Is BIG DATA real?

Hello again.

Today, we’re gonna talk about BIG DATA. And to be sure that we are talking about the same, first let’s determine what means BIG DATA.

Using an IBM definition, “big data is the definition to describe big ammounts of data”. For Gartner, means a bit more, once “big data is high-volume, high-velocity and high-variety information assets (…)”. According to SAP, “Big Data is the ocean of information we swim in every day – vast zetabytes of data flowing from our computers, mobile devices, and machine sensors (…)”. As we can see, we have a wide range of definitions, from an analytical view, to a “Internet of Things” alignment.

In this post, we will refer to these scenarios, and how to tackle these challenges.

Well, as I mentioned in my previous posts, one good thing to do when we think about IT is to align the business objectives and strategies with IT. However, as we can see on the Design Thinking (which I will talk about in the next posts), we need to have information enough, to take decisions. Otherwise, we are using only “perceptions” and “feelings”, which could be tricky, eventually.

The concept of BIG DATA comes to help us on that.

Considering the huge number of different sources of data, and the levels within this sources, in addition to the almost infinite number of new “stuff” that is generating these data, the challenge here is to find a way to transform it into something relevant. Into information.

From the strategic alignment point of view, BIG DATA comes to support the analysis on the business performance and KPIs, in a deeper level than ever. Given this information, I would like to refer to a marketing campaign that I heard here in Brazil, a couple weeks ago. They said: “That is not the answers that move the world, but the questions”. The BIG DATA helps us on this way.

According to IDC (2013), the IT spending on BIG DATA would increase about 30% last year. Gartner says the companies are investing (or will invest) on BIG DATA is about 64% for this year.

Just to give you an example, let’s have a look on the NBA BIG DATA approach and solution.

They manage to create a “fan portal”, which has about 4.5 quadrillion of combination of statistics. (here!) For NBA, the trigger to use BIG DATA was the fan engagement, bringing more supporters to the league.

But, before start implementing anything on this way, follows some questions that you have to wonder about:

  1. What is the view regarding BIG DATA, in my company? (remember those different perspectives, before starting)
  2. Which are the benefits I expect from it?
  3. Do I have a business case to support the project and investment?
  4. Do I have a real scenario to use BIG DATA?

But please, don’t confuse BIG DATA with business intelligence (BI). In a short, but very well done definition, made by Eric D. Brown:

Business Intelligence helps find answers to questions you know. Big Data helps you find the questions you don’t know you want to ask.

Well, that’s the deal, so…
If you have a scenario with multiple sources, huge amounts of data and opportunities to find new combinations of data, to create a variety of information from it, so you have an scenario to use the concept of BIG DATA.

Let’s try?

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