Who’s afraid of the dark?
Whilst the dark web may have frightening connotations, dark data isn’t nefarious in any way. It’s actually best described using an iceberg analogy.
See, of the masses of data we create, it is estimated that we only actually use around 1% of it. The vast majority of data is unstructured, collected by businesses but then left sitting untouched below the surface.
Of course, your gears may already be spinning; if we’re only using 1% of the data, what would happen if we were to use 2%, 10% or 50%?
Well, you’re not alone.
The idea of creating better systems to sift, analyze and structure this data is an integral part of machine learning and data science.
If you’ve read anything about the internet of things, you know that the generation of data isn’t simply coming from online surveys and user profiles but from every corner of the globe and every corner of your home.
But what is dark data specifically? And, more importantly, why is it just sitting there…in the dark?
Well, dark data is simply unstructured data that has yet to be analyzed, and it sits in data repositories.
Because companies are gathering so much data, much of this unstructured data has to be pushed into archives because it is not being used, hence it comes to be known as ‘Dark Data’.
The reason it sits there unused is due to two main reasons. Firstly, businesses generate much more data than they can use, and secondly, businesses don’t have a way to efficiently process the data.
An overworked data scientist who is already handling masses of other data for a company likely doesn’t have time to sift through every piece of data that is generated.
And like the Titanic, not seeing the whole iceberg does have its problems.
Analyzing more of this dark data would allow businesses to monitor things like customer support logs, network security, customer profile patterns and much more. As businesses move more into online platforms, maximizing efficiency is key, and by understanding dark data and data patterns they can ensure network structures are used correctly.
When this stuff goes unnoticed, it means key insights are being missed. In fact, analytics experts at Quantzig revealed that organizations that leveraged dark data achieved a 55-60% improvement in outcomes.
Essentially, for many businesses and brands, dark data is a blind spot in their analytics.
Global market research is worth billions and the martech (marketing technology) space has the potential to reach $100 billion dollars per the current WARC report.
Moreover, their report noted that it is data that drives the growth of martech, and as marketers realize that expertise in data leads to actionable insights, companies that have a handle on their data can achieve greater ROI and have more control over their products, services and applications.
However, it isn’t as simple as getting information out of the data, you also need to know what it is you are looking for. Finding the unanswered questions in your business and using dark data to answer them is what will separate the wheat from the chaff, especially as more and more businesses leverage the use of data to get an edge over their competitors.
