How well do you know the data your business collects? Many businesses, big and small, collect large amounts of data through their systems and processing. And often, they are collecting information that goes unnoticed, stowed away to gather dust on a server. This is known as “dark data,” and more companies are using big data software to access and analyse this unseen information to enhance their business.
If you’re looking for creative ways to use data to your advantage, read on. We’ll cover everything you need to know about dark data, including what it is, how to find it, and how to use it to your advantage.
What is dark data?
The official definition of dark data, according to Gartner, is “information assets organisations collect, process and store during regular business activities, but generally fail to use for other purposes.”
Dark data can refer to any type of data—but what sets it apart is the way it’s treated. It’s the information you collect as a business, but which your data team does not routinely analyse.
The phenomenon is surprisingly common. In a survey of 1,300 business and IT leaders, Splunk found that approximately 55% of organisations’ ’ data is dark. However, nearly every respondent said that they consider data to be “very” or “extremely” valuable to their success.
Examples of dark data
Data refers to any information your business collects in bulk. It’s a broad term, but there are certain types of data that are more likely to “go dark” than others.
Dark data can be split into three categories, so let’s break those down and discuss the different examples within each.
Unanalysed internal data
This is perhaps the most common type of dark data. It refers to the information that businesses collect and store as part of routine business operations. This could include customer interactions (how long customers spend on-site before making a purchase, for example), customer service call logs, email or chat logs, or even surveillance footage.
Data made available through new technology
Sometimes, new technology makes previously untapped data accessible. The best example of this is mobile analytical data. Thanks to the rise of the smartphone and tablets, you can now analyse things like device usage and geolocation of customers. You can also use new big data analysis tools to identify new patterns within data that you may not have known about before.
Data from the deep web
Sometimes, data goes dark all on its own. Firewalls, which businesses use to maintain security, can obscure information. It’s impossible to analyse this data unless your business has the right tools and expertise to gather and decode it. When collecting this type of data, businesses need to ensure they are not violating any privacy regulations, as sometimes information hidden behind a firewall is put there for safety reasons.
What are the benefits of using dark data?
Now that you understand what sort of information qualifies as “dark data”, you may be wondering why you’d dedicate time and resources to gather and analyse it.
Gain new insights to improve your business
Data is key to improving your business operations. According to Datumize, 71% of executives expect data to become more valuable in the next decade. This means that businesses that have more in-depth data to analyse will outshine their competitors and have a deeper understanding of their customers’ and clients’ behaviours.
Freeing up your server space
Part of the analysation process is determining which data sets are useful to your business, and which can be discarded. Your business likely pays for server space to store all of the data, and these costs can add up quickly. If you’re currently paying to store information that you aren’t or can’t use, then you are essentially throwing money down the drain.
By analysing the dark data, you can clear away anything that’s not necessary, so that you’re only paying to store data that has real value.
How to recover and start analysing your dark data
Is your business sitting on dark data that you’d like to put to use? Here are the steps you can follow to start unearthing the dark data to see how it may prove useful.
1. Ensure you have the right staff and technology
Analysing data in bulk is a big task. If you’re planning on unearthing even more data, you must have the right people and technology platforms in place. Speak with your current data analysis team to see whether they can take on the extra work. From there, you can make sure they have the tools they need to start the project.
2. Determine what “dark data” is available and worth analysing
Once your team is ready to go and have the technology in place, begin combing through your storage servers to see what data is available. Keep the aforementioned examples of dark data in mind as you look through what’s in storage. Compile these resources into a list, so you can determine what to keep, what to delete, and how to proceed with the next step.
3. Create a strategy for dark data analysis
Once you know what data you want to pull, your analysis team should begin building a strategy to start the process. To do this, they need to consider:
- Who will be responsible for which sets of data?
- How will you record findings from the analysis process?
- What other teams/staff need to be informed of the findings?
- What steps will the business take to effectively use the data?
Businesses that make dark data analysis part of their strategy stand to gain deep insights into their business. With the right plan in place, your company can reduce unneeded data while also pulling information that could change the way your business operates for years to come.