Over the last 5 years I have often been in boardrooms where C-Suite champions have entranced fellow VPs with glittering visual analytics. Too often they have not not moved far beyond that and everyone knows that "all that glitters is not gold"
Purpose built analytics applications deliver true decision-making capability. But, as Martin Butler points out, if us poor humans can generally only deal with five things at the same time, machine learning and automated decision-making must come to the rescue of humans to allow them to focus on the important five things.
Algorithms, and those derived from machine learning will have to evolve fast to achieve this end. Who would have predicted the spread of the zika virus before the 2016 Olympics? What was then a "Brazilian Thing" has now made Singapore a place to avoid today. Before we get too reliant on TeleHealth and IoT Wearables data scientists have lots of work to do on automated decision making.
I am interested in location intelligence solution providers like Carto. Can they combine location and health data to anticipate hazards like the Zika virus?
Combining these spatial and other data sources in analytics platforms and embedding these in healthcare decision-making engines is part of the Five stages of the Analytics of Everything.
Most organisations are only on stages one and two- to judge where you are check here.
I have used healthcare as one example but the same goes for all industries and segments
There are many reasons why visual analytics have captured the imagination of millions of business users. The most obvious is that they feel empowered by the ability to easily assemble attractive graphics displaying some aspect of business performance. It was only five or ten years ago that most business users had to rely on IT folk – something they truly resented. And so autonomy has proven to be extremely attractive. The suppliers of pretty data platforms know this and boldly assert that IT support is not needed from moody, unresponsive IT people. In actual fact we are already past the zenith of the pretty data fad- slicing and dicing data and formatting it with designer color schemes can become as tedious as everything else – unless of course a visual is being put together that totally discredits a political rival.
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