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Data continues to be a valuable asset for an organization and plays a crucial role in making operational and strategic business decisions. With the growth of hybrid, private, and multi-cloud models, much of the data is stored on these platforms and becomes vulnerable to malicious activities and potential data leaks.
Amid the vast volume of data, some of the data remains unknown, untapped, and unused with an organization's architecture. This dark data is generated by users' daily online interactions between several devices and systems.
Dark data might seem like a scary term, but it isn't, though it poses some risks. Since its percentage of data is rising more quickly than organizational data, business organizations are getting concerned about it. Hence, to grasp what dark data is and what issues it signifies, it's essential to understand it from a broader perspective.
What Is dark data?
Dark data is the type of organizational data whose value is not identified; hence, it can be crucial business data or useless data. A research report published by BigID reveals that 84% of organizations are seriously concerned about dark data. This data consists of the additional information collected and stored during daily business activities. But perhaps to your surprise, the organization may be unaware of the dark data and typically doesn't use it.
Dark data tends to be unstructured data that contains sensitive and unclassified information. The research report further reveals that eight out of ten organizations consider unstructured data the most critical to handle and secure. Dark data can be classified as follows:
- Emails, images, audio, video, and social media posts.
- Application trials including API caches and encryption keys such as VPN or SSH support.
- Data stored in overlooked virtual images activated or installed in local or cloud infrastructure.
- Forgotten unstructured data created on various database engines a long time ago.
- Customers and the company's employees own data on the desktop and mobile devices.
- The hidden data file in a file system can be in the form of old pictures, scanned documents, pdf forms, notes on MS Word documents, and signed files.
Dark data might seem benign, but it holds most of the organization's information. Thus, it can pose significant security risks if it falls into the wrong hands, like leaking a company's sensitive data and damaging its industry reputation. This is particularly alarming for organisations that do not use a reliable VPN or any other security tools to ensure data privacy and safety.
How can you utilize dark data to help your business?
Dark data seems challenging to handle and involves lengthy manual processes, but companies need to automate these processes. Technological advancements such as the use of AI have made it easier for companies to explore and process unstructured data.
Another important use of dark data is its role in boosting AI-powered solutions. As more and more data exists, the information that AI can analyse to produce even deeper insights. Alongside Artificial Intelligence, you can also use Machine Learning technology to discover untapped and unused data and insights. These insights might help organizations make more informed decisions regarding incoming data. Also, it guides them toward taking practical steps in response to their data.
Implementing AI and ML systems needs internal structural changes for businesses, costing organizations a great deal of time and money. However, the benefits will be a high return on investment, so do invest in it.
Besides this, organizations can use dark data to create management strategies around IoT technology to provide long- and short-term trend analyses to show possible results to managers and senior leadership.
Another way dark data can prove helpful is by developing new and productive business strategies. This helps enterprises analyse which department owns what type of data different employees and management hold. Moreover, it can help improve the quality assurance processes that detect and correct errors. Also, it looks for potential privacy loopholes, vulnerabilities, and compliance violations.
Dark data can improve business by creating revenue, streamlining processes, and reducing costs. It is capable of understanding the relationships between unrelated pieces of information.
Thus, analysing information like server log files can give insight into user behaviour, customer call records, geolocation data, and preferences that can reveal traffic patterns and help in further improving and expanding their business.
Hidden dark data cybersecurity risks
Dark data isn't going away anytime soon; hence, organizations should consider it a big challenge and poses significant cybersecurity risks. Here are some of the issues that dark data brings along it:
There are greater chances that the organization's dark data might violate the data privacy compliance mandates and regulations like the GDPR, PCI DSS, or HIPAA. The organization itself has no idea about this violation unless a breach occurs. In such a situation, the regulators and the clients become extremely angry for not protecting the data. Also, the organization might face lawsuits, sanctions, and hefty fines.
Unused business security intelligence
Another drawback of dark data stored within your organization is that enterprises fail to utilize all security intelligence. For instance, the dark data assets also include system log files that can be used to create more accurate threat and anomaly detection or cyber risk assessment models. But when it goes overlooked, enterprises might experience a hacking or data breaching incident, and they regret it later because they have a way to secure themselves but ignore it.
Increased risk of cyber-attacks
As you store more and more business data on local servers and within the cloud environment, it becomes more challenging to discover, reuse, or retrieve user data – which may increase the risk of a data breach.
When people within an organization don't know what information each data set contains, it can result in confusion about who can access it and who is unauthorized. Moreover, the poorly categorized data even lead to significant permission challenges. Any unauthorized person accessing sensitive information simply puts your business on the verge of a possible data breach or leaks of critical business data. If the wrong individuals are accessing sensitive information, you're putting your business at risk of a data breach.
Besides this, dark data also causes opportunity costs to an organization. If a company decides not to invest in the evaluation and processing of dark data, but its competitors do so, they likely fall behind. Hence, the organization pays the cost of lost opportunities.
How to handle dark data?
Despite using dark data constructively, there are some other ways that you can adopt to handle dark data more efficiently and in a well-organized manner. Here are some of these ways:
- Use strong encryption standards for your business data to prevent data security issues and add an extra security layer to your online data. Organizations need to apply this practice to in-house servers and data shifting in the cloud environment. Using a reliable VPN provider can provide a top-notch level of encryption and online security.
- Organizations must implement data retention policies and remain compliant with the data protection regulation. This allows them to store users' data for a limited time and helps prevent lawsuits or fines. Also, good data retention policies retain valuable data for later use.
- You need to perform regular audits of the database. It includes classifying and structuring data and gives an idea of where what kind of data is stored. Later if you need the data, you can find it easily in an organized database instead of an unorganized form.
- Organizations need to take control of dark data with an appropriate data governance plan. Companies can improve compliance and overall productivity with a robust plan in function.
An organization produces lots of data every day. In an era where cyberattacks are increasing at an unprecedented rate, protecting and governing different data types is an uphill task. Dark data is one of the data types that's tough to handle and secure. It brings multiple cybersecurity risks like legal and regulatory issues, intelligence risks, and increased attack surface.
However, if you know the appropriate strategies, you can make good use of the dark data as discussed above. If used constructively, dark data can bring increased success to your business; if not, it can cause havoc, so now the choice is yours.