Ensuring your business can secure all communication and data transfer channels indicates a need for extensive planning. You also require talented cybersecurity professionals and long-term risk mitigation strategies. By implementing global data safety standards, your leadership must protect the clients’ sensitive information. This post outlines the best data lifecycle management practices for enhanced security and uninterrupted operationality. 

What is Data Lifecycle Management? 

DLM, or data lifecycle management, encompasses data source listing, streaming, storage, cleansing, sorting, transforming, loading, analytics, visualization, security, and deletion. It prevents data loss and database inconsistencies through regular backups, cloud platforms, and process automation. 

Depending on software programs, file formats, and business correspondence needs, some micro and medium corporations can host their data on-site. However, this approach exposes those business intelligence (BI) assets to physical damages, fire hazards, or theft. So, companies seeking scalability and virtualized computing leverage data governance consulting services to avoid these threats. 

What is Data Governance? 

Data governance in DLM involves technologies concerning employee identification, user rights management, cybersecurity measures, and robust accountability standards. When an organization embraces data governance, it can successfully combat corporate espionage attempts. Simultaneously, managers can quickly regulate database modifications and intel sharing. 

Examples of data governance can include encryption and biometric authorization interfaces. Consider how end-to-end encryption makes eavesdropping more challenging for unauthorized third parties. Likewise, scanning a retina or thumb impression increases security. Additionally, firewalls help distinguish bad traffic from genuine visitors. 

Best Security Practices in Data Lifecycle Management 

1| Two-Factor Authentication (2FA) 

Cybercriminals often target user entry interfaces, database updates, and intelligence transmission channels. If a password is the only shield defending your organization’s intellectual property (IP) from digital intruders, cybersecurity risks are too high. According to established business strategy support, you can reduce the risks using multiple authorization mechanisms. 

What is multi-factor authentication? It incorporates hard-to-replicate identifiers to safeguard your firm’s IT resources from password theft. For instance, the 2FA framework, the easiest and most recognized approach, can demand a one-time password (OTP) whenever the user wants to modify, remove, or distribute an intelligence asset. 

DLM specialists can also introduce many distinct 2FA options. Doing so confuses individuals wanting unauthorized access. After all, they must guess whether an employee uses OTP-based 2FA or biometric 2FA. As a result, your business’s resilience against password-related security risks increases, improving data lifecycle management and governance. 

2| Version Control, Changelog, and File History 

Despite sharing some recording activities, version control differs from the changelog. Both belong to the best security practices that experienced data lifecycle managers adopt and promote. 

A changelog lists all remarkable edits and removals in the project documentation. On the other hand, version control creates groups of those changes, highlighting milestones in a “continuous improvement” strategy. 

Changelog and version control, along with file history tools in a device’s operating system, facilitate fast conflict detection. For example, if a program or a product suddenly exhibits undesirable performance, a recent change in its principal design data might be responsible. Therefore, cybersecurity experts, business strategists, and report authors will check changelogs and restorable file versions. 

You can resolve a minor bug through small and quick patches. Still, you need detailed records describing earlier versions if the entire system collapses. Likewise, file history is a less reliable but faster alternative to full-disk cloning in data backup methods. That means the same storage media will duplicate files and metadata in separate regions, mitigating localized data corruption risks. 

3| Encryption, Virtual Private Networks, and Antimalware 

A virtual private network (VPN) protects the company’s employees, IT resources, and business correspondence from online trackers. The corporate world relies on VPNs to grant remote workers more secure access to core databases and applications. As a result, communication stays private even if stakeholders, like overseas suppliers, were to use public WiFi networks. 

The Internet Service Providers (ISPs) will see the VPN server’s details, usage time, and encrypted data volume being uploaded or downloaded. However, they can neither track nor over-regulate what your employees do online after connecting to this server. If you work in clinical research or collect personally identifiable information (PII) of consenting consumers, you must get an organization-wide VPN as soon as possible. 

Aside from VPN and firewalls, encouraging all stakeholders to interact using fully encrypted communication channels is indispensable. They must also follow safety guidelines like periodic malware scanning and auditing data sources for cybersecurity risks. 

Security Challenges in Data Lifecycle Management 

1| Employee Education 

The best DLM and BI security practices will increase your enterprise’s resilience after your employees understand them. So, you want to host periodic training programs to educate new hires and experienced executives on the latest cybersecurity implementations. Otherwise, employees will struggle to complete their work as authentication tools and safety requirements keep changing. 

2| Voluntary Compliance 

“Convenience versus security” is a timeless debate between data protection officers (DPOs) and other professionals. While most employees will complete security training, whether they adopt all guidelines every day is often uncertain. Besides, poorly implemented governance systems can frustrate them. Consider how they will react if the 2FA tools lock them out of the company’s servers due to technical errors.  

3| Productivity Loss 

Antimalware scans take longer to complete when you want to check petabytes of data volume in one go. Likewise, upgrading software, repairing hardware, creating backups, and tracking bugs require computing and human resources. Although cybersecurity in data lifecycle management is essential, it has a noticeable impact on productivity. Unless computers and antimalware systems become faster, this issue will persist. Moreover, if security measures develop problems, you will need to delay critical operations. 

4| Talent and Technology Costs 

Recruiting and nourishing the right talent to create an effective in-house cybersecurity unit is arduous. Furthermore, cutting-edge data protection technologies are expensive, given the value they add and the demand for digital risk management. So, businesses must use cost optimization strategies, like outsourcing data lifecycle management tasks or reducing business intelligence scope. They also require more efficient compression algorithms and a hybrid cloud to handle storage costs. 

Conclusion 

Ponemon Institute found that 67% of organizations worry about insider threats. Similar statistics make the headlines worldwide. Indeed, rogue employees selling your trade secrets, insider trading, and corporate espionage are complex but real problems. Meanwhile, IBM estimates that the mean data breach costs affecting enterprises will rise to 4.2 million US dollars throughout 2023. 

On the other hand, the financial materiality risks of data loss, unauthorized access, and insecure PII processing have skyrocketed. Consumers, regulators, investors, and suppliers want your company to comply with data protection norms. They will undoubtedly penalize you due to governance failures. 

However, you can apply the best practices for data lifecycle management that have enhanced security and addressed stakeholder concerns for many. End-to-end encryption, version control systems, 2FA frameworks, VPNs, antimalware tools, and employee education are suitable for the start. 

DPOs and data lifecycle managers can also learn a lot from expert guidance, cybersecurity journals, and industry peers’ insights. Therefore, complying with privacy and governance directives is possible despite the complex hurdles. Remember, the legal, financial, social, and strategic advantages of safe DLM will boost your competitiveness. They matter to your organization’s long-term resilience against the ever-increasing evils of the information age threatening your data operations and stakeholder trust.