An Oproma expert completes a content server migration at his desk, sitting in front of monitors showing OpenText's website.

OpenText content server migration

9500000
Assets Discovered
3360000
Total files migrated
1360000
Files migrated from Containers
2610000
Files Disposed

Project overview

A Federal Government of Canada department required information intelligence and professional services to automate the identification of unstructured and semi-structured content, perform auto-classification, and apply disposition of ROT (Redundant, Obsolete, and Trivial) for over 9 million documents and files on a Network Shared Drive as well as other unstructured repositories such as the Collaboration Portal (SharePoint), employee user drives, which include Microsoft Email .PST file content.

Client:
Open Text

MiCore

The MiCore platform was vital in exhaustively cataloguing all Shared Drive content and providing actionable analytics that allowed the client to develop comprehensive business rules to perform the migration of classified content to OTCS (OpenText Content Server) – also known as GCDocs.

Pertinent metadata from the original source file including document language, original source path, original created date, original modified date, original author and original owner were added as custom meta-data.

As files were migrated, the original file was deleted, and a stub (shortcut) was left on the shared drive pointing to the new files in GCDocs. Throughout the engagement, AI was leveraged using natural language processing (NLP) and Entity Extraction (EE) to identify, normalize, classify and transform the digital assets.

Value realization

  • Consistent and reliable digital transformation outcomes based upon easily defined and reusable business rules
  • Speed and accuracy of transformations
  • Rules-based normalization of metadata
  • Ability to merge content from multiple sources to generate a holistic view of content and assets
  • Automatic migration of any related assets into the appropriate target location

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