So much conversation about getting value from your data or analysis focusses on technology or techniques.
Advertising by suppliers offering services in this area also seems to focus too much on these areas. Prospects can be confused as to practical application.
It seems too much technology advertising is simply trying to get an audience enthused about #BigData or #PredictiveAnalytics, without really explaining either or offering practical applications that will make money.
In such a context it was refreshing to read a recent piece from @bensalmon, published on LinkedIn, about how a business can better understand the data it has & how that can help. Excuse the title but I think he makes a great point.
Big Data: Beyond the spin, the data types that matter
Introduction There is so much noise and confusion with big data I thought I would look at the types of data available in an organisation. Let’s start
Public Health Benefits from the Internet of Things
Another often over-hyped ill-defined area at the moment is the “Internet of Things” or IoT for those who like to have the right TLA. Once again much is made by suppliers & media of how exciting this world of new shiny technology is, without much practical application. The has been a growing focus on “FinTech” as an application area for much technological development but for most firms it’s still probably obscure how they can apply this new IT to their customers. Well one concrete application that is already becoming mainstream is the use of wearables to track our fitness, sleep etc. In this excellent Guardian article, @arianaeunjung explains the real progress that has been made already with “personal health-monitoring devices“. Fascinating stuff, I’m increasingly fascinated by my Jawbone tracker (I’m already trying the UpCoffee experiment).
From the instant he wakes up each morning, through his workday and into the night, the essence of Larry Smarr is captured by a series of numbers: a resting heart rate of 40 beats per minute, a blood pressure of 130/70, a stress level of 2%, weight of 87kg, 8,000 steps taken, 15 floors climbed, eight hours of sleep.
Big Data for Social Good: Earthquake prediction
Finally, after the heartbreaking scenes in Nepal in 2015, which I’m sure prompted many of you to give to the DEC appeal, it’s encouraging to read of another application area for “Big Data“. Patrick Marshall writes of the work of One Concern in using small clues from nature together with satellite data to better predict earthquakes in future.
When a major disaster strikes, first responders routinely report that reliable information is what they need most. What is the extent of the damage? What critical infrastructure needs attention? And of course, most important of all, where are the most casualties likely to be?
I hope you found those articles interesting. If our discipline is to become increasingly professional, we need to make real world improvements to both customer experience & bottom lines. To achieve that needs a relentless focus on not just understanding new theories or new technologies but getting practical with them. Without practical application early on, all this new technology is just a time-wasting fetish.
What are you doing with Big Data or IoT?
Are you using Big Data, Predictive Analytics or the Internet of Things to make a practical difference for your customers or business profitability? Please do share your experience, we’d love to hear from you.