What is dark data?
The organisation, administration and governance of large volumes of data is becoming more and more difficult to manage, to the point that it is assumed that only 10 percent of Big Data is being managed effectively. The remaining 90 percent is the so called dark data which stands for operational data that is left unanalysed.
Various approaches to data
We can point out some different approaches to data management: the first one of which stands for data which is unknown to the organisation. Some entrepreneurs don’t even realise the existence of dark data and therefore cannot exploit it.
Another approach can be observed when an organisation is aware of their dark data collection but doesn’t have capacity to process it. There are companies that tend to accumulate dark data just in case hoping to analyse and make use of it in proper time.
Finally, some companies don’t conduct any analysis despite having capacity, as they either consider the analysis to be too expensive and not commensurate with the amount of work that would have to be put in it, or simply don’t know how to manage it.
In consequence future value of dark data diminishes and turns into hieroglyphs, unreadable to next generations. The most gloomy fact about dark data is its incoherence, so we don’t even know what to expect and what’s hidden inside the cluster. Putting it into a daylight can be similar to opening a Pandora’s box. On the other hand, dark data might have some hidden potential that we’re simply not aware of. The data can be monetised unless it is stored on devices that have become obsolete.
How to manage data?
From the perspective of a future business, dark data can be transformed into a 360-degree customer overview. Entrepreneurs are looking for effective ways to analyse their current figures and reduce maintenance expenses of unanalysed dark data. There are some strategies of how to achieve both goals.
First of all, it seems vital to correlate various sets of data which can be done by a specialist in database analysis. We can predict that, within a few years, analysts of such data will become one of the most-in-demand jobs. Deep analysis of dark data can make a positive contribution to a decision about customer service policies.
Secondly, enterprises should rethink real value of the data they hold. Each piece of information consumes space which in turn creates costs. Therefore, a reduction of data might be beneficial, especially when it comes to long-standing customer records. However, for better cost efficiency, out of date resources can be resided in the Cloud.
Dark data management requires intuitive, automated software that enables IT to deliver more analytics-ready data to the business faster. Disregarding data analysis and perceiving it as a short-term trend might be unreasonable from the business point of view. Data is the new currency and its importance will definitely grow.