Big Data Simplified

Over the past few months, I’ve heard and/or read the following statements from consultants:

• Big data is complex.
• Big data is complicated.
• Big data is the future.

While I would generally agree with those statements, I would also argue they are used as ‘scare’ tactics to try to drive business to consultants and big data vendors.

Big data is complex, complicated, scary and time-consuming to do correctly. Big data is also a bit scary for those folks that hear about how the future is big data yet they have no clue how to get started.

As I’ve written before, the first thing to realize is that big data isn’t necessarily about the size of the data that you have. Organizations trying to ‘do’ big data sometimes struggle with the fact that they can’t ‘do’ big data because their data sets and/or technology platforms aren’t big enough’.

In Big data, it’s all relative,I wrote:

Regardless of size of organization or data-set, the process of ‘doing’ big data remains the same: collect, verify, compare, contextualize, analyze and use the data. Repeat as necessary.

That really is all there is to it. Big data is complex and complicated if you let it be, but if you break it down into its simplest parts, big data is nothing more than collecting and analyzing data. There’s nothing too scary about that.

Don’t let the scare tactics of vendors and consultants confuse you into thinking big data is more than it is. You and your organization do need to have the right technologies and the right skills in place to do big data correctly, but you don’t need to hire heavy-duty consultants ore spend millions of dollars to get started analyzing your data.

All you really need to do is just start looking at your data and let the questions and answers flow. It can’t get much simpler than that.

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.