Best Practices for Data Lifecycle Management to Enhance Security

Securing all communication and data transfer channels in your business requires thorough planning, skilled cybersecurity professionals, and long-term risk mitigation strategies. Implementing global data safety standards is crucial for protecting clients’ sensitive information. This post outlines the best practices for data lifecycle management to enhance security and ensure smooth operations.

Understanding Data Lifecycle Management

Data Lifecycle Management (DLM) involves the complete process from data source identification to deletion, including streaming, storage, cleansing, sorting, transforming, loading, analytics, visualization, and security. Regular backups, cloud platforms, and process automation are vital to prevent data loss and database inconsistencies.

While some small and medium-sized businesses may host their data on-site, this approach can expose their business intelligence (BI) assets to physical damages, fire hazards, or theft. Therefore, companies looking for scalability and virtualized computing often turn to data governance consulting services to avoid these risks.

Defining Data Governance

Data governance within DLM involves technologies related to employee identification, user rights management, cybersecurity measures, and robust accountability standards. Effective data governance can combat corporate espionage attempts and streamline database modifications and intel sharing.

Examples of data governance include encryption and biometric authorization interfaces. End-to-end encryption makes unauthorized eavesdropping more difficult, while biometric scans such as retina or thumb impressions enhance security. Firewalls also play a critical role in distinguishing legitimate traffic from malicious visitors.

Best Practices in Data Lifecycle Management Security

1. Two-Factor Authentication (2FA) Cybercriminals frequently target user entry points, database updates, and data transmission channels. Relying solely on passwords leaves your organization vulnerable. Multiple authorization mechanisms, such as 2FA, significantly reduce these risks. 2FA often requires a one-time password (OTP) for any significant changes, adding an extra layer of security. Various 2FA options can confuse unauthorized individuals, enhancing your organization’s resilience against security threats.

2. Version Control, Changelog, and File History Version control and changelogs are crucial practices adopted by experienced data lifecycle managers. Changelogs list all significant edits and removals in project documentation, while version control groups these changes, marking milestones in a continuous improvement strategy. These tools help detect conflicts and resolve issues quickly, ensuring data integrity. File history, a faster alternative to full-disk cloning, duplicates files and metadata in separate regions to mitigate localized data corruption risks.

3. Encryption, Virtual Private Networks (VPNs), and Antimalware VPNs protect employees, IT resources, and business communications from online trackers. They enable secure access to core databases and applications, maintaining privacy even on public WiFi networks. Encrypting communication channels and following safety guidelines such as periodic malware scans are essential for cybersecurity. Encouraging stakeholders to use these measures ensures robust protection.

Security Challenges in Data Lifecycle Management

1. Employee Education Educating employees about the latest cybersecurity implementations is essential for effective DLM. Regular training programs ensure that new hires and experienced executives understand and adopt best practices.

2. Voluntary Compliance Balancing convenience and security is a common challenge. While employees may complete security training, consistent daily adoption of guidelines is uncertain. Poorly implemented governance systems can frustrate employees, leading to resistance.

3. Productivity Loss Comprehensive antimalware scans, software upgrades, hardware repairs, and backups can impact productivity. Although cybersecurity is essential, it requires significant computing and human resources. Delays in critical operations may occur if security measures encounter problems.

4. Talent and Technology Costs Recruiting and developing an in-house cybersecurity team is challenging and expensive. Cutting-edge data protection technologies also come at a high cost. Businesses must optimize costs, possibly through outsourcing DLM tasks or reducing the scope of business intelligence. Efficient compression algorithms and hybrid cloud solutions can help manage storage costs.

Conclusion

The Ponemon Institute found that 67% of organizations are concerned about insider threats. Similar concerns are prevalent worldwide. IBM estimates that the average cost of data breaches will reach 4.2 million USD in 2023. The risks of data loss, unauthorized access, and insecure PII processing are rising. Stakeholders demand compliance with data protection norms and will penalize failures in governance.

Implementing best practices in data lifecycle management, such as end-to-end encryption, version control systems, 2FA, VPNs, antimalware tools, and employee education, can significantly enhance security. Data protection officers and DLM managers can learn from expert guidance, cybersecurity journals, and industry peers’ insights to navigate complex challenges. Adhering to privacy and governance directives offers legal, financial, social, and strategic advantages, boosting long-term resilience against the evolving threats of the information age. Utilizing data governance consulting services can further ensure your company is protected against these threats.