4 Reasons to Migrate Enterprise Vault Data to Office 365
Learn about 4 critical reasons why it's important to migrate your legacy archive data from Enterprise Vault to Office 365
Legacy data refers to information that is stored in outdated or obsolete systems, formats, or technologies. This ...
Legacy data refers to information that is stored in outdated or obsolete systems, formats, or technologies. This includes structured and unstructured data. It includes data generated by humans as well as machine-generated. While legacy data may not be actively used, at least, if it is used, it's not used regularly, it is often crucial for legal, regulatory, or historical reasons. Managing legacy data can be challenging, but it is critical for ensuring compliance, improving data management, and making better business decisions.
In this guide we'll go on a deep-dive to explore some of the types of legacy data, as well as the challenges of managing it and the options available for your organization. We'll also cover best practices for archiving, security, compliance and legacy data migration. Whatever your role is in your organization this guide will help you to understand legacy data, how to manage and how to ensure its usefulness to your business.
Legacy data refers to information that is stored in outdated or obsolete systems, formats, or technologies that is often difficult to access. This data was created years ago and may not be actively used by an organization anymore. However, it is often crucial for legal, regulatory / compliance, or historical reasons.
Examples of legacy data include:
The challenge with legacy data is that it can be difficult to access and use, especially if the systems and technologies used to store the data are no longer supported or compatible with current technology. Sometimes more up to date technology simply can't access, or even open, the legacy data file formats. Effective management of legacy data is critical for ensuring compliance, improving data management, and making better business decisions.
Legacy data can be stored in a variety of formats, such as paper records, magnetic tape, floppy disks, and early versions of file formats (eg early versions of Microsoft Excel). It can also be stored in outdated software or hardware systems that are no longer supported or used (eg software like Lotus 1-2-3).
In some cases, the data may be stored in proprietary formats that require specific software or hardware to access. Managing legacy data requires a careful approach to ensure that the data remains secure, accessible, and compliant with legal and regulatory requirements. It often involves migrating, archiving, and preserving the data in a way that ensures it remains accessible and usable over time. Effective management of legacy data can help organizations unlock valuable insights and information that can support better decision-making and improve overall business operations.
Managing legacy data is important for several reasons:
Compliance: Legacy data may be subject to legal or regulatory requirements that mandate how it should be stored, managed, protected and expired. Failure to comply with these requirements can result in legal and financial penalties, reputational damage, and loss of business.
Improved data management: Legacy data can be a valuable source of information that can be used to inform business decisions, identify trends, and support strategic planning. Effective management of legacy data can ensure that it remains accessible and usable, even as new technologies emerge.
Better decision-making: By analyzing legacy data, organizations can gain insights into past business operations and use this information to improve future decision-making. Legacy data can also help organizations identify patterns and details that can help product development, define marketing strategies, and other key business decisions.
Enhanced customer service: Access to historical data is critical for providing high-quality customer service. For example, having access to a customer's purchase history can help a business tailor its products and services to better meet their needs.
Cost savings: By managing legacy data effectively, organizations can avoid the costs associated with maintaining outdated systems and technologies. This can include costs associated with hardware and software maintenance, data migration, and compliance-related expenses.
There are several types of legacy data that organizations may need to manage. Including:
This is data that is stored in a structured format, such as a database or spreadsheet. Structured data may include customer records, financial data, inventory data, employee records, sales data, medical records, website analytics and more.
This is data that is not organized in a structured format, such as emails, documents, images, and videos. Unstructured data may be stored in a variety of formats and will probably require specialized tools to manage and analyze.
This is data that is generated by machines, such as log files, sensor data, and machine-generated reports. Machine-generated data may be produced in large volumes and may require specialized tools to process and analyze.
This is data that is created by humans. It includes emails, chat logs, documents, spreadsheets, presentations, and social media posts. Human-generated data may be stored in a variety of formats and may require specific software to access, review and update.
Each of these types of legacy data may require different management strategies and tools to ensure that the data remains accessible and usable over time.
Managing legacy data can be challenging for many reasons, how they affect each individual organization may vary and the importance of these challenges often also varies between organizations and geographies. Here are some of the key challenges:
Compatibility: Legacy data may be stored in outdated formats (such as spreadsheets stored in Lotus 1-2-3 file formats) or systems that are no longer compatible with current technologies (such as data stored on CDROM). This makes it difficult to access, read, or transfer the data.
Accessibility: Even if the data is accessible, it may be difficult to find or retrieve specific pieces of information within the data. This can make it time-consuming and resource-intensive to use the data effectively.
Data quality: Legacy data may contain errors, inconsistencies, or inaccuracies that can make it less useful for analysis or decision-making. Ensuring data quality may require significant effort and resources.
Security: Legacy data may contain sensitive or confidential information that needs to be protected from unauthorized access or breaches. As security threats evolve over time, ensuring the security of legacy data can be a significant challenge especially if some of the legacy systems or software are no longer supported by the original manufacturer.
Cost: Managing legacy data can be expensive, particularly if it involves migrating data to new systems or technologies. The cost of maintaining outdated systems or finding specialized tools, or employees to manage the data can also be significant.
Complexity: Managing legacy data can be complex, particularly if the data is stored in a variety of formats or locations.
Legal and regulatory compliance: Legacy data may be subject to legal and regulatory requirements that mandate how it should be stored, managed, protected and expired. Ensuring compliance with these requirements can be challenging.
In order to overcome these challenges, organizations may need to invest in specialized tools and expertise to effectively manage legacy data. Both of these are likely to incur significant cost. However, by doing so, you can ensure that the data remains accessible, accurate, and secure over time, and can unlock valuable insights and information that can improve business operations and drive success. It can also lead to a reasoned approach to migrate the appropriate legacy data to a more modern, more accessible system.
Here are some of the key reasons why legacy systems can be complex:
Over time, legacy systems can accumulate technical debt, which refers to the cost of maintaining outdated software, hardware, and other technologies. This can make it difficult to upgrade or migrate legacy systems to newer technologies.
Legacy systems may not be designed to work with newer technologies or systems. This can make it challenging to integrate legacy systems with newer tools and technologies, which can result in compatibility issues and errors.
Legacy systems may have been heavily customized to meet the specific needs of an organization, but those needs will likely have changed over time. This can make it difficult to transfer the system to a new environment, as the organization may need to replicate customizations in the new environment or go through a lengthy (and costly) mapping process between legacy and more-modern system.
Legacy systems may have outdated or incomplete documentation, which can make it challenging to understand how the system works and how it should be managed. If the legacy system is no longer supported by the original manufacturer then clarifying the issues with the documentation will be difficult.
Employees who were familiar with legacy systems may retire or move on to other roles in your organization or move to a different organization. This makes it challenging to transfer knowledge about how the legacy system works and how it should be managed by new employees.
Legacy systems may be more vulnerable to security risks than newer systems, as they may not have been designed with modern security threats in mind and the legacy system may no longer be receiving security updates. This can make it challenging to ensure the security of the system and the data it contains. In some organizations this may lead to increasingly restrictive access to potentially valuable legacy data.
Effective management of legacy systems requires specialized expertise and tools. Organizations may need to invest in training employees or hiring outside experts to manage legacy systems effectively.
Here are 5 of the key security risks associated with legacy data:
Outdated security protocols
Legacy data may have been stored using outdated security protocols, which may not be as effective at protecting the data from modern security threats. For example, legacy systems may use weak or no encryption, or they may not have implemented multi-factor authentication. Data being transferred over the wire may also be susceptible to being eavesdropped, potentially by external parties.
Legacy data may be stored in systems that are no longer supported or maintained by the original vendor. This can leave the data vulnerable to security vulnerabilities and (more importantly) exploits that are no longer being patched by the vendor.
Increased attack surface
Legacy data may be stored in systems that are no longer in use or have been almost forgotten about by your organization. This can increase the attack surface of the organization, as attackers may be able to exploit these systems to gain access to sensitive data or to jump over to other internal systems.
Legacy data may be stored in systems that have outdated or ineffective access controls. This can make it easier for unauthorized users to gain access to the data, which can lead to data breaches or other security incidents.
Legacy data may be subject to data integrity issues, which can compromise the accuracy and reliability of the data. For example, legacy data may be subject to data corruption or tampering, which can make it difficult to trust the data or use it effectively.
To mitigate the security risks associated with legacy data, organizations should develop a comprehensive security strategy that takes into account the unique challenges associated with legacy systems and data. This may include implementing strong access controls, additional firewalls, using modern encryption and authentication protocols, regularly patching and updating legacy systems, and monitoring legacy systems for signs of unauthorized access or suspicious activity.
Here are some of the key costs associated with maintaining legacy data:
Legacy data may be stored on hardware or software that is no longer supported by the vendor. This can make it expensive to maintain the hardware or software, as the organization may need to invest in custom maintenance or support services.
Legacy data may not be compatible with newer hardware or software, which can make it expensive to transfer the data to newer systems. The organization may need to invest in migration tools or services to ensure that the data can be transferred accurately and securely.
Legacy data may take up a significant amount of storage space, which can be expensive to maintain over time. In fact some legacy storage platforms may also suffer the issues relating to no longer being supported by the original vendor. The organization may need to invest in additional storage hardware or cloud storage services to ensure that the data can be stored and accessed effectively.
Legacy data may be subject to data integrity issues. To ensure that the data remains usable over time, your organization may need to invest in data cleaning, verification and validation services.
Legacy systems may require specialized expertise to maintain effectively. The organization may need to invest in training programs or outside consultants to ensure that employees have the skills and knowledge needed to manage legacy systems and data. It's also likely that the costs associated with this will begin to increase dramatically as time progresses.
To reduce the costs associated with maintaining legacy data, organizations should consider migrating the data to newer hardware or software systems and storage platforms. This can help reduce hardware and software maintenance costs, as well as storage costs. However, organizations should carefully evaluate the costs and risks associated with data migration, as it can be a complex and challenging process. Ultimately, the best approach, blending data expiration, migration and commitment to legacy systems, will depend on the specific needs and constraints of the organization.
Managing legacy data can provide several benefits for organizations, including:
Improved data access: By managing legacy data effectively, organizations can ensure that the data remains accessible and usable now and in the future. This can help support business continuity and enable employees to access the data they need.
Enhanced data quality: Legacy data can be subject to data integrity issues, such as data corruption or duplication. By managing legacy data effectively, organizations can identify and address these issues, which can help improve the overall quality of the data.
Compliance and legal requirements: Many organizations are required by law to retain certain types of data for a specified period of time. By managing legacy data effectively, organizations can ensure that they are meeting these requirements and avoiding potential legal or regulatory penalties. This can be particularly challenging for enterprise-size organizations that have a global presence.
Improved efficiency: Managing legacy data effectively can help streamline business processes and reduce the time and resources needed to access and use the data. This can help improve operational efficiency and enable employees to focus on other important tasks.
Risk management: Legacy data can be vulnerable to security risks, such as data breaches or unauthorized access. By managing legacy data effectively, organizations can help reduce these risks and protect the data from external as well as internal threats.
Cost savings: Effective management of legacy data can help reduce costs associated with hardware and software maintenance, storage, employee-resources and data migration. By ensuring that the data remains usable and accessible over time, organizations can avoid the costs associated with re-creating or re-acquiring the data in the future - and of course for many organizations that might not even be possible.
Overall, managing legacy data effectively can help organizations leverage the value of their historical data assets, while minimizing the risks and costs associated with maintaining these assets. Organizations need to take a strategic and proactive approach to legacy data management, ensuring that they are able to access and use their legacy data in a way that supports their long-term business goals and objectives.
Compliance with legal and regulatory requirements is a critical aspect of managing legacy data. Many organizations are subject to legal and
regulatory requirements that dictate how they must manage and retain certain types of data, including legacy data. Failure to comply with these requirements can result in legal or financial penalties, damage to an organization's reputation, or other negative consequences.
Here are some of the key considerations for compliance with legal and regulatory requirements:
Organizations must develop and implement data retention policies that specify how long certain types of data must be retained and how they must be managed during that time. An essential part of the policy is also defining how and when data will be expired. These policies must be based on legal and regulatory requirements, as well as business needs and risks.
Organizations must ensure that legacy data is protected from unauthorized access, use, or disclosure. This includes implementing appropriate data security and privacy controls, such as access controls, encryption (while data is in transit, and at rest), and system monitoring.
Organizations must be able to demonstrate that they are complying with legal and regulatory requirements for legacy data. This may include maintaining records of data retention and management activities, conducting audits, and reporting compliance to appropriate authorities.
Different industries may have specific legal and regulatory requirements for managing legacy data. For example, healthcare organizations must comply with the Health Insurance Portability and Accountability Act (HIPAA), which includes specific requirements for the retention and management of medical records and other healthcare data.
Organizations that operate in multiple countries must comply with a variety of international regulations that may apply to legacy data. For example, the General Data Protection Regulation (GDPR) applies to the retention and management of personal data for organizations that operate in the European Union.
To ensure compliance with legal and regulatory requirements for legacy data, organizations must take a proactive and comprehensive approach to data management. This includes developing and implementing data retention policies, implementing appropriate data security and privacy controls, and regularly monitoring and reporting on compliance. By doing so, organizations can help reduce the risks associated with managing legacy data and ensure that they are able to meet their legal and regulatory obligations.
Legacy data archiving is a process of storing inactive or infrequently accessed data from outdated or obsolete systems for long-term retention and future reference. An organization might do this particular task if they can not for certain determine that data has no more business value. The purpose of legacy data archiving is to preserve data that is still relevant (or may still be relevant) but no longer needed in day-to-day operations, and to free up space in the active production system.
The process of legacy data archiving typically involves the following steps:
Identify and categorize the data: Determine which data needs to be archived, based on factors such as regulatory requirements, legal obligations, and business needs. Sometimes there is a lot of data, so organizations would then categorize the data based on its level of importance, so that you can prioritize which data to archive first. One of the other reasons to perform this task is that some archiving platforms might not be able to onboard the data quickly enough.
Define retention policies: Establish guidelines for how long data should be retained in the archive. To do this you will need to take into account regulatory and legal requirements and business needs.
Select an archiving solution: Choose an archiving solution that meets the needs of your organization, such as an on-premises storage system like Enterprise Vault, a cloud storage environment like Microsoft Azure, or a hybrid solution.
Migrate the data: Transfer the selected data from the legacy system to the archiving solution, using data migration tools and techniques. In addition remember that sometimes there is a lot more to performing a data migration than just copying the data from a source environment to a target environment.
Index and search the data: Index the archived data so that it can be easily searched and retrieved in the future. This may involve using metadata to classify and tag the data. It might also involve using a different system to index the data, than to store the data. Consider again the length of time that the data might need to be kept for and choose an appropriate solution.
Manage the archive: Establish procedures for managing the archive, such as monitoring and auditing access to the data, and periodically reviewing and updating the retention policies.
Legacy data archiving provides several benefits, such as reducing storage costs, improving system performance, and ensuring compliance with regulatory requirements. Additionally, archived data can be used for business analytics and reporting, and can provide valuable historical insights into the operations of an organization.
Legacy data preservation is the process of protecting, maintaining, and storing data from outdated or obsolete systems that are no longer in active use. The purpose of legacy data preservation is to ensure the long-term retention and accessibility of important data that may still be relevant for legal, regulatory, or business reasons.
The process of legacy data preservation involves the following steps:
Identify the data: Determine which data needs to be preserved, based on its business value, legal or regulatory requirements, or historical significance within the organization or industry.
Review the data: Evaluate the condition and format of the data to determine whether it is still accessible and usable. This may involve using specialized tools and techniques to read and recover data from obsolete media or software.
Choose preservation methods: Select appropriate preservation methods based on the type and format of the data. This may include data migration to modern storage media, emulation of obsolete hardware and software, or conversion of data to newer file formats.
Store the data: Choose a secure and stable storage environment for the preserved data. Consider whether the storage locks-you-in to keeping that storage for a considerable period of time, holding your data in storage like that might mean additional costs in the future.
Manage the data: Establish procedures for managing the data, including monitoring and auditing access to the data, ensuring regular backups and updates, and periodically reviewing how the data is stored.
Legacy data preservation is critical for organizations that rely on historical data for research, legal or regulatory compliance, or operational continuity. Preserved data can also provide valuable insights into the history and evolution of an organization or industry, and can serve as an important resource for future generations. However, preserving legacy data can be challenging, as it often requires specialized skills and resources to access and maintain data in obsolete formats and systems.
Legacy data retrieval and access refers to the process of finding and accessing data stored in outdated or obsolete systems, applications, or file formats.
The process of legacy data retrieval and access typically involves the following steps:
Identify the data: Determine which data needs to be retrieved, based on its business value, legal or regulatory requirements, or historical significance. Consider that if the data is being accessed frequently costs might be incurred depending on where and how the data is stored.
Locate the data: Determine where the data is stored, whether in an obsolete system or format, or in a modern archive or platform.
Assess the data: Evaluate the condition and format of the data to validate whether it is still accessible and usable.
Extract the data: Extract the data from its original system or format, using specialized tools and techniques to read and convert the data to a modern format.
Transfer the data: Transfer the data to a modern system or format, such as a cloud-based storage system or a newer application.
Index and search the data: Index the retrieved data so that it can be easily searched and retrieved in the future. This may involve using metadata to classify and tag the data. The index might be an external system, if so, ensure that it adheres to industry standards and that storage of the appropriate indices is considered in the overall data storage plan.
Manage the data: Establish procedures for managing the retrieved data, including monitoring and auditing access to the data, ensuring regular backups and updates.
Legacy data retrieval and access can be a complex and time-consuming process, as it often requires specialized skills and tools to access and retrieve data from obsolete systems or formats. However, it is critical for organizations that rely on historical data for research, legal or regulatory compliance, or operational continuity. Retaining access to legacy data can also provide valuable insights into the history and evolution of an organization or industry, and can serve as an important resource for future generations.
Legacy data security and compliance refer to the processes and procedures used to protect, secure and ensure that legacy data is handled in a manner that is compliant with relevant laws, regulations, and policies. This is especially important for organizations that store sensitive information in legacy systems or formats, which may be more vulnerable to security breaches or non-compliance with current data protection regulations.
The process of legacy data security and compliance typically involves the following steps:
Identify the data: Determine which legacy data requires protection and compliance, based on its business value, legal or regulatory requirements, or the sensitivity of the data. Consider also the differences within an industry based on the geography of where the data is stored, or accessed from, or both.
Assess the risks: Evaluate the risks to the legacy data, such as unauthorized access, data breaches, or non-compliance with relevant regulations. It's worth considering as many types of risk as possible.
Develop a security and compliance plan: Create a plan to secure and protect the legacy data and ensure compliance with applicable regulations. This may include measures such as data encryption, access controls, and regular monitoring of the data. The plan should also consider what actions will be taken if unauthorized access is obtained to the data.
Implement security and compliance measures: Implement the plan and take steps to secure the legacy data and ensure compliance. This may involve using specialized security tools and technologies, such as firewalls, and intrusion detection systems.
Monitor and audit the data: Regularly monitor and audit access to the legacy data, and review data usage to ensure compliance with relevant regulations.
Plan for disaster recovery: Develop a plan for disaster recovery in the event of a security breach or other unexpected event that could compromise the security or integrity of the legacy data.
Legacy data security and compliance are critical for organizations that store sensitive data in legacy systems or formats. Failure to adequately protect or ensure compliance with this data can result in financial penalties, legal liabilities, and damage to an organization's reputation. Therefore, it is important to implement appropriate security and compliance measures and regularly review and update these measures to ensure that they remain effective and up-to-date with changing regulations and security threats.
Legacy data migration is the process of transferring data from an old or outdated system to a new one. It is often necessary when organizations upgrade their technology platforms or adopt new systems that require data from previous systems.
The migration process involves extracting the legacy data from the old system, transforming it into a format suitable for the new system, and loading (sometimes called importing or ingesting) it into the new system. It also often involves many other steps aside from just copying the data.
Legacy data migration can be a complex and challenging process, as the data may be stored in a variety of formats and structures, and may be distributed across multiple systems. It requires careful planning, testing, and execution to ensure that the data is transferred accurately and securely, and that the new system is able to use it effectively.
Legacy data migration is important for organizations as it enables them to take advantage of new technology platforms and systems, while preserving valuable data from previous systems. It also helps to reduce the risks associated with data loss, corruption, or inaccessibility, and ensures that business operations can continue without interruption.
There are several types of legacy data migrations, including:
Platform migration: This type of migration involves transferring data from one software platform to another, such as moving data from a legacy system to a cloud-based system.
Database migration: This type of migration involves moving data from one database to another, such as upgrading from a traditional database system to a more modern one.
Application migration: This type of migration involves moving data from one application to another, such as migrating from a legacy CRM system to a new one.
Storage migration: This type of migration involves moving data from one storage system to another, such as moving data from tape backups to a disk-based system.
Server migration: This type of migration involves moving data from one server to another, such as transferring data from an outdated server to a new one.
Format migration: This type of migration involves converting data from one format to another, such as converting data from an outdated file format to a newer one.
Cloud migration: This type of migration involves moving data from on-premises servers to cloud-based systems, such as migrating from a legacy data center to a cloud infrastructure. Cloud migration often has many additional advantages (around data accessibility) but also comes with its own risks.
Each type of data migration requires careful planning and execution to ensure a successful transition of the data from the legacy system to the new system.
Another way to look at data migrations is to think about migrating user data, versus system collected journal data. Migrating legacy user data and legacy journal data can be a challenging task, particularly if the data is stored in outdated formats or on obsolete systems. In general, legacy user data refers to the information and files that were created or stored on older systems, while legacy journal data refers to the system logs and records that were generated by older operating systems or applications.
When migrating legacy user data, one of the biggest challenges is ensuring that the data is still accessible and usable on the new system. In addition during any kind of data migration exercise a migration project team should try to ensure seamless, uninterrupted access to the data, even while it is being migrated. Typically user data will include all of the data generated by current employees, and employees who have left the organization.
It is likely that legacy user data such as emails or data stored in legacy archive systems like Enterprise Vault will consist of:
Migrating legacy journal data can also be a challenge. Consider a typical scenario where email data has been journaled by Microsoft Exchange into an on-premise system like Enterprise Vault for more than a decade. There will hundreds of millions of items and terabytes of data to move from a single, or a few, data repositories. All of that migration needs to happen while legal teams are still able to perform eDiscovery and compliance activities. A tricky challenge for many organisations!
It is likely that legacy journal data, particularly from a messaging system like Microsoft Exchange with data stored in Enterprise Vault will consist of:
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