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Preserving the Past and Securing the Future: Legacy Data Management with a Data-Driven Approach

As businesses evolve, so do their data systems and storage technologies. The changing technology landscape has made it increasingly challenging for organizations to manage legacy data effectively, as it is often stored in outdated formats that are no longer compatible with modern systems. To mitigate compliance risks associated with legacy data management, organizations must be able to convert legacy data to modern, open formats that are widely supported.

Additionally, it’s important to recognize that digital media has a fixed life, which can pose a challenge for organizations looking to preserve legacy data. Unlike paper, which can last for up to 300 years, digital media can degrade over time, resulting in data loss and other issues. This underscores the importance of implementing effective data governance and data stewardship practices, including regular backups and data migration, to ensure that legacy data remains accessible and usable over time.

Amit Dhawan
CISO & DPO
Quantiphi

By implementing best practices for legacy data management and staying up-to-date with changing technology trends, organizations can effectively mitigate compliance risks associated with legacy data and leverage the value of their data to drive business growth and success. Over the course of this article, I will try to articulate the questions raised by Kanchi Shah, our moderator, during the “The CXO dialogue – Mitigating compliance risks with legacy data management” and bring out answers in a formal fashion.

What are some of the biggest challenges associated with managing legacy data?

In today’s world of data security and compliance, legacy data management has never been more strategic. Invariably, legacy data management can pose several challenges for organizations, including:

  • Compatibility issues: Legacy data may be stored in obsolete formats, which may not be compatible with modern systems. This can create problems when organizations try to migrate data to new systems or integrate legacy data with new applications.
  • Data quality: Legacy data may be incomplete, inaccurate, or inconsistent, making it difficult for organizations to trust the data and use it effectively.
  • Security risks: Legacy data may contain sensitive information that needs to be protected from unauthorized access. However, legacy systems may have weak security controls, making it challenging to safeguard the data adequately.
  • Lack of expertise: Legacy systems may require specialized skills and knowledge to maintain and manage effectively. As technology evolves, it can become increasingly difficult to find personnel with the necessary skills to manage legacy systems.
  • Compliance challenges: Regulations and compliance requirements, like Privacy, are constantly evolving, and organizations must ensure that legacy data is managed in accordance with current regulations.
  • Cost: Managing legacy systems and data can be expensive, as it may require specialized hardware, software, and personnel. As a result, organizations may be reluctant to invest resources in managing legacy data, which can create further challenges down the road.

What are some of the imperatives of managing legacy data effectively?

Migrating legacy data can be a challenging task for any organization, especially when you are trying to migrate to the Cloud or an application. Managing legacy data effectively is essential for any organization that wants to migrate to a new platform. Some of the imperatives include:

  • Planning: Organizations must develop a clear plan, including inventory of all data, for migrating it to the cloud or on-prem server.
  • Data mapping: It is important to map the data between legacy & other applications, and also understand its future use.
  • Data security: Security is a critical concern and it is important to ensure that sensitive data is adequately protected during the migration process.
  • Testing: Organizations must thoroughly test the migration process to identify any issues or errors that may arise during the migration process.
  • Compliance: Organizations must ensure that data is managed in accordance with current regulations, and that any potential compliance risks are identified and addressed during the migration process.
  • Change management: Migrating legacy data can be a complex process that can impact business operations. Organizations must manage change effectively, including communicating with stakeholders, training staff, and ensuring that the new system is integrated into business processes.

How to preserve legacy data in a format that can be accessed and used in the future?

Preserving legacy data in a format that can be accessed and used in the future is essential to ensure that their data remains valuable and usable over time. Here are some ways that organizations can proactively implement to ensure that their legacy data is preserved:

  • Convert data to an open format: Legacy data may be converted and stored in open & standardized formats to prevent obsolescence over time.
  • Use data archiving solutions: Archiving solutions can be used to store legacy data in a secure, accessible format that can be accessed and used in the future. This ensures that data is preserved and can be used for regulatory compliance or other purposes.
  • Implement data governance policies: Data governance policies can help organizations ensure that data is managed and preserved effectively over time. This includes policies for data retention, data access, and data security.

What are some of the risks associated with maintaining legacy data systems and how can they be mitigated?

Maintaining legacy data systems can pose several risks to organizations, including:

  • Security risks: Legacy systems may have security vulnerabilities that can be exploited by attackers. This can result in data breaches, unauthorized access to sensitive information, and other security incidents.
  • Compliance risks: Regulations and compliance requirements are constantly evolving, and legacy systems may not be designed to meet current compliance standards. This can result in compliance violations, fines, and other legal issues.
  • Cost risks: Maintaining legacy systems can be expensive, as it may require specialized hardware, software, and personnel. This can result in increased costs for the organization.
  • Operational risks: Legacy systems may be less efficient and less reliable than modern systems, which can result in operational issues such as system downtime and data loss.

To mitigate these risks, organizations can take several steps, including upgrading the legacy systems, implementing compensating controls if direct controls would not work, and finally, test and monitor the access of these systems. Data backups and a risk management strategy should nevertheless be in place for these initiatives.

How to create a data-driven decision-making culture focused on leveraging legacy data in the decision-making process?

The saying “In God we trust, rest all should bring Data” is an apt example of the importance data has for organizations. Creating a culture of data influencing the decision making is essential for organizations that want to leverage the value of legacy or any other data in that process. Here are some ways that organizations can create a culture of data-driven decision-making:

  • Educate employees about the value of data: Organizations should educate employees about the value of data and how it can be used to inform decision-making. This includes providing training on data analysis, visualization, and interpretation.
  • Establish clear data governance policies: Organizations should establish clear data governance policies that outline how data is managed and used within the organization. This includes policies for data access, data security, and data quality.
  • Develop data analytics capabilities: Organizations should develop data analytics capabilities that enable them to analyze and interpret legacy data effectively. This includes investing in tools and technologies that support data analytics, as well as developing skills and expertise in data analytics.
  • Encourage data sharing and collaboration: Organizations should encourage data sharing and collaboration across departments and teams. This includes providing access to data repositories and analytics tools that enable employees to collaborate on data analysis projects.
  • Align data with business objectives: Organizations should align data with their business objectives to ensure that data is used to inform decision-making that is aligned with the organization’s goals and objectives.
  • Recognize and reward data-driven decision-making: Organizations should recognize and reward employees who use data to inform their decision-making. This includes highlighting examples of successful data-driven decision-making and providing incentives for employees who use data effectively.

In conclusion, it is clear that managing and maintaining legacy data is integral to organizational success, especially in today’s data-driven world. While there are some challenges and risks along the way, adopting the right practices and following a strategic approach can help organizations leverage legacy data for decision making.

About the author

Amit Dhawan is currently the CISO & DPO Quantiphi. He has more than 20 years of experience in the IT and information security domain. Before Quantiphi, Dhawan served in leadership roles in Birlasoft as the CISO and Data Privacy officer, eAvighna (his own InfoSec Training & Consulting startup), JP Morgan and American Express driving technology controls and leading the Infosec practices.

Disclaimer: The views expressed in this feature article are of the author. This is not meant to be an advisory to purchase or invest in products, services or solutions of a particular type or, those promoted and sold by a particular company, their legal subsidiary in India or their channel partners. No warranty or any other liability is either expressed or implied.
Reproduction or Copying in part or whole is not permitted unless approved by author.

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