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Sensitive and non-sensitive data are treated differently, as sensitive data should be stored separately from non-sensitive data and protected first.
FREMONT, CA: Every firm requires a data loss prevention (DLP) plan regardless of size or sector. This encompasses all strategic tools and processes that prevent a company's data from being lost, mistreated, or accessed by unauthorized parties. Whether the purpose of DLP policy is to secure consumer data, intellectual property, or corporate data, it is carefully developed and implemented. Knowing where to begin with DLP can be challenging, but keeping in mind a few essential best practices can assist assure the long-term success of any DLP strategy.
Assigning the roles of the users
Before doing anything else, identify the roles and responsibilities of everyone in the organization involved in data loss prevention. DLP techniques entail many things, but optimal practices include recognizing organizational hierarchy and roles in DLP policies. This differentiation restricts data access. The idea of least privilege states that users should only have access to the information they need to execute their jobs. If a user's account is hacked, it's easier to determine how much data is at risk. Clear user roles help in a worst-case scenario. Defining responsibilities will prevent miscommunication, confusion, and inaction.
Define data clearly. Some data will be more sensitive and valuable as firms become more data-driven. By segregating sensitive data from non-sensitive data, they may prioritize business priorities and improve risk management. It should include all company details. All data flowing in or out of systems is in danger, so a bird's-eye perspective is necessary to discover blind spots. After scanning the organization from top to bottom and side to side, categorize data by importance. This data is a crown jewel and may make or break a company.
In security, backups are common information. Without them, lost data would be gone forever, and enterprises would flounder. The quality of data backups will decide how much a security event affects. The backup strategy must balance breadth and depth. Build a layered structure to prevent data loss. Depending on paranoia, adding layers makes the system bulletproof. Businesses should Daily data backups will be worth the investment in a catastrophe recovery scenario. In these circumstances, safety comes first.
Remove extra information
AI and automation may suggest that all data is good and more are better. Data is only useful when it serves a clear purpose. Excess data can impair productivity and efficiency and cause data loss. If data is collected and stored because it's available, it's probably harmful. It clutters the data environment, distracts from critical data, and increases data loss. Eliminate dead weight to reduce risk. If data isn't assisting the business, remove it. Data that doesn't exist can't be lost.