More and more, organizations are beginning to identify their dark data and trying to figure out what to do with it. Dark data could include items like unopened email attachments, raw survey data, website log files, and document drafts saved on personal devices. Employees, customers, and vendors create this data as part of regular business operations and processes, but organizations in the past rarely used it or they may not have even realized that it exists. The unstructured nature of dark data makes it hard to track or to know what to do with it. However, companies are now beginning to realize that managing this data can yield valuable business intelligence and improve information governance. The first step towards achieving these goals is to be aware of the issues associated with dark data. The next step? Determine what tools can help combat these issues and provide organizations with access to their dark data and derive benefits that come from it.
Potential Dark Data Obstacles
While each organization has their own unique needs and challenges, dark data generally provides the same roadblocks for most. This type of data is difficult to track down and can hinder daily operations. For example, if an organization experiences a breach and there is a large amount of dark data floating around, the corporation will not know the extent of its compromise, nor all the parties that should be included in necessary notifications.
Consequently, this can result in compliance violations and opens the door for hackers to have access to sensitive information without anyone knowing.
Another big obstacle is litigation compliance. Organizations must preserve, identify, and disclose any unstructured data subject to litigation, even if it is hidden in various places. If an organization fails to perform due diligence and retrieve dark data subject to litigation, they could face sanctions and an unfavorable outcome in court.
Dark data also raises potential costs associated with eDiscovery retrieval and review. Without a comprehensive management system of dark data, it is difficult to know what data is valuable and what is useless. As a result, the time and cost spent looking through unstructured dark data to respond to a discovery request is wasteful. Dark data that is irrelevant is considered a type of “stale data”. Stale data is a term of art that essentially refers to outdated versions of a data source that are contained in the cache. Stale data takes up a large space in the dark data universe and organizations need to address the implications this causes.
Utilizing Technology to Address Dark Data Challenges
Dark data management and analysis can be overwhelming. However, there are resources that can make this process efficient. Auto-classification tools are excellent options to get dark data in order. Since much of an organization’s dark data is often stale, it is vital to explore technological tools that can help limit the amount of dark data within a corporation. After defining the type of data that is present and implementing a classification system for dark data, an auto-classification solution can help with identification and retrieval. An auto-tool frees up time for designated employees to pinpoint which data is stale and dive deeper into the dark data to actually derive some insight.
Consider the following scenario: an organization determined that the sales department received several emails with attachments that were not pertinent to their department, so the sales reps did not open the attachments. As a result, the data went dark. However, these attachments contained data that is valuable to the marketing department. Using auto-classification technology could streamline the process of data identification, retrieval, and classification while allowing staff to analyze this data and realize the potential business intelligence it holds. In the above example, an auto-classification tool would have seamlessly targeted the data in the unopened attachments as useful and thus, the data would never go dark but instead, create value.
There is good news for organizations that already have or intend to invest in Microsoft 365 – they can save significant time and money by simply learning to configure and deploy its various auto-classification tools and features to help manage dark data and decrease risk.
The Microsoft 365 solution provides the ability to move organized data to a centralized, secured cloud, and bucket it accordingly. Certain tools can also assess what data is stale or sensitive. In turn, this ensures that organizations will be more aware of their dark data and have it organized, which helps meet privacy requirements, comply with litigation demands, and develop better business strategies. Being able to reuse technological investments for dark data management is a smart business move because it cuts down on costs and training needs. All of this leads to improved information governance, and better business decisions.
For more information, please contact:
Caroline Woodman, Senior Vice President and Managing Director, Asia, Epiq
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