given the size of the device relative to the average, never mind the fatter, finger.

What these reviewers, critics and bloggers are overlooking is that the smart watch is not intended to be a small version of the increasingly inaccurately named smart phone. To date, we have computed on computing terms. At a desk, perhaps on our laps using a keyboard and screen. Wearable technology is about computing on human terms. Wearable marks a profound change to our relationship with technology.

Smart phones like the Pebble along with devices like Google Glass,  the Jawbone Up, Nike Fuelband and the San francisco based fitness tracking startup Fitbit fresh from raising another $43m  all owe a debt to the work of Mark Weiser a researcher at the Xerox Parc Alto Research Centre. More than thirty years ago, Weiser predicted that computing would go way beyond personal and would be ‘in the woodwork’ it would be everywhere; it would be ubiquitous.

Wearable computing is just the start of ubiquitous and situational computing that monitors and responds to our needs, our situation, in context. Wearable doesn’t need a screen or a keyboard, it need only do one thing well and be connected to the internet through equally ubiquitous connectivity.  In the old world a PC user selected the time, manner and duration of their interaction with a machine. In a world of ubiquitous and pervasive computing the thermostat at home is changed, journeys are redirected, sleep patterns detected, alternative arrangements for transit delays organised and medication regimes checked without a keyboard or screen, touch or otherwise.

In the interest of full disclosure the author is a functioning geek with a growing collection of wearables. For example, my Kickstarter edition pebble watch will track my running pace through Runkeepe and alert me to incoming calls, text messages and emails on a low-power e-ink screen. Contained within its (more geek than chic) case is a magnetometer, ambient light sensors and an accelerometer. It will also tell the time.