The World of Dark Data

 

I am not sure if I have been living under a rock, but it has only been recently that I have heard the term ‘dark data’. 

So, what does this term mean?

According to Gartner dark data is the information assets organisations collect, process and store during regular business activities, but generally fail to use it for other purposes, such as analytics, business relationships or marketing etc.

In my research there are advantages and disadvantages to organisations and dark data.

It can: –

  • Provide valuable insights into areas previously unknown as the data has not been analysed before
  • It can help save time and money and provide business the option to automate consuming task
  • Can assist better with decision making
  • The more data available the more information that AI can analyze and can allow AI tools to product deeper and more accurate insights
 

But it can also be: –

  • Time consuming and expensive
  • Requires a lot of storage as it can be extremely large and unstructured
  • Can be hard to interpret
 

It then occurred to me that if organisations have all this data that they are not using, surely it raises ethical concerns that businesses need to navigate to maintain trust and transparency. If dark data can come from a range of sources, such as customer records, social media posts, emails and so, is there not potential for misuse and privacy violations, especially when you look at it in the context of advanced analytics and AI technologies. 

On further thought and investigation, there would appear to be quite a few ethical concerns when it comes to Dark Data.

  • Many individuals may not even know that their data is being collected, so there is the question of consent
  • With all this dark data you would need to question the security aspects, given the increasing number of data breaches and cyberattacks, the ethical concerns and understanding how to protect this sensitive information would seem vital
  • Consideration for discrimination and bias with organisations that have a strong reliance on AI and machine learning algorithms to analyze and make decisions based on data, could be at risk of the unintentionally creation of bias
  • Not only do organisations need to consider the collection and storage of dark data, but also the third-party vendors and partners who work with these organisations, to ensure that date is being used responsibility and ethically
 

As always, I seem to find myself asking more questions when I research topics around data. But it would appear that in order to avoid the potential damage that dark data can cause, organisations need to create strategies to manage dark data challenges. Developing a plan on how to manage it, as well as investing in the right tools and technologies to ensure compliance seems like the best place to start.

….and who knows what they might find when doing this……

Tracee Rowe

Konnexus

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