Data serves as the cornerstone of organizations— propelling innovation, fostering expansion, and shaping strategic decisions. However, with great data comes great responsibility. Enter Data Risk Management, a critical practice that ensures your organization’s data remains secure, compliant, and free from threats. In this blog, we’ll explore common mistakes that organizations make, the importance of data risk assessment, real-world statistics, and a practical “How-To” guide on managing data effectively to mitigate risk.

What is Data Risk Management?

Data risk management is the practice of identifying, assessing, and mitigating potential risks related to the handling and protection of data within an organization. Nearly all of today’s business operations hinge on data— whether it be decision-making or innovation—data risk management is essential, especially so for GDPR (General Data Protection Regulation) and other evolving regulations.

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The Importance of Data Risk Assessment

Effective data risk management begins with a thorough data risk assessment. This process involves identifying, evaluating, and prioritizing potential risks to your organization’s data. It provides insights into vulnerabilities and helps allocate resources for risk mitigation among several other benefits like:

  • Data Privacy Compliance: With regulations like GDPR, CCPA (California Consumer Privacy Act), and more, organizations are legally obligated to protect individuals’ personal data. Failing to comply with these regulations can result in hefty fines and legal consequences. Data risk management helps ensure that an organization meets its legal obligations in handling data responsibly.
  • Data Security: Cyber threats, data breaches, and cyberattacks are on the rise. Proper data risk management helps protect sensitive data from unauthorized access, reducing the risk of data breaches and safeguarding an organization’s reputation.
  • Reputation and Trust: Data breaches and mishandling of data can significantly damage an organization’s reputation and erode trust among customers, partners, and stakeholders. Effective data risk management ensures data remains secure and trustworthy.
  • Operational Efficiency: Managing data risks also involves maintaining data quality, accuracy, and availability. When data is reliable, an organization can make better decisions, improve processes, and operate more efficiently.
  • Financial Consequences: Data breaches and regulatory fines can lead to substantial financial losses. By managing data risks, organizations can avoid these costly repercussions and allocate resources more effectively.
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Common Mistakes in Managing Data Risk

Data risk look different across organizations and various industries but there are some common pitfalls to watch out for like:

  • Underestimating Data Value: Many organizations overlook the immense value of their data. This can lead to insufficient investments in data protection measures, leaving them vulnerable to breaches and cyberattacks.
  • Inadequate Data Classification: Failure to properly classify data according to its sensitivity can result in inadequate protection. Not all data is created equal; personal and financial data demand higher security measures than non-sensitive information.
  • Neglecting Employee Training: Human error is a leading cause of data breaches. Without proper training, employees may unknowingly compromise data security. A lack of awareness training makes an organization more susceptible to insider threats.
  • Ignoring Data Lifecycle Management: Data isn’t static; it has a lifecycle from creation to disposal. Failing to manage data throughout its lifecycle can lead to data breaches, compliance violations, and inefficiencies.

Real-World Statistics on Data Risk Management

How-To: Managing Data for Privacy, Security, and Governance

Where to start? A few key steps can make all the difference to help improve your organization’s risk posture and protect your most valuable assets. A few critical steps you can take are:

  1. Data Classification: Implement a robust data classification system to categorize data by sensitivity. This helps determine appropriate security measures.
  2. Access Control: Restrict data access based on job roles and the principle of least privilege. Ensure that employees only have access to data necessary for their tasks.
  3. Regular Auditing and Monitoring: Continuously monitor data access and conduct regular security audits to identify and address vulnerabilities.
  4. Employee Training: Provide comprehensive data security training to employees to raise awareness of potential risks and how to mitigate them.
  5. Data Backup and Recovery: Implement regular data backup procedures and disaster recovery plans to ensure data availability in case of a breach or system failure.
  6. Incident Response Plan: Develop a well-defined incident response plan to swiftly and effectively address data breaches should they occur.
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BigID’s Approach to Data Risk Management

BigID is the industry leading platform for privacy, security, and governance— with next gen data discovery that leverages advanced AI and machine learning for total visibility and control across all your sensitive data. Both in the cloud and on premises, BigID scans, identifies, and classifies structured and unstructured data at scale. Reduce your risk with comprehensive data lifecycle management from end to end.

With BigID you can:

  • Know Your Data: Get deeper insight and understanding of all your sensitive data— no matter where it resides. Accurately discover, identify, and label across your entire data ecosystem including structured, unstructured, and dark data.
  • Automate Classification: Automatically map and classify across different connectors, with a comprehensive and dynamic data inventory.
  • Reduce Data Access Risk: Closely monitor, assign, and revoke data access based on need. Locate over privileged users and roll back rights over non essential data for reduced risk.
  • Prioritize Remediation: Streamline remediation efforts using the BigID Action Center by automating specific actions such as making an API call, sending an email, or opening a Jira ticket to enable remediation. Carry out actions such as masking, deleting, quarantining, or encrypting data.

Successful data risk management depends on your organization’s ability to be proactive— to see how BigID can help you start tackling risk head on, book a 1:1 demo with our security experts today.