Is visualizing data enough?

The short answer is “No.”  If you want to stop reading now, at least you got the answer!

Brad Peters’ recent article at Forbes is really a great read, to the point where I had to try and figure out which parts I wanted to address in this post.  Because he raises so many interesting points and potential questions, this post could go on forever in engaging them.

But the core of what he is talking about is really quite something:

The key to being successful with visualization – and for being successful across your entire BI strategy for that matter – is ensuring priorities are established. Consider this: before spending all of your money on a super sound system for your car you may want to invest in a navigation system to ensure you can get where you want to go easily. The same can be said of any organization’s data strategy. Why invest in the bells and whistles if you haven’t yet determined the core problems you need to solve?

What he is saying here (and throughout the whole article, really) is that visualization is not enough.  And by this, Peters is referring to the demand for businesses to prioritize their data and BI needs, so as to better understand what their actual goals are and how best to meet them.

Like Peters, iVEDiX is a firm believer in placing things like visualization on a spectrum of importance, because he is eminently correct when he says that visualization is only a useful tool after you have the required systems in place. After all, if your data is a mess, you will only visualize a mess.  Visualization is beholden to the systems that are working underneath it.

Not coincidentally, this is why miVEDiX is not just a visual tool, but an entire platform.  It starts with data mapping techniques that ensure your visualzation is actually going to be productive.  And this is a hugely important difference between miVEDiX and other mobile BI offerings, as the former has been designed with this premise clearly understood.  As Peters points out:

This is not to belittle the art of visualizing business information. It has the potential to be a hugely powerful capability in a company’s BI toolkit. But if you are buying cars you don’t start with the Ferrari as an everyday driver — and only then buy the reliable minivan.

 Absolutely correct, as far as we can see.  So how do we get to this point?

We like to tell people that miVEDiX offers real data discovery.  This is not to disparage other methods or modes for data discovery, but our complex visualization scheme is built upon a platform of assets that makes the visualization work to actually aid that discovery.  This might seem like a mish-mash of concepts, but Peters’ advice is pretty prescient, here.  It doesn’t take much to realize that most of the normal business intelligence processes can be done with simple dashboards and reports.  You, the reader, do me a favor: take your most used business intelligence application, and think for a moment about the aspects you use most.  How many dashboards do you use?  How many charts do you look at on a daily or weekly basis?  What are the key figures you are interested in?

If you are like most BI solution users, you probably only use a select few of all of these on a regular basis.  You have your favorite metrics that you like to check, and a your favorite measures that you like to keep an eye on.  And all of that is cool and probably inevitable.  Where good visualization comes into play is after you have established these patterns, these likes and dislikes.  Or as Peters calls them, your reliable minivan.  Once this system is set up though, and once you have a robust framework from which to work, visualizing new trends becomes an invaluable process — and here we get into real data discovery.

They key point to take away from all of this is not that visualization is a frill or a fringe benefit.  A robust visualization system can add tremendous value to your BI initiatives.  But it has to come after your organization has decided which aspects of BI are the most valuable to your goals.  There is far too much data out there, and there are too many ways to look at it, to simply say “Visualization!” is the way to do business intelligence.

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