IT leaders who want to use the data their companies collect to benefit the business face many challenges. One of the most misunderstood challenges is that of dark data.
What Is Dark Data?
Dark data is the type of data that was not fully used in a timely manner for its intended purpose. As a result, organizations often forget that it’s still part of their data ecosystem.
According to Data Dynamics blog Illuminating Dark Data: Shedding Light on Unutilized Information for Enhanced Business Insights and Decision-Making,
This data is information routinely collected while doing business. The main sources from where it is generated is by employees, customers, and business processes. Identifying dark data, its location, and content is crucial. This step is key to protecting the important parts and deleting unnecessary data.
What Is the Cost of Dark Data?
When more than half the data collected goes unused, that comes at a cost in terms of storage, regulatory risks, and security threats. Let’s look at the cost of dark data along these parameters:
Data Breach: When firms don’t have end-to-end visibility of where the data resides and what it contains, it’s possible to accidentally make copies in non-secure devices and expose them to security threats. Besides the reputational damage, firms must also pay a fine for exposing customer information to a breach.
Data Regulation: There is an increased level of spending on collecting and storing customer data for compliance and regulatory purposes. Most of the data is probably never used, but it will have to be stored with proper security procedures to comply with data laws and regulations.
Data Storage: If a large portion of that data is unused, organizations spend millions merely to store dark data. This adds a significant drain on company resources.
Data R.O.T: Dark data can often contain inaccuracies. Redundant, Obsolete, and Trivial data can result in productivity loss whenever wrong data sets are shared for downstream consumption.
Mitigating the Risks of Dark Data
According to a report by BigID, The State of Data Security, 84% of organizations are highly concerned about dark data.
CISOs and legal and compliance executives often seek to implement information governance and security programs like defensible deletion, data migration, and data audits across their unstructured data to detect risks and improve non-compliance.
However, those goals still need actual and scalable technology platforms to achieve these goals. Some of the key challenges that they face are:
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Governance
CISOs generally have a good handle on perimeter integrity, encryption, and other key priorities, such as zero-day network attacks and malware. However, while these measures are essential, distributed dark data is largely a blind spot for cybersecurity tech. As such, organizations have very little visibility into the content of such data. Privacy rules like GDPR and CCPA have made this challenge even more urgent.
CISOs need to make decisions that ensure scalable solutions are implemented. The best way to accomplish this is to have a dedicated IG/compliance team armed with technology that allows and empowers them to push decisions to information owners.
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Data Storage
Data discovery is about gaining total visibility of a firm’s overall data environment by running a process on a huge amount of unstructured data. Firms can identify important data by using various data analytics tools or applying various data pattern algorithms or queries.
Cheap cloud storage options have further made it too easy to be a data hoarder. Firms should proactively update their data retention policies to avoid unnecessary compliance and security risks. This is important in noncritical areas where holding onto certain types of data for longer than necessary could expose the firms to risks. Storing data costs money, so it’s important to remember what data firms accumulate.
Also Read: The Dark Web and Data Breaches: Unveiling the Connection
The next step that CISOs should focus on in dark data management is classifying enterprise data using a data categorization engine. This process enables businesses to determine the value of a certain piece of data and the business to which it belongs, such as where the data might be helpful, data value, security, and risk. This step will help determine what exists within dark data.
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Effective Data Use
CISOs need to ensure that the collected data is used effectively and timely. This goal can be achieved by investing in tools that can query data where it is stored and by moving the data to centralized platforms.
Companies can use tools to find, analyze, and display data across various platforms and locations. This eliminates the need to store the same information multiple times. As a result, it becomes easier for companies to access and view the data. To reduce the number of data stores that must be tracked and managed, storage platforms should be used to collect and store inaccessible data. This will help streamline data management.
Automatically manage the data more effectively with policies that optimize data location. Identify and isolate high-risk dark data, store less frequently used dark data in archives, and prioritize critical data by storing it on the most valuable platforms.
Conclusion
Storing dark data can be expensive for organizations, leading to high storage costs and potential non-compliance fees. However, dark data also has valuable untapped potential to help firms grow. Thus, it is important to identify whether if firms have dark data and figure out ways to manage it to unlock its value.
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