Resources > Articles

Finding Answers in Dark Data

Dark Data

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.

Author

Other Resources in this Series

Most Recent

Spotify is data-driven
Article

Case Study: How Spotify Prioritizes Data Projects for a Personalized Music Experience

Spotify, a titan in the realm of audio streaming, has transformed the way we experience music and podcasts. Since its inception in 2008, it’s become a ubiquitous platform, boasting a colossal user base of approximately...
Category: Data Science
Team Prioritizing Projects
Article

Avoid These Mistakes When Prioritizing Data Projects for Your Company

Even in a world full of data, business decisions often still rely on instinct and emotions. However, when it comes to business, considering all external factors before making a move is essential. This is where...
Category: Data Science
Guy celebrates connection
Article

Harnessing Data to Forge Emotional Bonds with Customers: Insights from Zack Wenthe

Zack Wenthe joined a recent episode of Data Chats to discuss the importance of understanding how consumers interact with your brand, how customers make decisions emotionally and leveraging data to create meaningful decisions.   Wenthe is...
Man and Woman Working on Same Laptop
Article

The Path to Data Democratization

Data democratization isn't easy. Developing a successful data strategy requires a clear vision of the end goal or purpose that an organization wants to achieve within one year to eighteen months. This vision should be comprehensive and ambitious, considering every aspect of the investment and budget.
Category: Data Science
Business Team Communicating
Article

Communicating Data to Non-Data Teams

Providing data insights to non-data teams can be a challenging task. Non-data teams often have limited knowledge of data and statistics and may not have the skills to interpret and apply insights effectively. Here's what you can do about it.
Category: Data Science

OTHER ArticleS

Spotify is data-driven
Article

Case Study: How Spotify Prioritizes Data Projects for a Personalized Music Experience

Spotify, a titan in the realm of audio streaming, has transformed the way we experience music and podcasts. Since its inception in 2008, it’s become a ubiquitous platform, boasting a colossal user base of approximately...
Category: Data Science
Team Prioritizing Projects
Article

Avoid These Mistakes When Prioritizing Data Projects for Your Company

Even in a world full of data, business decisions often still rely on instinct and emotions. However, when it comes to business, considering all external factors before making a move is essential. This is where...
Category: Data Science

Sign up to stay up to date on the latest industry best practices.

Sign up to received invites to upcoming webinars, updates on our recent podcast episodes and the latest on industry best practices.

Training on Your Schedule

Fill out the form today and our sales team will help you schedule your private Pragmatic training today.

Subscribe

Subscribe