The purpose of data analytics, using big or small data, is
to provide business insight. It is about taking sets of information,
organizing them in a meaningful way and then combining them with other bits of information
in order to empower intelligent decisions.
We all use the best analytics tool, every day, practically all
the time: our brains!
I am sitting here looking out the
window at a set of colors and shapes. That is really meaningless information,
as what I described is too vague. If I provide you with more details you will
be able to match the patterns in your analytical tool (your brain), compare it
to things you already know and will soon be able to comprehend what I am
looking at. Let’s fire-up your analytics engine: I am looking at Green and
brown patterns. The brown patterns are rectangle-like in vertical orientation
and considerably thick. The green ones are mainly on the upper portion of my
view, in oval-like shapes, randomly oriented, and have chainsaw-like edges. They
are mixed with long, thin and curved brown patterns which link to the bigger brown
patterns I already mentioned earlier. I can stop. You probably worked-out that I
am looking at some trees outside my window.
You may be thinking now: well
obviously our brains are analytical tools. We always talk about people’s
analytical skills. That is true, but the property I am after here is the effectiveness
of the tool. Can we build analytical technologies which are better than our own
brains? Faster? Definitely. Bigger capacity? Of course. Better ability to filter
information, reason and draw insight? I doubt it!
If now I tell you that the wind is blowing. You will start
asking: well what does this mean? Well, that is related to reason I am looking
out the window in the first place. Let’s assume I am planning to go on a picnic.
Because I know it is windy, you might conclude that this is likely to degrade
the quality of the picnic. So the “business” dilemma here is whether to
postpone or cancel the picnic. This now demands further insight. Can I go at any
other time? What is at stake? Are there any other parties involved? What if I now
told you now it is 2 degrees Celsius outside?
Or that the planned picnic’s location is far away from where I am now, or
even that the scheduled time is only tomorrow afternoon?
Your brain is continuously integrating the information I am giving you. It is analyzing each scenario and drawing insight.
You can barely even notice that your brain is doing all this work for you.
The point I am trying to make is that our brain does not
change its capacity or processing speed yet we generally improve our analytical skills
every day through learning. So forget distributed data stores, in-memory computing, and
processors’ speed. The best analytical tool obviously needs all the right
information and knowledge base to draw conclusions, but the real “magic” lies
in its ability to filter and integrate information, even (or especially) when
there are gaps in the information that is available to us. Performance will
always come second to clear business requirements and well-designed algorithms
for reasoning and decision making. It seems to me that we are always chasing
the rainbow of bigger and better data stores with stronger processing power, perhaps
conveniently forgetting to check our pockets for wisdom, common sense and
simplicity.
Therefore, I leave you with this: Ask not what you can do
with the data, but ask what can the data do for you.
