Utilize a Three-Phase Data Migration Framework for EDiscovery

In a blog post on the Relativity website, Sara Anwar explains how Elevate employs a three-phase data migration framework for eDiscovery platforms. This method streamlines the migration process while adhering to best practices and reducing the complexities associated with data migrations. It also maintains the quality and usability of essential data.

The first phase emphasizes preparation and planning. It involves coordination meetings, creating a migration tracker and checklist, and tailoring workspace templates. A kickoff call is critical to understanding platform operations and streamlining the process. Additional steps include organizing single sign-on methods and identifying automation opportunities to reduce manual tasks.

Execution is the second phase, which focuses on accurately exporting and importing data. It includes systematically exporting data like produced files, metadata, and work products while generating cross-reference files for field mapping. Key tasks involve integrating production values, aligning fields, and preparing search term reports and saved searches. A cross-reference report ensures data integrity by tracking all work products, safeguarding against data loss or alteration.

In the final phase, comprehensive quality checks verify data accuracy, metadata, relationships, and functionalities. A detailed checklist documents all checks performed, enabling client review and confirmation. After validation, source data is securely transferred or deleted. 

Double-checking ensures all data and functionalities from the old system transition seamlessly, maintaining integrity and enhancing capabilities in the new environment. Verifying the transfer of all data and work product — documents, coding, production, searches, search terms, and highlighting — is crucial. Documentation is necessary for data that has not been migrated.  

Data migration is a critical aspect of eDiscovery, requiring precise planning, execution, and assurance to ensure seamless transitions, minimal disruption, and data fidelity. The three-phase data migration framework simplifies and streamlines this process.