By Filip Cotfas, Channel Manager, CoSoSys
Modern business is indeed heavily reliant on data. Organizations constantly seek new ways to use data intelligence to enhance marketing, sales, and operations. However, this dependency comes at a cost: the unstoppable increase of unstructured data.
What exactly is unstructured data, and why is it a problem?
Organizations have traditionally only had to deal with limited quantities of structured data that have been arranged into a prepared repository. With work from home and the Hybrid working model, the tendency has turned toward massive volumes of unstructured data from emails, multi-media content, other sources. The source has become multiple devices and not a single device. Because this sort of data does not adhere to traditional data models, it might be challenging to analyse.
Sharing sensitive information through any workplace communication technologies might also expose data, whether within or outside the firm. That is, quite likely to have large volumes of Personally Identifiable Information (PII) or Intellectual Property (IP) stored in the systems as unstructured data. The challenge of unstructured data is worsened by the fact that the vast majority of it is text-heavy and frequently people-oriented. This is where both data protection & data privacy becomes concerning for businesses and enterprises.
Why Unstructured Data should be taken seriously
To address this, we must first examine the existing approach: the hyper-focus on perimeter defenses frequently leads to a lack of complementary internal security, exposing businesses to one of the most serious security threats: the insider threat. Insider threats are particularly harmful since they are difficult to detect, with many occurrences resulting from authorized individuals accidentally misusing data. Because the data in your company has a monetary value in the real world, businesses must preserve their massive unstructured data to avoid reputational injury, expensive penalties, lawsuits, and economic loss.
How Should You Approach Unstructured Data?
The need to guarantee that unstructured data/sensitive information is kept confidential and that there is no risk of data leakage is becoming a major issue for organizations of all sizes across sectors. To secure data, it is critical to ensure that specific security risks are addressed and design policies and processes that are effective yet simple to apply. Policies and practices such as restricting guest access, tracking third-party software, and lifecycle management can all assist. On the other hand, organizations should be cognizant while using workplace tools & their efficacy and how simple it is for users to share data correctly, in line with the regulations. Personnel training is another critical measure that can help to decrease security risks even further. Companies should ensure that their staff is aware of their data security rules and acceptable data sharing methods.
Companies can also use Data Loss Prevention (DLP) solutions and technologies with content-aware protection capabilities to give an additional layer of data security. First, you must ensure that you have a method of identifying where your sensitive data is located using Data Discovery and categorization using DLP Solutions. That is the process of identifying, marking, and categorizing data that you believe is in danger. Furthermore, DLP Solutions can audit, monitor, and notify changes to data in real-time. Some DLP software contains predefined definitions for the most common types of protected data, such as personally identifiable information (PII), credit card numbers, source code, and regular expressions. They also enable you to safeguard data based on file type or name and provide unique content to fulfill specific requirements.
Enterprises must take data security seriously since a lack of effective controls and checks may expose a company to considerable threats.