The 5 R’s of Big Data
- Posted: 12th January 2015
- Written by:
In the midst of a string of recent external communication around Big Data and the growing disappointment with such initiatives I, jokingly, suggested that I should seek fame and fortune writing on the subject of the Five R’s (not the sustainability ones, although there may be something here about the sustainability of continual data acquisition).
This was a rather off the cuff remark, part pun on the old Three R’s of education and part frustration on my part at what seemed to me to be the blindingly obvious being ignored by otherwise intelligent individuals. Having thought some more about this I decided that, whilst I doubt that fame and fortune would follow, it would make a good subject for the Celerity Blog, following on from other data related musings.
The Five R’s as I refer to them are as follows:
- the right data from
- the right sources delivered at
- the right time interpreted in
- the right way and utilised for
- the right purposes
There are implications to this (which I have mentioned in a previous post) in that the start point has to be an understanding of what you are trying to achieve from a business perspective, as this enables you to define the right purposes where everything else flows.
There is no point in keeping every lowest level transaction item or thousand word Facebook rant if what you are trying to achieve is an understanding of information at a much higher level – nor if there are doubts about the veracity or quality of the data that you are gathering.
There is an adage that says that you are far more likely to hear from a disgruntled customer than you are a satisfied one and this is true in spades for online forums and social media. This is not to say that there is no value in understanding these negatives, but you wouldn’t want to build your future product or sales plans around an assumption that it was truly reflective of your business; here again it’s all about the appropriate use (interpretation & utilisation) of the right data from the right sources.
Even worse would be to make those decisions based upon opinion (or even fact) that was months or years out of date. Like everything else data has a shelf life and part of good data governance should be to apply health warnings and ‘use by’ information to data to ensure that it can be properly utilised for appropriate decision making at the right time. You need understand that a particular set of figures are five years old and should only be used in that context, or that a complaint is about a product that you no longer stock, sell or manufacture.
Continuing to capture data without proper governance (including housekeeping), simply because current technology allows it, will not in the longer term serve any one in the knowledge business well, although those who sell storage technology will be more than happy.
You could of course continue to keep everything for ever “just in case”, but then this simply increases the need for better governance, else you’re likely to find that, like my loft, your data store is full of things you no longer need and in which you can no longer find the things that you do.