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Data Loss Prevention Strategy Essentials
Data Loss Prevention (DLP) should be a concern for companies of all sizes. Earlier organizations had to focus only on securing physical documents, but the explosion of the internet has made it easier for hackers to steal valuable data. DLP is crucial for an organization, but there are specific guidelines an organization must follow before a data loss prevention program. Here are a few steps:
Companies hold vast amounts of data, but not all data is essential. A company must prioritize their intellectual property in their DLP efforts, especially of their future projects. Similarly, retailers must keep their PCI data on priority and healthcare companies must safeguard their patient records.
Classification of Data
Classification of data by context such as associating with the source application, the user who created the data and data store is one of the significant challenges in DLP. Applying classification tags to the data allows an organization to track its use.
Track Data Movement
Identify and understand how data is used and moved. Data movement doesn’t mean that data will be lost, but some activities can increase the risk of data loss. Organizations must keep their data safe and secure by monitoring it and should make a DLP strategy that takes care of the issue.
Organizations must work with business managers to create controls and reduce data risks. Monitoring the data shows an organization the amount of risk their information carries. Data usage control is one of the simplest DLP strategies while getting support from managers. The organization can develop better methods to mitigate specific risks after the DLP program matures.
Employees with proper training can often mitigate the risk of accidental data loss. Organizations must train their employees regarding their actions leading to data loss. Advanced DLP solutions stop employees from violating company policy.
Get in Control
Drafting relevant data and regulating it is the first step in DLP. It is not a one time job and needs focused effort. DLP is easy to execute and run, and when applied accurately, it renders precise feedback on growing the program further.