By Joe Peppard
While “Big data” has garnered a lot of attention over the last number of years, many managers struggle in deciding where to begin. They can often be mistakenly seduced by technology companies with the promise of an IT solution to the (big) data problem. By first distinguishing between the two different ways that data can be leveraged, this article suggests a route to navigate the terrain. It introduces the QuDa model as the foundation from which a (big) data initiative can be mapped. Its fundamental premise is that it is managers not technology that give meaning to data.
One of the questions that I frequently encounter in my work with executives concerning so called “big data” is where to start. Unfortunately, many look to their IT organisation for guidance, seeing the challenges as being technical in origin and consequently having an IT solution. They can often be convinced – wrongly in my opinion – of the need to buy technologies like a data warehouse, analytical tools, or perhaps event to invest in Hadoop. While all these technologies might help, my advice is to first get a handle on the data your organisation has, its quality and how you currently use it. With this understanding, you can then start to become more sophisticated in thinking about how you might use data and the outcomes being sought.
Of course, it is crucial to first acknowledge what you are trying to achieve. This is why it is important at the outset to recognise the distinction between the exploration of data and the exploitation of data; this helps in establishing a focus for any initiative. With this understanding, particularly how the two concepts interrelate, managers can then begin to map out what they are seeking to achieve. In this article I argue that there are four possible outcomes when exploring data and that these outcomes can help in providing the clarity that is all too often absent.