The increasing amount of personal data that organizations collect and process has heightened the focus on data privacy, quality, and governance for individuals and corporations alike. How can your organization address these top-of-mind concerns while ensuring data trust and striking the right balance between protecting personal data and accessing it to support business-critical functions?
You can think of data privacy, quality, and governance as the three pillars that provide the foundation for establishing effective data protection:
- Data privacy relates to protecting personal data from unauthorized access, use, disclosure, or destruction. Organizations are responsible for implementing policies, procedures, and technical measures to protect personal data and ensure it’s only used for the purposes for which it was collected.
- Data quality addresses the accuracy, completeness, consistency, and timeliness of data, all of which are critical to ensuring accurate, reliable sensitive data. Meeting these imperatives requires making sure that sensitive data is properly monitored for quality, correctly classified, encrypted, secured, and accessible solely to authorized users. Maintaining high-quality sensitive data is essential to protecting individual privacy and organizational security, and it requires a holistic approach that addresses both technical and organizational challenges.
- Data governance is a set of processes, policies, and responsibilities that ensure effective, efficient management of an organization’s data assets. Strong data governance requires defining policies and standards, managing data quality, and protecting sensitive data.
When combined, data privacy, quality, and governance provide a comprehensive approach to enabling trust in—and protection of—personal data. By implementing a robust data governance framework, your business can ensure that:
- Its data privacy and quality policies are effectively enforced.
- The personal data it collects is used legally, responsibly, and ethically by people with legitimate and approved access needs.
All organizations have an enormous incentive to ensure their data is protected, well-governed, and trusted, given the host of negative consequences that can accompany inaccurate or incomplete sensitive data:
- Data breaches: If you can’t track who accessed sensitive data and how it was used—or don’t have critical information about who is authorized to access it—it’s easier for malicious actors to exploit system vulnerabilities and gain access.
- Identity theft: Identity theft often involves using incorrect or missing information to impersonate an authorized, verified user. For example, if a financial institution relies on incomplete or inaccurate data for customer verification, it’s easier for criminals to open fraudulent accounts or conduct unauthorized transactions.
- Error-prone data correlation and linkage: When multiple data sources are used to cross-reference or validate sensitive information, inaccuracies can lead to misidentification or the failure to detect fraudulent activities.
- Misdirected communications: Incomplete or incorrect contact information can result in sensitive information being sent to the wrong individuals. This error can inadvertently disclose personal information to unauthorized parties, leading to privacy breaches.
- Regulatory non-compliance: Many regulations and privacy laws, such as the General Data Protection Regulation (GDPR) in the European Union and the Health Insurance Portability and Accountability Act (HIPAA) in the United States, require organizations to maintain accurate and complete sensitive data. Failing to do so can result in significant fines and legal action.
- Reputation damage and revenue loss: Inaccurate or incomplete sensitive data can damage your organization's reputation. When customers discover their sensitive information isn’t properly safeguarded, they may lose trust and take their business elsewhere.
- Operational errors: Incomplete data can lead to operational errors. For example, incorrect patient information in healthcare settings can lead to medical errors that compromise patient safety.
- Lost business opportunities: Inaccurate data can hinder your organization’s ability to make informed decisions and identify new business opportunities, impeding business growth and innovation.
- Making sure your organization’s sensitive data is complete and accurate is critical to safeguarding individuals' privacy, preventing identity theft, and ensuring secure and compliant data handling. Mitigating these risks and protecting sensitive data effectively requires robust data quality and governance measures.
- Sensitive data elements and data quality are closely linked because sensitive data is typically subject to strict regulatory requirements. Any errors or inaccuracies in that data can lead to severe consequences for individuals and companies.
- To maintain high-quality sensitive data, your organization needs rigorous data management policies and procedures to help prevent errors, omissions, and other data quality issues. Your business can ensure data accuracy and integrity by implementing strong data governance practices, using data quality tools and techniques, and regularly auditing and monitoring its data.
Ensuring well-governed, compliant, and accurate data—whatever its type and wherever it resides—can be a time-consuming, complex undertaking. Data Sentinel’s technology, managed services, and advisory capabilities are sophisticated, but our comprehensive data privacy compliance, governance, and remediation solutions are designed to be simple and integrate seamlessly into your business.
Learn more about how Data Sentinel can help your organization accelerate its path to ensuring its data is 100 percent trustworthy and meets regulatory requirements. You can also connect with us or request a demonstration to see our solution in action.